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Author-wise

Adam Paszke

Paper Name Status Topic Category Year Conference Author Summary Link
0 Evaluation of neural network architectures for embedded systems Read CNNs, CV , Image Comparison 2017 IEEE ISCAS Adam Paszke, Alfredo Canziani, Eugenio Culurciello Compare CNN classification architectures on accuracy, memory footprint, parameters, operations count, inference time and power consumption. link

Aditya Ramesh

Paper Name Status Topic Category Year Conference Author Summary Link
0 DALL·E: Creating Images from Text Pending Image , Text , Transformers 2021 Blog Aditya Ramesh, Gabriel Goh, Ilya Sutskever, Mikhail Pavlov, Scott Gray link

Agata Mosinska

Paper Name Status Topic Category Year Conference Author Summary Link
0 Topological Loss: Beyond the Pixel-Wise Loss for Topology-Aware Delineation Pending Image , Loss Function, Segmentation 2018 CVPR Agata Mosinska, Mateusz Koziński, Pablo Márquez-Neila, Pascal Fua link

Alec Radford

Paper Name Status Topic Category Year Conference Author Summary Link
0 GPT-2 (Language Models are Unsupervised Multitask Learners) Pending Attention, Text , Transformers 2019 Alec Radford, Dario Amodei, Ilya Sutskever, Jeffrey Wu link
1 Improved Techniques for Training GANs Pending GANs, Image Semi-Supervised 2016 NIPS Alec Radford, Ian Goodfellow, Tim Salimans, Vicki Cheung, Wojciech Zaremba, Xi Chen link
2 CLIP: Connecting Text and Images Pending Image , Text , Transformers Multimodal, Pre-Training 2021 arXiv Alec Radford, Ilya Sutskever, Jong Wook Kim link

Aleksander Madry

Paper Name Status Topic Category Year Conference Author Summary Link
0 How Does Batch Normalization Help Optimization? Pending NNs, Normalization Optimizations 2018 arXiv Aleksander Madry, Andrew Ilyas, Dimitris Tsipras, Shibani Santurkar link

Alexandre Alahi

Paper Name Status Topic Category Year Conference Author Summary Link
0 Perceptual Losses for Real-Time Style Transfer and Super-Resolution Pending Loss Function, NNs 2016 ECCV Alexandre Alahi, Justin Johnson, Li Fei-Fei link

Alexei A. Efros

Paper Name Status Topic Category Year Conference Author Summary Link
0 Pix2Pix: Image-to-Image Translation with Conditional Adversarial Nets Read GANs, Image 2017 CVPR Alexei A. Efros, Jun-Yan Zhu, Phillip Isola, Tinghui Zhou Image to image translation using Conditional GANs and dataset of image pairs from one domain to another. link
1 CycleGAN: Unpaired Image-To-Image Translation Using Cycle-Consistent Adversarial Networks Pending GANs, Image Architecture 2017 ICCV Alexei A. Efros, Jun-Yan Zhu, Phillip Isola, Taesung Park link

Alexey Dosovitskiy

Paper Name Status Topic Category Year Conference Author Summary Link
0 Vision Transformer: An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Pending Attention, Image , Transformers 2021 ICLR Alexey Dosovitskiy, Jakob Uszkoreit, Lucas Beyer, Neil Houlsby link

Alexis Conneau

Paper Name Status Topic Category Year Conference Author Summary Link
0 Phrase-Based & Neural Unsupervised Machine Translation Pending NMT, Text , Transformers Unsupervised 2018 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link
1 Unsupervised Machine Translation Using Monolingual Corpora Only Pending GANs, NMT, Text , Transformers Unsupervised 2017 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link
2 Cross-lingual Language Model Pretraining Pending NMT, Text , Transformers Unsupervised 2019 arXiv Alexis Conneau, Guillaume Lample link

Alfredo Canziani

Paper Name Status Topic Category Year Conference Author Summary Link
0 Evaluation of neural network architectures for embedded systems Read CNNs, CV , Image Comparison 2017 IEEE ISCAS Adam Paszke, Alfredo Canziani, Eugenio Culurciello Compare CNN classification architectures on accuracy, memory footprint, parameters, operations count, inference time and power consumption. link

Ali Farhadi

Paper Name Status Topic Category Year Conference Author Summary Link
0 VisualCOMET: Reasoning about the Dynamic Context of a Still Image Pending AGI, Dataset, Image , Text , Transformers 2020 ECCV Ali Farhadi, Chandra Bhagavatula, Jae Sung Park, Yejin Choi link

Alimohammad Beigi

Paper Name Status Topic Category Year Conference Author Summary Link
0 Large Language Models for Data Annotation: A Survey This week Dataset, Generative, Large-Language-Models Prompting, Tips & Tricks 2024 arXiv Alimohammad Beigi, Zhen Tan link

Anant Jain

Paper Name Status Topic Category Year Conference Author Summary Link
0 Breaking neural networks with adversarial attacks Pending CNNs, Image Adversarial 2019 Blog Anant Jain link

Andreas Mayr

Paper Name Status Topic Category Year Conference Author Summary Link
0 Self-Normalizing Neural Networks Pending Activation Function, Tabular Optimizations, Tips & Tricks 2017 NIPS Andreas Mayr, Günter Klambauer, Thomas Unterthiner link

Andrew G. Howard

Paper Name Status Topic Category Year Conference Author Summary Link
0 MobileNet (Efficient Convolutional Neural Networks for Mobile Vision Applications) Pending CNNs, CV , Image Architecture, Optimization-No. of params 2017 arXiv Andrew G. Howard, Menglong Zhu link

Andrew Ilyas

Paper Name Status Topic Category Year Conference Author Summary Link
0 How Does Batch Normalization Help Optimization? Pending NNs, Normalization Optimizations 2018 arXiv Aleksander Madry, Andrew Ilyas, Dimitris Tsipras, Shibani Santurkar link

Anselm Levskaya

Paper Name Status Topic Category Year Conference Author Summary Link
0 Reformer: The Efficient Transformer Read Attention, Text , Transformers Architecture, Optimization-Memory, Optimization-No. of params 2020 arXiv Anselm Levskaya, Lukasz Kaiser, Nikita Kitaev Overcome time and memory complexity of Transformers by bucketing Query, Keys and using Reversible residual connections. link

Antoine Bosselut

Paper Name Status Topic Category Year Conference Author Summary Link
0 COMET: Commonsense Transformers for Automatic Knowledge Graph Construction Pending AGI, Text , Transformers 2019 ACL Antoine Bosselut, Hannah Rashkin, Yejin Choi link

Ari S. Morcos

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs Pending CNNs, Image 2020 arXiv Ari S. Morcos, David J. Schwab, Jonathan Frankle link

Ashish Vaswani

Paper Name Status Topic Category Year Conference Author Summary Link
0 Attention is All you Need Read Attention, Text , Transformers Architecture 2017 NIPS Ashish Vaswani, Illia Polosukhin, Noam Shazeer, Łukasz Kaiser Talks about Transformer architecture which brings SOTA performance for different tasks in NLP link

Asim Kadav

Paper Name Status Topic Category Year Conference Author Summary Link
0 Pruning Filters for Efficient ConvNets Pending CNNs, CV , Image Optimization-No. of params 2017 arXiv Asim Kadav, Hao Li link

Augustus Odena

Paper Name Status Topic Category Year Conference Author Summary Link
0 SAGAN: Self-Attention Generative Adversarial Networks Pending Attention, GANs, Image Architecture 2018 arXiv Augustus Odena, Dimitris Metaxas, Han Zhang, Ian Goodfellow link

Bharath Hariharan

Paper Name Status Topic Category Year Conference Author Summary Link
0 Few-Shot Learning with Localization in Realistic Settings Pending CNNs, Image Few-shot-learning 2019 CVPR Bharath Hariharan, Davis Wertheimer link
1 Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition Pending CNNs, Image Few-shot-learning 2020 CVPR Bharath Hariharan, Davis Wertheimer, Luming Tang link

Boaz Barak

Paper Name Status Topic Category Year Conference Author Summary Link
0 Deep Double Descent: Where Bigger Models and More Data Hurt Pending NNs 2019 arXiv Boaz Barak, Gal Kaplun, Ilya Sutskever, Preetum Nakkiran, Tristan Yang, Yamini Bansal link

Carroll L. Wainwright

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training language models to follow instructions with human feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Semi-Supervised 2022 arXiv Carroll L. Wainwright, Diogo Almeida, Jan Leike, Jeff Wu, Long Ouyang, Pamela Mishkin, Paul Christiano, Ryan Lowe, Xu Jiang This paper presents InstructGPT, a model fine-tuned with human feedback to better align with user intent across various tasks. Despite having significantly fewer parameters than larger models, InstructGPT outperforms them in human evaluations, demonstrating improved truthfulness, reduced toxicity, and minimal performance regressions on public NLP datasets, highlighting the potential of fine-tuning with human feedback for enhancing language model alignment with human intent. link

Chandra Bhagavatula

Paper Name Status Topic Category Year Conference Author Summary Link
0 VisualCOMET: Reasoning about the Dynamic Context of a Still Image Pending AGI, Dataset, Image , Text , Transformers 2020 ECCV Ali Farhadi, Chandra Bhagavatula, Jae Sung Park, Yejin Choi link
1 Symbolic Knowledge Distillation: from General Language Models to Commonsense Models Pending Dataset, Text , Transformers Optimizations, Tips & Tricks 2021 arXiv Chandra Bhagavatula, Jack Hessel, Peter West, Yejin Choi link

Christian Buck

Paper Name Status Topic Category Year Conference Author Summary Link
0 Decoding a Neural Retriever’s Latent Space for Query Suggestion Pending Text Embeddings, Latent space 2022 arXiv Christian Buck, Leonard Adolphs, Michelle Chen Huebscher link

Christian Szegedy

Paper Name Status Topic Category Year Conference Author Summary Link
0 Inception-v1 (Going Deeper With Convolutions) Read CNNs, CV , Image Architecture 2015 CVPR Christian Szegedy, Wei Liu Propose the use of 1x1 conv operations to reduce the number of parameters in a deep and wide CNN link

Colin Raffel

Paper Name Status Topic Category Year Conference Author Summary Link
0 T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Read Attention, Text , Transformers 2020 JMLR Colin Raffel, Noam Shazeer, Peter J. Liu, Wei Liu, Yanqi Zhou Presents a Text-to-Text transformer model with multi-task learning capabilities, simultaneously solving problems such as machine translation, document summarization, question answering, and classification tasks. link

Danqi Chen

Paper Name Status Topic Category Year Conference Author Summary Link
0 SpanBERT: Improving Pre-training by Representing and Predicting Spans Read Question-Answering, Text , Transformers Pre-Training 2020 TACL Danqi Chen, Mandar Joshi A different pre-training strategy for BERT model to improve performance for Question Answering task. link

Dario Amodei

Paper Name Status Topic Category Year Conference Author Summary Link
0 GPT-2 (Language Models are Unsupervised Multitask Learners) Pending Attention, Text , Transformers 2019 Alec Radford, Dario Amodei, Ilya Sutskever, Jeffrey Wu link

David Berthelot

Paper Name Status Topic Category Year Conference Author Summary Link
0 BEGAN: Boundary Equilibrium Generative Adversarial Networks Pending GANs, Image 2017 arXiv David Berthelot, Luke Metz, Thomas Schumm link

David J. Schwab

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs Pending CNNs, Image 2020 arXiv Ari S. Morcos, David J. Schwab, Jonathan Frankle link

David Silver

Paper Name Status Topic Category Year Conference Author Summary Link
0 MuZero: Mastering Go, chess, shogi and Atari without rules Pending Reinforcement-Learning 2020 Nature David Silver, Demis Hassabis, Ioannis Antonoglou, Julian Schrittwiese link

Davis Wertheimer

Paper Name Status Topic Category Year Conference Author Summary Link
0 Few-Shot Learning with Localization in Realistic Settings Pending CNNs, Image Few-shot-learning 2019 CVPR Bharath Hariharan, Davis Wertheimer link
1 Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition Pending CNNs, Image Few-shot-learning 2020 CVPR Bharath Hariharan, Davis Wertheimer, Luming Tang link

Dedy Kredo

Paper Name Status Topic Category Year Conference Author Summary Link
0 Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering Pending Large-Language-Models Prompting, Tips & Tricks 2024 arXiv Dedy Kredo, Itamar Friedman, Tal Ridnik This paper introduces AlphaCodium, a novel test-based, multi-stage, code-oriented iterative approach for improving the performance of Language Model Models (LLMs) on code generation tasks. link

Demis Hassabis

Paper Name Status Topic Category Year Conference Author Summary Link
0 MuZero: Mastering Go, chess, shogi and Atari without rules Pending Reinforcement-Learning 2020 Nature David Silver, Demis Hassabis, Ioannis Antonoglou, Julian Schrittwiese link

Denny Zhou

Paper Name Status Topic Category Year Conference Author Summary Link
0 Chain of Thought Prompting Elicits Reasoning in Large Language Models Pending Question-Answering, Text , Transformers 2022 arXiv Denny Zhou, Jason Wei, Xuezhi Wang link

Dian Yu

Paper Name Status Topic Category Year Conference Author Summary Link
0 ReAct: Synergizing Reasoning and Acting in Language Models Pending Generative, Large-Language-Models, Text Optimizations, Tips & Tricks 2023 ICLR Dian Yu, Izhak Shafran, Jeffrey Zhao, Karthik Narasimhan, Nan Du, Shunyu Yao, Yuan Cao This paper introduces ReAct, a novel approach that leverages Large Language Models (LLMs) to interleave reasoning traces and task-specific actions. ReAct outperforms existing methods on various language and decision-making tasks, addressing issues like hallucination, error propagation, and improving human interpretability and trustworthiness. link

Diederik P. Kingma

Paper Name Status Topic Category Year Conference Author Summary Link
0 Adam: A Method for Stochastic Optimization Pending NNs, Optimizers 2015 ICLR Diederik P. Kingma, Jimmy Ba link

Dimitris Metaxas

Paper Name Status Topic Category Year Conference Author Summary Link
0 SAGAN: Self-Attention Generative Adversarial Networks Pending Attention, GANs, Image Architecture 2018 arXiv Augustus Odena, Dimitris Metaxas, Han Zhang, Ian Goodfellow link

Dimitris Tsipras

Paper Name Status Topic Category Year Conference Author Summary Link
0 How Does Batch Normalization Help Optimization? Pending NNs, Normalization Optimizations 2018 arXiv Aleksander Madry, Andrew Ilyas, Dimitris Tsipras, Shibani Santurkar link

Diogo Almeida

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training language models to follow instructions with human feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Semi-Supervised 2022 arXiv Carroll L. Wainwright, Diogo Almeida, Jan Leike, Jeff Wu, Long Ouyang, Pamela Mishkin, Paul Christiano, Ryan Lowe, Xu Jiang This paper presents InstructGPT, a model fine-tuned with human feedback to better align with user intent across various tasks. Despite having significantly fewer parameters than larger models, InstructGPT outperforms them in human evaluations, demonstrating improved truthfulness, reduced toxicity, and minimal performance regressions on public NLP datasets, highlighting the potential of fine-tuning with human feedback for enhancing language model alignment with human intent. link

Diyi Yang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Interpreting Deep Learning Models in Natural Language Processing: A Review Pending Text Comparison, Visualization 2021 arXiv Diyi Yang, Xiaofei Sun link

Dmytro Mishkin

Paper Name Status Topic Category Year Conference Author Summary Link
0 All you need is a good init Pending NN Initialization Tips & Tricks 2015 arXiv Dmytro Mishkin, Jiri Matas link

Eugenio Culurciello

Paper Name Status Topic Category Year Conference Author Summary Link
0 Evaluation of neural network architectures for embedded systems Read CNNs, CV , Image Comparison 2017 IEEE ISCAS Adam Paszke, Alfredo Canziani, Eugenio Culurciello Compare CNN classification architectures on accuracy, memory footprint, parameters, operations count, inference time and power consumption. link

Fangxiaoyu Feng

Paper Name Status Topic Category Year Conference Author Summary Link
0 Language-Agnostic BERT Sentence Embedding Read Attention, Siamese Network, Text , Transformers Embeddings 2020 arXiv Fangxiaoyu Feng, Yinfei Yang A BERT model with multilingual sentence embeddings learned over 112 languages and Zero-shot learning over unseen languages. link

Forrest N. Iandola

Paper Name Status Topic Category Year Conference Author Summary Link
0 SqueezeNet Read CNNs, CV , Image Architecture, Optimization-No. of params 2016 arXiv Forrest N. Iandola, Song Han Explores model compression by using 1x1 convolutions called fire modules. link

Gabriel Goh

Paper Name Status Topic Category Year Conference Author Summary Link
0 DALL·E: Creating Images from Text Pending Image , Text , Transformers 2021 Blog Aditya Ramesh, Gabriel Goh, Ilya Sutskever, Mikhail Pavlov, Scott Gray link

Gal Kaplun

Paper Name Status Topic Category Year Conference Author Summary Link
0 Deep Double Descent: Where Bigger Models and More Data Hurt Pending NNs 2019 arXiv Boaz Barak, Gal Kaplun, Ilya Sutskever, Preetum Nakkiran, Tristan Yang, Yamini Bansal link

Geoffrey E Hinton

Paper Name Status Topic Category Year Conference Author Summary Link
0 Capsule Networks: Dynamic Routing Between Capsules Pending CV , Image Architecture 2017 arXiv Geoffrey E Hinton, Nicholas Frosst, Sara Sabour link

Greg Corrado

Paper Name Status Topic Category Year Conference Author Summary Link
0 Word2Vec: Efficient Estimation of Word Representations in Vector Space Pending Text Embeddings, Tips & Tricks 2013 arXiv Greg Corrado, Jeffrey Dean, Kai Chen, Tomas Mikolov link

Guillaume Lample

Paper Name Status Topic Category Year Conference Author Summary Link
0 Phrase-Based & Neural Unsupervised Machine Translation Pending NMT, Text , Transformers Unsupervised 2018 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link
1 Unsupervised Machine Translation Using Monolingual Corpora Only Pending GANs, NMT, Text , Transformers Unsupervised 2017 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link
2 Cross-lingual Language Model Pretraining Pending NMT, Text , Transformers Unsupervised 2019 arXiv Alexis Conneau, Guillaume Lample link

Günter Klambauer

Paper Name Status Topic Category Year Conference Author Summary Link
0 Self-Normalizing Neural Networks Pending Activation Function, Tabular Optimizations, Tips & Tricks 2017 NIPS Andreas Mayr, Günter Klambauer, Thomas Unterthiner link

Han Zhang

Paper Name Status Topic Category Year Conference Author Summary Link
0 SAGAN: Self-Attention Generative Adversarial Networks Pending Attention, GANs, Image Architecture 2018 arXiv Augustus Odena, Dimitris Metaxas, Han Zhang, Ian Goodfellow link

Hannah Rashkin

Paper Name Status Topic Category Year Conference Author Summary Link
0 COMET: Commonsense Transformers for Automatic Knowledge Graph Construction Pending AGI, Text , Transformers 2019 ACL Antoine Bosselut, Hannah Rashkin, Yejin Choi link

Hao Li

Paper Name Status Topic Category Year Conference Author Summary Link
0 Pruning Filters for Efficient ConvNets Pending CNNs, CV , Image Optimization-No. of params 2017 arXiv Asim Kadav, Hao Li link

Hao Tan

Paper Name Status Topic Category Year Conference Author Summary Link
0 Vokenization: Improving Language Understanding with Contextualized, Visual-Grounded Supervision This week Image , Text , Transformers Multimodal 2020 EMNLP Hao Tan, Mohit Bansal link
1 VL-T5: Unifying Vision-and-Language Tasks via Text Generation Read CNNs, CV , Generative, Image , Large-Language-Models, Question-Answering, Text , Transformers Architecture, Embeddings, Multimodal, Pre-Training 2021 arXiv Hao Tan, Jaemin Cho, Jie Le, Mohit Bansal Unifying two modalities (image and text) together in a single transformer model to solve multiple tasks in a single architecture using text prefixes similar to T5. link

Hattie Zhou

Paper Name Status Topic Category Year Conference Author Summary Link
0 Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask Read NN Initialization, NNs Comparison, Optimization-No. of params, Tips & Tricks 2019 NeurIPS Hattie Zhou, Janice Lan, Jason Yosinski, Rosanne Liu Follow up on Lottery Ticket Hypothesis exploring the effects of different Masking criteria as well as Mask-1 and Mask-0 actions. link

Hyung Won Chung

Paper Name Status Topic Category Year Conference Author Summary Link
0 Flan-T5: Scaling Instruction-Finetuned Language Models Pending Generative, Text , Transformers Architecture, Pre-Training 2022 arXiv Hyung Won Chung, Le Hou link
1 Scaling Instruction-Finetuned Language Models (FLAN) Pending Generative, Large-Language-Models, Question-Answering, Text , Transformers Instruction-Finetuning 2022 arXiv Hyung Won Chung, Jason Wei, Jeffrey Dean, Le Hou, Quoc V. Le, Shayne Longpre https://arxiv.org/abs/2210.11416 introduces FLAN (Fine-tuned LAnguage Net), an instruction finetuning method, and presents the results of its application. The study demonstrates that by fine-tuning the 540B PaLM model on 1836 tasks while incorporating Chain-of-Thought Reasoning data, FLAN achieves improvements in generalization, human usability, and zero-shot reasoning over the base model. The paper also provides detailed information on how each these aspects was evaluated. link

Ian Goodfellow

Paper Name Status Topic Category Year Conference Author Summary Link
0 SAGAN: Self-Attention Generative Adversarial Networks Pending Attention, GANs, Image Architecture 2018 arXiv Augustus Odena, Dimitris Metaxas, Han Zhang, Ian Goodfellow link
1 Improved Techniques for Training GANs Pending GANs, Image Semi-Supervised 2016 NIPS Alec Radford, Ian Goodfellow, Tim Salimans, Vicki Cheung, Wojciech Zaremba, Xi Chen link

Iftekhar Naim

Paper Name Status Topic Category Year Conference Author Summary Link
0 Transforming Sequence Tagging Into A Seq2Seq Task Pending Generative, Text Comparison, Tips & Tricks 2022 arXiv Iftekhar Naim, Karthik Raman, Krishna Srinivasan link

Illia Polosukhin

Paper Name Status Topic Category Year Conference Author Summary Link
0 Attention is All you Need Read Attention, Text , Transformers Architecture 2017 NIPS Ashish Vaswani, Illia Polosukhin, Noam Shazeer, Łukasz Kaiser Talks about Transformer architecture which brings SOTA performance for different tasks in NLP link

Ilya Sutskever

Paper Name Status Topic Category Year Conference Author Summary Link
0 GPT-2 (Language Models are Unsupervised Multitask Learners) Pending Attention, Text , Transformers 2019 Alec Radford, Dario Amodei, Ilya Sutskever, Jeffrey Wu link
1 Deep Double Descent: Where Bigger Models and More Data Hurt Pending NNs 2019 arXiv Boaz Barak, Gal Kaplun, Ilya Sutskever, Preetum Nakkiran, Tristan Yang, Yamini Bansal link
2 GPT-f: Generative Language Modeling for Automated Theorem Proving Pending Attention, Transformers 2020 arXiv Ilya Sutskever, Stanislas Polu link
3 DALL·E: Creating Images from Text Pending Image , Text , Transformers 2021 Blog Aditya Ramesh, Gabriel Goh, Ilya Sutskever, Mikhail Pavlov, Scott Gray link
4 CLIP: Connecting Text and Images Pending Image , Text , Transformers Multimodal, Pre-Training 2021 arXiv Alec Radford, Ilya Sutskever, Jong Wook Kim link

Ioannis Antonoglou

Paper Name Status Topic Category Year Conference Author Summary Link
0 MuZero: Mastering Go, chess, shogi and Atari without rules Pending Reinforcement-Learning 2020 Nature David Silver, Demis Hassabis, Ioannis Antonoglou, Julian Schrittwiese link

Itamar Friedman

Paper Name Status Topic Category Year Conference Author Summary Link
0 Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering Pending Large-Language-Models Prompting, Tips & Tricks 2024 arXiv Dedy Kredo, Itamar Friedman, Tal Ridnik This paper introduces AlphaCodium, a novel test-based, multi-stage, code-oriented iterative approach for improving the performance of Language Model Models (LLMs) on code generation tasks. link

Izhak Shafran

Paper Name Status Topic Category Year Conference Author Summary Link
0 ReAct: Synergizing Reasoning and Acting in Language Models Pending Generative, Large-Language-Models, Text Optimizations, Tips & Tricks 2023 ICLR Dian Yu, Izhak Shafran, Jeffrey Zhao, Karthik Narasimhan, Nan Du, Shunyu Yao, Yuan Cao This paper introduces ReAct, a novel approach that leverages Large Language Models (LLMs) to interleave reasoning traces and task-specific actions. ReAct outperforms existing methods on various language and decision-making tasks, addressing issues like hallucination, error propagation, and improving human interpretability and trustworthiness. link

Jaakko Lehtinen

Paper Name Status Topic Category Year Conference Author Summary Link
0 Progressive Growing of GANs for Improved Quality, Stability, and Variation Pending GANs, Image Tips & Tricks 2018 ICLR Jaakko Lehtinen, Samuli Laine, Tero Karras, Timo Aila link

Jack Hessel

Paper Name Status Topic Category Year Conference Author Summary Link
0 Symbolic Knowledge Distillation: from General Language Models to Commonsense Models Pending Dataset, Text , Transformers Optimizations, Tips & Tricks 2021 arXiv Chandra Bhagavatula, Jack Hessel, Peter West, Yejin Choi link

Jacob Devlin

Paper Name Status Topic Category Year Conference Author Summary Link
0 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Read Attention, Text , Transformers Embeddings 2018 NAACL Jacob Devlin, Kenton Lee, Kristina Toutanova, Ming-Wei Chang BERT is an extension to Transformer based architecture which introduces a masked word pretraining and next sentence prediction task to pretrain the model for a wide variety of tasks. link

Jae Sung Park

Paper Name Status Topic Category Year Conference Author Summary Link
0 VisualCOMET: Reasoning about the Dynamic Context of a Still Image Pending AGI, Dataset, Image , Text , Transformers 2020 ECCV Ali Farhadi, Chandra Bhagavatula, Jae Sung Park, Yejin Choi link

Jaegul Choo

Paper Name Status Topic Category Year Conference Author Summary Link
0 StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation Pending GANs, Image 2018 CVPR Jaegul Choo, Jung-Woo Ha, Minje Choi, Munyoung Kim, Sunghun Kim, Yunjey Choi link

Jaemin Cho

Paper Name Status Topic Category Year Conference Author Summary Link
0 VL-T5: Unifying Vision-and-Language Tasks via Text Generation Read CNNs, CV , Generative, Image , Large-Language-Models, Question-Answering, Text , Transformers Architecture, Embeddings, Multimodal, Pre-Training 2021 arXiv Hao Tan, Jaemin Cho, Jie Le, Mohit Bansal Unifying two modalities (image and text) together in a single transformer model to solve multiple tasks in a single architecture using text prefixes similar to T5. link

Jakob Uszkoreit

Paper Name Status Topic Category Year Conference Author Summary Link
0 Vision Transformer: An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Pending Attention, Image , Transformers 2021 ICLR Alexey Dosovitskiy, Jakob Uszkoreit, Lucas Beyer, Neil Houlsby link

James J. Little

Paper Name Status Topic Category Year Conference Author Summary Link
0 A Simple yet Effective Baseline for 3D Human Pose Estimation Pending CV , Pose Estimation 2017 ICCV James J. Little, Javier Romero, Julieta Martinez, Rayat Hossain link

Jan Leike

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training language models to follow instructions with human feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Semi-Supervised 2022 arXiv Carroll L. Wainwright, Diogo Almeida, Jan Leike, Jeff Wu, Long Ouyang, Pamela Mishkin, Paul Christiano, Ryan Lowe, Xu Jiang This paper presents InstructGPT, a model fine-tuned with human feedback to better align with user intent across various tasks. Despite having significantly fewer parameters than larger models, InstructGPT outperforms them in human evaluations, demonstrating improved truthfulness, reduced toxicity, and minimal performance regressions on public NLP datasets, highlighting the potential of fine-tuning with human feedback for enhancing language model alignment with human intent. link

Janice Lan

Paper Name Status Topic Category Year Conference Author Summary Link
0 Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask Read NN Initialization, NNs Comparison, Optimization-No. of params, Tips & Tricks 2019 NeurIPS Hattie Zhou, Janice Lan, Jason Yosinski, Rosanne Liu Follow up on Lottery Ticket Hypothesis exploring the effects of different Masking criteria as well as Mask-1 and Mask-0 actions. link

Jared Kaplan

Paper Name Status Topic Category Year Conference Author Summary Link
0 Constitutional AI: Harmlessness from AI Feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Unsupervised 2022 arXiv Jared Kaplan, Yuntao Ba The paper introduces Constitutional AI, a method for training a safe AI assistant without human-labeled data on harmful outputs. It combines supervised learning and reinforcement learning phases, enabling the AI to engage with harmful queries by explaining its objections, thus improving control, transparency, and human-judged performance with minimal human oversight. link

Jason Wei

Paper Name Status Topic Category Year Conference Author Summary Link
0 Chain of Thought Prompting Elicits Reasoning in Large Language Models Pending Question-Answering, Text , Transformers 2022 arXiv Denny Zhou, Jason Wei, Xuezhi Wang link
1 Scaling Instruction-Finetuned Language Models (FLAN) Pending Generative, Large-Language-Models, Question-Answering, Text , Transformers Instruction-Finetuning 2022 arXiv Hyung Won Chung, Jason Wei, Jeffrey Dean, Le Hou, Quoc V. Le, Shayne Longpre https://arxiv.org/abs/2210.11416 introduces FLAN (Fine-tuned LAnguage Net), an instruction finetuning method, and presents the results of its application. The study demonstrates that by fine-tuning the 540B PaLM model on 1836 tasks while incorporating Chain-of-Thought Reasoning data, FLAN achieves improvements in generalization, human usability, and zero-shot reasoning over the base model. The paper also provides detailed information on how each these aspects was evaluated. link

Jason Weston

Paper Name Status Topic Category Year Conference Author Summary Link
0 Self-Alignment with Instruction Backtranslation Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning 2023 arXiv Jason Weston, Mike Lewis, Ping Yu, Xian Li The paper introduces a scalable method called "instruction backtranslation" to create a high-quality instruction-following language model. This method involves self-augmentation and self-curation of training examples generated from web documents, resulting in a model that outperforms others in its category without relying on distillation data, showcasing its effective self-alignment capability. link

Jason Yosinski

Paper Name Status Topic Category Year Conference Author Summary Link
0 Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask Read NN Initialization, NNs Comparison, Optimization-No. of params, Tips & Tricks 2019 NeurIPS Hattie Zhou, Janice Lan, Jason Yosinski, Rosanne Liu Follow up on Lottery Ticket Hypothesis exploring the effects of different Masking criteria as well as Mask-1 and Mask-0 actions. link

Javier Romero

Paper Name Status Topic Category Year Conference Author Summary Link
0 A Simple yet Effective Baseline for 3D Human Pose Estimation Pending CV , Pose Estimation 2017 ICCV James J. Little, Javier Romero, Julieta Martinez, Rayat Hossain link

Jeff Wu

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training language models to follow instructions with human feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Semi-Supervised 2022 arXiv Carroll L. Wainwright, Diogo Almeida, Jan Leike, Jeff Wu, Long Ouyang, Pamela Mishkin, Paul Christiano, Ryan Lowe, Xu Jiang This paper presents InstructGPT, a model fine-tuned with human feedback to better align with user intent across various tasks. Despite having significantly fewer parameters than larger models, InstructGPT outperforms them in human evaluations, demonstrating improved truthfulness, reduced toxicity, and minimal performance regressions on public NLP datasets, highlighting the potential of fine-tuning with human feedback for enhancing language model alignment with human intent. link

Jeffrey Dean

Paper Name Status Topic Category Year Conference Author Summary Link
0 Word2Vec: Efficient Estimation of Word Representations in Vector Space Pending Text Embeddings, Tips & Tricks 2013 arXiv Greg Corrado, Jeffrey Dean, Kai Chen, Tomas Mikolov link
1 Scaling Instruction-Finetuned Language Models (FLAN) Pending Generative, Large-Language-Models, Question-Answering, Text , Transformers Instruction-Finetuning 2022 arXiv Hyung Won Chung, Jason Wei, Jeffrey Dean, Le Hou, Quoc V. Le, Shayne Longpre https://arxiv.org/abs/2210.11416 introduces FLAN (Fine-tuned LAnguage Net), an instruction finetuning method, and presents the results of its application. The study demonstrates that by fine-tuning the 540B PaLM model on 1836 tasks while incorporating Chain-of-Thought Reasoning data, FLAN achieves improvements in generalization, human usability, and zero-shot reasoning over the base model. The paper also provides detailed information on how each these aspects was evaluated. link

Jeffrey Wu

Paper Name Status Topic Category Year Conference Author Summary Link
0 GPT-2 (Language Models are Unsupervised Multitask Learners) Pending Attention, Text , Transformers 2019 Alec Radford, Dario Amodei, Ilya Sutskever, Jeffrey Wu link

Jeffrey Zhao

Paper Name Status Topic Category Year Conference Author Summary Link
0 ReAct: Synergizing Reasoning and Acting in Language Models Pending Generative, Large-Language-Models, Text Optimizations, Tips & Tricks 2023 ICLR Dian Yu, Izhak Shafran, Jeffrey Zhao, Karthik Narasimhan, Nan Du, Shunyu Yao, Yuan Cao This paper introduces ReAct, a novel approach that leverages Large Language Models (LLMs) to interleave reasoning traces and task-specific actions. ReAct outperforms existing methods on various language and decision-making tasks, addressing issues like hallucination, error propagation, and improving human interpretability and trustworthiness. link

Jessica B. Hamrick

Paper Name Status Topic Category Year Conference Author Summary Link
0 Graph Neural Network: Relational inductive biases, deep learning, and graph networks Pending GraphNN Architecture 2018 arXiv Jessica B. Hamrick, Oriol Vinyals, Peter W. Battaglia link

Jiakai Zhang

Paper Name Status Topic Category Year Conference Author Summary Link
0 AnimeGAN: Towards the Automatic Anime Characters Creation with Generative Adversarial Networks Pending GANs, Image 2017 NIPS Jiakai Zhang, Minjun Li, Yanghua Jin link

Jie Le

Paper Name Status Topic Category Year Conference Author Summary Link
0 VL-T5: Unifying Vision-and-Language Tasks via Text Generation Read CNNs, CV , Generative, Image , Large-Language-Models, Question-Answering, Text , Transformers Architecture, Embeddings, Multimodal, Pre-Training 2021 arXiv Hao Tan, Jaemin Cho, Jie Le, Mohit Bansal Unifying two modalities (image and text) together in a single transformer model to solve multiple tasks in a single architecture using text prefixes similar to T5. link

Jimmy Ba

Paper Name Status Topic Category Year Conference Author Summary Link
0 Adam: A Method for Stochastic Optimization Pending NNs, Optimizers 2015 ICLR Diederik P. Kingma, Jimmy Ba link

Jiri Matas

Paper Name Status Topic Category Year Conference Author Summary Link
0 All you need is a good init Pending NN Initialization Tips & Tricks 2015 arXiv Dmytro Mishkin, Jiri Matas link

Jitendra Malik

Paper Name Status Topic Category Year Conference Author Summary Link
0 IMLE-GAN: Inclusive GAN: Improving Data and Minority Coverage in Generative Models Pending GANs 2020 arXiv Jitendra Malik, Ke Li, Larry Davis, Mario Fritz, Ning Yu, Peng Zhou link

Jonathan Frankle

Paper Name Status Topic Category Year Conference Author Summary Link
0 The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Read NN Initialization, NNs Optimization-No. of params, Tips & Tricks 2019 ICLR Jonathan Frankle, Michael Carbin Lottery ticket hypothesis: dense, randomly-initialized, feed-forward networks contain subnetworks (winning tickets) that—when trained in isolation— reach test accuracy comparable to the original network in a similar number of iterations. link
1 Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs Pending CNNs, Image 2020 arXiv Ari S. Morcos, David J. Schwab, Jonathan Frankle link

Jong Wook Kim

Paper Name Status Topic Category Year Conference Author Summary Link
0 CLIP: Connecting Text and Images Pending Image , Text , Transformers Multimodal, Pre-Training 2021 arXiv Alec Radford, Ilya Sutskever, Jong Wook Kim link

Jordan Hoffmann

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training Compute-Optimal Large Language Models Pending Large-Language-Models, Transformers Architecture, Optimization-No. of params, Pre-Training, Tips & Tricks 2022 arXiv Jordan Hoffmann, Laurent Sifre, Oriol Vinyals, Sebastian Borgeaud link

Julian Schrittwiese

Paper Name Status Topic Category Year Conference Author Summary Link
0 MuZero: Mastering Go, chess, shogi and Atari without rules Pending Reinforcement-Learning 2020 Nature David Silver, Demis Hassabis, Ioannis Antonoglou, Julian Schrittwiese link

Julieta Martinez

Paper Name Status Topic Category Year Conference Author Summary Link
0 A Simple yet Effective Baseline for 3D Human Pose Estimation Pending CV , Pose Estimation 2017 ICCV James J. Little, Javier Romero, Julieta Martinez, Rayat Hossain link

Jun Huang

Paper Name Status Topic Category Year Conference Author Summary Link
0 One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information Extraction Pending Image , Text 2020 arXiv Jun Huang, Mengli Cheng, Minghui Qiu, Wei Lin, Xing Shi link

Jun-Yan Zhu

Paper Name Status Topic Category Year Conference Author Summary Link
0 Pix2Pix: Image-to-Image Translation with Conditional Adversarial Nets Read GANs, Image 2017 CVPR Alexei A. Efros, Jun-Yan Zhu, Phillip Isola, Tinghui Zhou Image to image translation using Conditional GANs and dataset of image pairs from one domain to another. link
1 CycleGAN: Unpaired Image-To-Image Translation Using Cycle-Consistent Adversarial Networks Pending GANs, Image Architecture 2017 ICCV Alexei A. Efros, Jun-Yan Zhu, Phillip Isola, Taesung Park link

Jung-Woo Ha

Paper Name Status Topic Category Year Conference Author Summary Link
0 StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation Pending GANs, Image 2018 CVPR Jaegul Choo, Jung-Woo Ha, Minje Choi, Munyoung Kim, Sunghun Kim, Yunjey Choi link

Justin Johnson

Paper Name Status Topic Category Year Conference Author Summary Link
0 Perceptual Losses for Real-Time Style Transfer and Super-Resolution Pending Loss Function, NNs 2016 ECCV Alexandre Alahi, Justin Johnson, Li Fei-Fei link

Kai Chen

Paper Name Status Topic Category Year Conference Author Summary Link
0 Word2Vec: Efficient Estimation of Word Representations in Vector Space Pending Text Embeddings, Tips & Tricks 2013 arXiv Greg Corrado, Jeffrey Dean, Kai Chen, Tomas Mikolov link

Kaiming He

Paper Name Status Topic Category Year Conference Author Summary Link
0 ResNet (Deep Residual Learning for Image Recognition) Read CNNs, CV , Image Architecture 2016 CVPR Kaiming He, Xiangyu Zhang Introduces Residual or Skip Connections to allow increase in the depth of a DNN link
1 Group Normalization Pending NNs, Normalization Optimizations 2018 arXiv Kaiming He, Yuxin Wu link

Karthik Narasimhan

Paper Name Status Topic Category Year Conference Author Summary Link
0 ReAct: Synergizing Reasoning and Acting in Language Models Pending Generative, Large-Language-Models, Text Optimizations, Tips & Tricks 2023 ICLR Dian Yu, Izhak Shafran, Jeffrey Zhao, Karthik Narasimhan, Nan Du, Shunyu Yao, Yuan Cao This paper introduces ReAct, a novel approach that leverages Large Language Models (LLMs) to interleave reasoning traces and task-specific actions. ReAct outperforms existing methods on various language and decision-making tasks, addressing issues like hallucination, error propagation, and improving human interpretability and trustworthiness. link

Karthik Raman

Paper Name Status Topic Category Year Conference Author Summary Link
0 Transforming Sequence Tagging Into A Seq2Seq Task Pending Generative, Text Comparison, Tips & Tricks 2022 arXiv Iftekhar Naim, Karthik Raman, Krishna Srinivasan link

Ke Li

Paper Name Status Topic Category Year Conference Author Summary Link
0 IMLE-GAN: Inclusive GAN: Improving Data and Minority Coverage in Generative Models Pending GANs 2020 arXiv Jitendra Malik, Ke Li, Larry Davis, Mario Fritz, Ning Yu, Peng Zhou link

Kenton Lee

Paper Name Status Topic Category Year Conference Author Summary Link
0 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Read Attention, Text , Transformers Embeddings 2018 NAACL Jacob Devlin, Kenton Lee, Kristina Toutanova, Ming-Wei Chang BERT is an extension to Transformer based architecture which introduces a masked word pretraining and next sentence prediction task to pretrain the model for a wide variety of tasks. link

Krishna Srinivasan

Paper Name Status Topic Category Year Conference Author Summary Link
0 Transforming Sequence Tagging Into A Seq2Seq Task Pending Generative, Text Comparison, Tips & Tricks 2022 arXiv Iftekhar Naim, Karthik Raman, Krishna Srinivasan link

Kristen Grauman

Paper Name Status Topic Category Year Conference Author Summary Link
0 Occupancy Anticipation for Efficient Exploration and Navigation Pending CNNs, Image Reinforcement-Learning 2020 ECCV Kristen Grauman, Santhosh K. Ramakrishnan, Ziad Al-Halah link

Kristina Toutanova

Paper Name Status Topic Category Year Conference Author Summary Link
0 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Read Attention, Text , Transformers Embeddings 2018 NAACL Jacob Devlin, Kenton Lee, Kristina Toutanova, Ming-Wei Chang BERT is an extension to Transformer based architecture which introduces a masked word pretraining and next sentence prediction task to pretrain the model for a wide variety of tasks. link

Larry Davis

Paper Name Status Topic Category Year Conference Author Summary Link
0 IMLE-GAN: Inclusive GAN: Improving Data and Minority Coverage in Generative Models Pending GANs 2020 arXiv Jitendra Malik, Ke Li, Larry Davis, Mario Fritz, Ning Yu, Peng Zhou link

Laurent Sifre

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training Compute-Optimal Large Language Models Pending Large-Language-Models, Transformers Architecture, Optimization-No. of params, Pre-Training, Tips & Tricks 2022 arXiv Jordan Hoffmann, Laurent Sifre, Oriol Vinyals, Sebastian Borgeaud link

Le Hou

Paper Name Status Topic Category Year Conference Author Summary Link
0 Flan-T5: Scaling Instruction-Finetuned Language Models Pending Generative, Text , Transformers Architecture, Pre-Training 2022 arXiv Hyung Won Chung, Le Hou link
1 Scaling Instruction-Finetuned Language Models (FLAN) Pending Generative, Large-Language-Models, Question-Answering, Text , Transformers Instruction-Finetuning 2022 arXiv Hyung Won Chung, Jason Wei, Jeffrey Dean, Le Hou, Quoc V. Le, Shayne Longpre https://arxiv.org/abs/2210.11416 introduces FLAN (Fine-tuned LAnguage Net), an instruction finetuning method, and presents the results of its application. The study demonstrates that by fine-tuning the 540B PaLM model on 1836 tasks while incorporating Chain-of-Thought Reasoning data, FLAN achieves improvements in generalization, human usability, and zero-shot reasoning over the base model. The paper also provides detailed information on how each these aspects was evaluated. link

Leonard Adolphs

Paper Name Status Topic Category Year Conference Author Summary Link
0 Decoding a Neural Retriever’s Latent Space for Query Suggestion Pending Text Embeddings, Latent space 2022 arXiv Christian Buck, Leonard Adolphs, Michelle Chen Huebscher link

Li Fei-Fei

Paper Name Status Topic Category Year Conference Author Summary Link
0 Perceptual Losses for Real-Time Style Transfer and Super-Resolution Pending Loss Function, NNs 2016 ECCV Alexandre Alahi, Justin Johnson, Li Fei-Fei link

Li Yang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Learning to Extract Attribute Value from Product via Question Answering: A Multi-task Approach Read Question-Answering, Text , Transformers Zero-shot-learning 2020 KDD Li Yang, Qifan Wang Question Answering BERT model used to extract attributes from products. Introduce further No Answer loss and distillation to promote zero shot learning. link

Long Ouyang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training language models to follow instructions with human feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Semi-Supervised 2022 arXiv Carroll L. Wainwright, Diogo Almeida, Jan Leike, Jeff Wu, Long Ouyang, Pamela Mishkin, Paul Christiano, Ryan Lowe, Xu Jiang This paper presents InstructGPT, a model fine-tuned with human feedback to better align with user intent across various tasks. Despite having significantly fewer parameters than larger models, InstructGPT outperforms them in human evaluations, demonstrating improved truthfulness, reduced toxicity, and minimal performance regressions on public NLP datasets, highlighting the potential of fine-tuning with human feedback for enhancing language model alignment with human intent. link

Lucas Beyer

Paper Name Status Topic Category Year Conference Author Summary Link
0 Vision Transformer: An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Pending Attention, Image , Transformers 2021 ICLR Alexey Dosovitskiy, Jakob Uszkoreit, Lucas Beyer, Neil Houlsby link

Ludovic Denoyer

Paper Name Status Topic Category Year Conference Author Summary Link
0 Phrase-Based & Neural Unsupervised Machine Translation Pending NMT, Text , Transformers Unsupervised 2018 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link
1 Unsupervised Machine Translation Using Monolingual Corpora Only Pending GANs, NMT, Text , Transformers Unsupervised 2017 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link

Lukasz Kaiser

Paper Name Status Topic Category Year Conference Author Summary Link
0 Reformer: The Efficient Transformer Read Attention, Text , Transformers Architecture, Optimization-Memory, Optimization-No. of params 2020 arXiv Anselm Levskaya, Lukasz Kaiser, Nikita Kitaev Overcome time and memory complexity of Transformers by bucketing Query, Keys and using Reversible residual connections. link

Luke Metz

Paper Name Status Topic Category Year Conference Author Summary Link
0 BEGAN: Boundary Equilibrium Generative Adversarial Networks Pending GANs, Image 2017 arXiv David Berthelot, Luke Metz, Thomas Schumm link

Luming Tang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition Pending CNNs, Image Few-shot-learning 2020 CVPR Bharath Hariharan, Davis Wertheimer, Luming Tang link

Léon Bottou

Paper Name Status Topic Category Year Conference Author Summary Link
0 WGAN: Wasserstein GAN Pending GANs, Loss Function 2017 arXiv Léon Bottou, Martin Arjovsky, Soumith Chintala link

Maarten Sap

Paper Name Status Topic Category Year Conference Author Summary Link
0 ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning Pending AGI, Dataset, Text 2019 AAAI Maarten Sap, Noah A. Smith, Ronan Le Bras, Yejin Choi link

Mandar Joshi

Paper Name Status Topic Category Year Conference Author Summary Link
0 SpanBERT: Improving Pre-training by Representing and Predicting Spans Read Question-Answering, Text , Transformers Pre-Training 2020 TACL Danqi Chen, Mandar Joshi A different pre-training strategy for BERT model to improve performance for Question Answering task. link

Marc'Aurelio Ranzato

Paper Name Status Topic Category Year Conference Author Summary Link
0 Phrase-Based & Neural Unsupervised Machine Translation Pending NMT, Text , Transformers Unsupervised 2018 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link
1 Unsupervised Machine Translation Using Monolingual Corpora Only Pending GANs, NMT, Text , Transformers Unsupervised 2017 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link

Mario Fritz

Paper Name Status Topic Category Year Conference Author Summary Link
0 IMLE-GAN: Inclusive GAN: Improving Data and Minority Coverage in Generative Models Pending GANs 2020 arXiv Jitendra Malik, Ke Li, Larry Davis, Mario Fritz, Ning Yu, Peng Zhou link

Martin Arjovsky

Paper Name Status Topic Category Year Conference Author Summary Link
0 WGAN: Wasserstein GAN Pending GANs, Loss Function 2017 arXiv Léon Bottou, Martin Arjovsky, Soumith Chintala link

Masanori Koyama

Paper Name Status Topic Category Year Conference Author Summary Link
0 Spectral Normalization for GANs Pending GANs, Normalization Optimizations 2018 arXiv Masanori Koyama, Takeru Miyato, Toshiki Kataoka, Yuichi Yoshida link

Mateusz Koziński

Paper Name Status Topic Category Year Conference Author Summary Link
0 Topological Loss: Beyond the Pixel-Wise Loss for Topology-Aware Delineation Pending Image , Loss Function, Segmentation 2018 CVPR Agata Mosinska, Mateusz Koziński, Pablo Márquez-Neila, Pascal Fua link

Matthew D. Zeiler

Paper Name Status Topic Category Year Conference Author Summary Link
0 ZF Net (Visualizing and Understanding Convolutional Networks) Read CNNs, CV , Image Visualization 2014 ECCV Matthew D. Zeiler, Rob Fergus Visualize CNN Filters / Kernels using De-Convolutions on CNN filter activations. link

Matthias Bethge

Paper Name Status Topic Category Year Conference Author Summary Link
0 Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet Reading CNNs, CV , Image 2019 arXiv Matthias Bethge, Wieland Brendel link

Mengli Cheng

Paper Name Status Topic Category Year Conference Author Summary Link
0 One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information Extraction Pending Image , Text 2020 arXiv Jun Huang, Mengli Cheng, Minghui Qiu, Wei Lin, Xing Shi link

Menglin Jia

Paper Name Status Topic Category Year Conference Author Summary Link
0 Class-Balanced Loss Based on Effective Number of Samples Pending Loss Function Tips & Tricks 2019 CVPR Menglin Jia, Yin Cui link

Menglong Zhu

Paper Name Status Topic Category Year Conference Author Summary Link
0 MobileNet (Efficient Convolutional Neural Networks for Mobile Vision Applications) Pending CNNs, CV , Image Architecture, Optimization-No. of params 2017 arXiv Andrew G. Howard, Menglong Zhu link

Michael Carbin

Paper Name Status Topic Category Year Conference Author Summary Link
0 The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Read NN Initialization, NNs Optimization-No. of params, Tips & Tricks 2019 ICLR Jonathan Frankle, Michael Carbin Lottery ticket hypothesis: dense, randomly-initialized, feed-forward networks contain subnetworks (winning tickets) that—when trained in isolation— reach test accuracy comparable to the original network in a similar number of iterations. link

Michelle Chen Huebscher

Paper Name Status Topic Category Year Conference Author Summary Link
0 Decoding a Neural Retriever’s Latent Space for Query Suggestion Pending Text Embeddings, Latent space 2022 arXiv Christian Buck, Leonard Adolphs, Michelle Chen Huebscher link

Mike Lewis

Paper Name Status Topic Category Year Conference Author Summary Link
0 Self-Alignment with Instruction Backtranslation Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning 2023 arXiv Jason Weston, Mike Lewis, Ping Yu, Xian Li The paper introduces a scalable method called "instruction backtranslation" to create a high-quality instruction-following language model. This method involves self-augmentation and self-curation of training examples generated from web documents, resulting in a model that outperforms others in its category without relying on distillation data, showcasing its effective self-alignment capability. link

Mikhail Pavlov

Paper Name Status Topic Category Year Conference Author Summary Link
0 DALL·E: Creating Images from Text Pending Image , Text , Transformers 2021 Blog Aditya Ramesh, Gabriel Goh, Ilya Sutskever, Mikhail Pavlov, Scott Gray link

Ming-Wei Chang

Paper Name Status Topic Category Year Conference Author Summary Link
0 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Read Attention, Text , Transformers Embeddings 2018 NAACL Jacob Devlin, Kenton Lee, Kristina Toutanova, Ming-Wei Chang BERT is an extension to Transformer based architecture which introduces a masked word pretraining and next sentence prediction task to pretrain the model for a wide variety of tasks. link

Minghui Qiu

Paper Name Status Topic Category Year Conference Author Summary Link
0 One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information Extraction Pending Image , Text 2020 arXiv Jun Huang, Mengli Cheng, Minghui Qiu, Wei Lin, Xing Shi link

Minje Choi

Paper Name Status Topic Category Year Conference Author Summary Link
0 StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation Pending GANs, Image 2018 CVPR Jaegul Choo, Jung-Woo Ha, Minje Choi, Munyoung Kim, Sunghun Kim, Yunjey Choi link

Minjun Li

Paper Name Status Topic Category Year Conference Author Summary Link
0 AnimeGAN: Towards the Automatic Anime Characters Creation with Generative Adversarial Networks Pending GANs, Image 2017 NIPS Jiakai Zhang, Minjun Li, Yanghua Jin link

Mohit Bansal

Paper Name Status Topic Category Year Conference Author Summary Link
0 Vokenization: Improving Language Understanding with Contextualized, Visual-Grounded Supervision This week Image , Text , Transformers Multimodal 2020 EMNLP Hao Tan, Mohit Bansal link
1 VL-T5: Unifying Vision-and-Language Tasks via Text Generation Read CNNs, CV , Generative, Image , Large-Language-Models, Question-Answering, Text , Transformers Architecture, Embeddings, Multimodal, Pre-Training 2021 arXiv Hao Tan, Jaemin Cho, Jie Le, Mohit Bansal Unifying two modalities (image and text) together in a single transformer model to solve multiple tasks in a single architecture using text prefixes similar to T5. link

Munyoung Kim

Paper Name Status Topic Category Year Conference Author Summary Link
0 StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation Pending GANs, Image 2018 CVPR Jaegul Choo, Jung-Woo Ha, Minje Choi, Munyoung Kim, Sunghun Kim, Yunjey Choi link

Myle Ott

Paper Name Status Topic Category Year Conference Author Summary Link
0 Phrase-Based & Neural Unsupervised Machine Translation Pending NMT, Text , Transformers Unsupervised 2018 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link
1 Unsupervised Machine Translation Using Monolingual Corpora Only Pending GANs, NMT, Text , Transformers Unsupervised 2017 arXiv Alexis Conneau, Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato, Myle Ott link

Nan Du

Paper Name Status Topic Category Year Conference Author Summary Link
0 ReAct: Synergizing Reasoning and Acting in Language Models Pending Generative, Large-Language-Models, Text Optimizations, Tips & Tricks 2023 ICLR Dian Yu, Izhak Shafran, Jeffrey Zhao, Karthik Narasimhan, Nan Du, Shunyu Yao, Yuan Cao This paper introduces ReAct, a novel approach that leverages Large Language Models (LLMs) to interleave reasoning traces and task-specific actions. ReAct outperforms existing methods on various language and decision-making tasks, addressing issues like hallucination, error propagation, and improving human interpretability and trustworthiness. link

Neil Houlsby

Paper Name Status Topic Category Year Conference Author Summary Link
0 Vision Transformer: An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Pending Attention, Image , Transformers 2021 ICLR Alexey Dosovitskiy, Jakob Uszkoreit, Lucas Beyer, Neil Houlsby link

Nicholas Frosst

Paper Name Status Topic Category Year Conference Author Summary Link
0 Capsule Networks: Dynamic Routing Between Capsules Pending CV , Image Architecture 2017 arXiv Geoffrey E Hinton, Nicholas Frosst, Sara Sabour link

Nikita Kitaev

Paper Name Status Topic Category Year Conference Author Summary Link
0 Reformer: The Efficient Transformer Read Attention, Text , Transformers Architecture, Optimization-Memory, Optimization-No. of params 2020 arXiv Anselm Levskaya, Lukasz Kaiser, Nikita Kitaev Overcome time and memory complexity of Transformers by bucketing Query, Keys and using Reversible residual connections. link

Ning Yu

Paper Name Status Topic Category Year Conference Author Summary Link
0 IMLE-GAN: Inclusive GAN: Improving Data and Minority Coverage in Generative Models Pending GANs 2020 arXiv Jitendra Malik, Ke Li, Larry Davis, Mario Fritz, Ning Yu, Peng Zhou link

Noah A. Smith

Paper Name Status Topic Category Year Conference Author Summary Link
0 ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning Pending AGI, Dataset, Text 2019 AAAI Maarten Sap, Noah A. Smith, Ronan Le Bras, Yejin Choi link

Noam Shazeer

Paper Name Status Topic Category Year Conference Author Summary Link
0 Attention is All you Need Read Attention, Text , Transformers Architecture 2017 NIPS Ashish Vaswani, Illia Polosukhin, Noam Shazeer, Łukasz Kaiser Talks about Transformer architecture which brings SOTA performance for different tasks in NLP link
1 T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Read Attention, Text , Transformers 2020 JMLR Colin Raffel, Noam Shazeer, Peter J. Liu, Wei Liu, Yanqi Zhou Presents a Text-to-Text transformer model with multi-task learning capabilities, simultaneously solving problems such as machine translation, document summarization, question answering, and classification tasks. link

Oriol Vinyals

Paper Name Status Topic Category Year Conference Author Summary Link
0 Graph Neural Network: Relational inductive biases, deep learning, and graph networks Pending GraphNN Architecture 2018 arXiv Jessica B. Hamrick, Oriol Vinyals, Peter W. Battaglia link
1 Training Compute-Optimal Large Language Models Pending Large-Language-Models, Transformers Architecture, Optimization-No. of params, Pre-Training, Tips & Tricks 2022 arXiv Jordan Hoffmann, Laurent Sifre, Oriol Vinyals, Sebastian Borgeaud link

Other

Paper Name Status Topic Category Year Conference Author Summary Link
0 Table-GPT: Table-tuned GPT for Diverse Table Tasks Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning 2023 arXiv Other link

Pablo Márquez-Neila

Paper Name Status Topic Category Year Conference Author Summary Link
0 Topological Loss: Beyond the Pixel-Wise Loss for Topology-Aware Delineation Pending Image , Loss Function, Segmentation 2018 CVPR Agata Mosinska, Mateusz Koziński, Pablo Márquez-Neila, Pascal Fua link

Pamela Mishkin

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training language models to follow instructions with human feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Semi-Supervised 2022 arXiv Carroll L. Wainwright, Diogo Almeida, Jan Leike, Jeff Wu, Long Ouyang, Pamela Mishkin, Paul Christiano, Ryan Lowe, Xu Jiang This paper presents InstructGPT, a model fine-tuned with human feedback to better align with user intent across various tasks. Despite having significantly fewer parameters than larger models, InstructGPT outperforms them in human evaluations, demonstrating improved truthfulness, reduced toxicity, and minimal performance regressions on public NLP datasets, highlighting the potential of fine-tuning with human feedback for enhancing language model alignment with human intent. link

Pascal Fua

Paper Name Status Topic Category Year Conference Author Summary Link
0 Topological Loss: Beyond the Pixel-Wise Loss for Topology-Aware Delineation Pending Image , Loss Function, Segmentation 2018 CVPR Agata Mosinska, Mateusz Koziński, Pablo Márquez-Neila, Pascal Fua link

Paul Christiano

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training language models to follow instructions with human feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Semi-Supervised 2022 arXiv Carroll L. Wainwright, Diogo Almeida, Jan Leike, Jeff Wu, Long Ouyang, Pamela Mishkin, Paul Christiano, Ryan Lowe, Xu Jiang This paper presents InstructGPT, a model fine-tuned with human feedback to better align with user intent across various tasks. Despite having significantly fewer parameters than larger models, InstructGPT outperforms them in human evaluations, demonstrating improved truthfulness, reduced toxicity, and minimal performance regressions on public NLP datasets, highlighting the potential of fine-tuning with human feedback for enhancing language model alignment with human intent. link

Peng Zhou

Paper Name Status Topic Category Year Conference Author Summary Link
0 IMLE-GAN: Inclusive GAN: Improving Data and Minority Coverage in Generative Models Pending GANs 2020 arXiv Jitendra Malik, Ke Li, Larry Davis, Mario Fritz, Ning Yu, Peng Zhou link

Peter J. Liu

Paper Name Status Topic Category Year Conference Author Summary Link
0 T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Read Attention, Text , Transformers 2020 JMLR Colin Raffel, Noam Shazeer, Peter J. Liu, Wei Liu, Yanqi Zhou Presents a Text-to-Text transformer model with multi-task learning capabilities, simultaneously solving problems such as machine translation, document summarization, question answering, and classification tasks. link

Peter W. Battaglia

Paper Name Status Topic Category Year Conference Author Summary Link
0 Graph Neural Network: Relational inductive biases, deep learning, and graph networks Pending GraphNN Architecture 2018 arXiv Jessica B. Hamrick, Oriol Vinyals, Peter W. Battaglia link

Peter West

Paper Name Status Topic Category Year Conference Author Summary Link
0 Symbolic Knowledge Distillation: from General Language Models to Commonsense Models Pending Dataset, Text , Transformers Optimizations, Tips & Tricks 2021 arXiv Chandra Bhagavatula, Jack Hessel, Peter West, Yejin Choi link

Peter Wonka

Paper Name Status Topic Category Year Conference Author Summary Link
0 Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space? Pending GANs, Image 2019 ICCV Peter Wonka, Rameen Abdal, Yipeng Qin link

Phillip Isola

Paper Name Status Topic Category Year Conference Author Summary Link
0 Pix2Pix: Image-to-Image Translation with Conditional Adversarial Nets Read GANs, Image 2017 CVPR Alexei A. Efros, Jun-Yan Zhu, Phillip Isola, Tinghui Zhou Image to image translation using Conditional GANs and dataset of image pairs from one domain to another. link
1 CycleGAN: Unpaired Image-To-Image Translation Using Cycle-Consistent Adversarial Networks Pending GANs, Image Architecture 2017 ICCV Alexei A. Efros, Jun-Yan Zhu, Phillip Isola, Taesung Park link

Ping Yu

Paper Name Status Topic Category Year Conference Author Summary Link
0 Self-Alignment with Instruction Backtranslation Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning 2023 arXiv Jason Weston, Mike Lewis, Ping Yu, Xian Li The paper introduces a scalable method called "instruction backtranslation" to create a high-quality instruction-following language model. This method involves self-augmentation and self-curation of training examples generated from web documents, resulting in a model that outperforms others in its category without relying on distillation data, showcasing its effective self-alignment capability. link

Preetum Nakkiran

Paper Name Status Topic Category Year Conference Author Summary Link
0 Deep Double Descent: Where Bigger Models and More Data Hurt Pending NNs 2019 arXiv Boaz Barak, Gal Kaplun, Ilya Sutskever, Preetum Nakkiran, Tristan Yang, Yamini Bansal link

Qifan Wang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Learning to Extract Attribute Value from Product via Question Answering: A Multi-task Approach Read Question-Answering, Text , Transformers Zero-shot-learning 2020 KDD Li Yang, Qifan Wang Question Answering BERT model used to extract attributes from products. Introduce further No Answer loss and distillation to promote zero shot learning. link

Quoc V. Le

Paper Name Status Topic Category Year Conference Author Summary Link
0 Scaling Instruction-Finetuned Language Models (FLAN) Pending Generative, Large-Language-Models, Question-Answering, Text , Transformers Instruction-Finetuning 2022 arXiv Hyung Won Chung, Jason Wei, Jeffrey Dean, Le Hou, Quoc V. Le, Shayne Longpre https://arxiv.org/abs/2210.11416 introduces FLAN (Fine-tuned LAnguage Net), an instruction finetuning method, and presents the results of its application. The study demonstrates that by fine-tuning the 540B PaLM model on 1836 tasks while incorporating Chain-of-Thought Reasoning data, FLAN achieves improvements in generalization, human usability, and zero-shot reasoning over the base model. The paper also provides detailed information on how each these aspects was evaluated. link

Rameen Abdal

Paper Name Status Topic Category Year Conference Author Summary Link
0 Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space? Pending GANs, Image 2019 ICCV Peter Wonka, Rameen Abdal, Yipeng Qin link

Rayat Hossain

Paper Name Status Topic Category Year Conference Author Summary Link
0 A Simple yet Effective Baseline for 3D Human Pose Estimation Pending CV , Pose Estimation 2017 ICCV James J. Little, Javier Romero, Julieta Martinez, Rayat Hossain link

Rob Fergus

Paper Name Status Topic Category Year Conference Author Summary Link
0 ZF Net (Visualizing and Understanding Convolutional Networks) Read CNNs, CV , Image Visualization 2014 ECCV Matthew D. Zeiler, Rob Fergus Visualize CNN Filters / Kernels using De-Convolutions on CNN filter activations. link

Ronan Le Bras

Paper Name Status Topic Category Year Conference Author Summary Link
0 ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning Pending AGI, Dataset, Text 2019 AAAI Maarten Sap, Noah A. Smith, Ronan Le Bras, Yejin Choi link

Rosanne Liu

Paper Name Status Topic Category Year Conference Author Summary Link
0 Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask Read NN Initialization, NNs Comparison, Optimization-No. of params, Tips & Tricks 2019 NeurIPS Hattie Zhou, Janice Lan, Jason Yosinski, Rosanne Liu Follow up on Lottery Ticket Hypothesis exploring the effects of different Masking criteria as well as Mask-1 and Mask-0 actions. link

Ryan Lowe

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training language models to follow instructions with human feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Semi-Supervised 2022 arXiv Carroll L. Wainwright, Diogo Almeida, Jan Leike, Jeff Wu, Long Ouyang, Pamela Mishkin, Paul Christiano, Ryan Lowe, Xu Jiang This paper presents InstructGPT, a model fine-tuned with human feedback to better align with user intent across various tasks. Despite having significantly fewer parameters than larger models, InstructGPT outperforms them in human evaluations, demonstrating improved truthfulness, reduced toxicity, and minimal performance regressions on public NLP datasets, highlighting the potential of fine-tuning with human feedback for enhancing language model alignment with human intent. link

Samuli Laine

Paper Name Status Topic Category Year Conference Author Summary Link
0 StyleGAN: A Style-Based Generator Architecture for Generative Adversarial Networks Pending GANs, Image 2019 CVPR Samuli Laine, Tero Karras, Timo Aila link
1 Progressive Growing of GANs for Improved Quality, Stability, and Variation Pending GANs, Image Tips & Tricks 2018 ICLR Jaakko Lehtinen, Samuli Laine, Tero Karras, Timo Aila link

Santhosh K. Ramakrishnan

Paper Name Status Topic Category Year Conference Author Summary Link
0 Occupancy Anticipation for Efficient Exploration and Navigation Pending CNNs, Image Reinforcement-Learning 2020 ECCV Kristen Grauman, Santhosh K. Ramakrishnan, Ziad Al-Halah link

Sara Sabour

Paper Name Status Topic Category Year Conference Author Summary Link
0 Capsule Networks: Dynamic Routing Between Capsules Pending CV , Image Architecture 2017 arXiv Geoffrey E Hinton, Nicholas Frosst, Sara Sabour link

Scott Gray

Paper Name Status Topic Category Year Conference Author Summary Link
0 DALL·E: Creating Images from Text Pending Image , Text , Transformers 2021 Blog Aditya Ramesh, Gabriel Goh, Ilya Sutskever, Mikhail Pavlov, Scott Gray link

Sebastian Borgeaud

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training Compute-Optimal Large Language Models Pending Large-Language-Models, Transformers Architecture, Optimization-No. of params, Pre-Training, Tips & Tricks 2022 arXiv Jordan Hoffmann, Laurent Sifre, Oriol Vinyals, Sebastian Borgeaud link

Serge Belongie

Paper Name Status Topic Category Year Conference Author Summary Link
0 Arbitrary Style Transfer in Real-Time With Adaptive Instance Normalization Pending CNNs, Image 2017 ICCV Serge Belongie, Xun Huang link

Shayne Longpre

Paper Name Status Topic Category Year Conference Author Summary Link
0 Scaling Instruction-Finetuned Language Models (FLAN) Pending Generative, Large-Language-Models, Question-Answering, Text , Transformers Instruction-Finetuning 2022 arXiv Hyung Won Chung, Jason Wei, Jeffrey Dean, Le Hou, Quoc V. Le, Shayne Longpre https://arxiv.org/abs/2210.11416 introduces FLAN (Fine-tuned LAnguage Net), an instruction finetuning method, and presents the results of its application. The study demonstrates that by fine-tuning the 540B PaLM model on 1836 tasks while incorporating Chain-of-Thought Reasoning data, FLAN achieves improvements in generalization, human usability, and zero-shot reasoning over the base model. The paper also provides detailed information on how each these aspects was evaluated. link

Shibani Santurkar

Paper Name Status Topic Category Year Conference Author Summary Link
0 How Does Batch Normalization Help Optimization? Pending NNs, Normalization Optimizations 2018 arXiv Aleksander Madry, Andrew Ilyas, Dimitris Tsipras, Shibani Santurkar link

Shiyu Chang

Paper Name Status Topic Category Year Conference Author Summary Link
0 TransGAN: Two Transformers Can Make One Strong GAN Pending GANs, Image , Transformers Architecture 2021 arXiv Shiyu Chang, Yifan Jiang, Zhangyang Wang link

Shunyu Yao

Paper Name Status Topic Category Year Conference Author Summary Link
0 ReAct: Synergizing Reasoning and Acting in Language Models Pending Generative, Large-Language-Models, Text Optimizations, Tips & Tricks 2023 ICLR Dian Yu, Izhak Shafran, Jeffrey Zhao, Karthik Narasimhan, Nan Du, Shunyu Yao, Yuan Cao This paper introduces ReAct, a novel approach that leverages Large Language Models (LLMs) to interleave reasoning traces and task-specific actions. ReAct outperforms existing methods on various language and decision-making tasks, addressing issues like hallucination, error propagation, and improving human interpretability and trustworthiness. link

Song Han

Paper Name Status Topic Category Year Conference Author Summary Link
0 SqueezeNet Read CNNs, CV , Image Architecture, Optimization-No. of params 2016 arXiv Forrest N. Iandola, Song Han Explores model compression by using 1x1 convolutions called fire modules. link

Soumith Chintala

Paper Name Status Topic Category Year Conference Author Summary Link
0 WGAN: Wasserstein GAN Pending GANs, Loss Function 2017 arXiv Léon Bottou, Martin Arjovsky, Soumith Chintala link

Sowmya Yellapragada

Paper Name Status Topic Category Year Conference Author Summary Link
0 Understanding Loss Functions in Computer Vision Pending CV , GANs, Image , Loss Function Comparison, Tips & Tricks 2020 Blog Sowmya Yellapragada link

Stanislas Polu

Paper Name Status Topic Category Year Conference Author Summary Link
0 GPT-f: Generative Language Modeling for Automated Theorem Proving Pending Attention, Transformers 2020 arXiv Ilya Sutskever, Stanislas Polu link

Stephen Merity

Paper Name Status Topic Category Year Conference Author Summary Link
0 Single Headed Attention RNN: Stop Thinking With Your Head Pending Attention, LSTMs, Text Optimization-No. of params 2019 arXiv Stephen Merity link

Sudharshan Chandra Babu

Paper Name Status Topic Category Year Conference Author Summary Link
0 A 2019 guide to Human Pose Estimation with Deep Learning Pending CV , Pose Estimation Comparison 2019 Blog Sudharshan Chandra Babu link

Sunghun Kim

Paper Name Status Topic Category Year Conference Author Summary Link
0 StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation Pending GANs, Image 2018 CVPR Jaegul Choo, Jung-Woo Ha, Minje Choi, Munyoung Kim, Sunghun Kim, Yunjey Choi link

Taesung Park

Paper Name Status Topic Category Year Conference Author Summary Link
0 CycleGAN: Unpaired Image-To-Image Translation Using Cycle-Consistent Adversarial Networks Pending GANs, Image Architecture 2017 ICCV Alexei A. Efros, Jun-Yan Zhu, Phillip Isola, Taesung Park link

Takeru Miyato

Paper Name Status Topic Category Year Conference Author Summary Link
0 Spectral Normalization for GANs Pending GANs, Normalization Optimizations 2018 arXiv Masanori Koyama, Takeru Miyato, Toshiki Kataoka, Yuichi Yoshida link

Takeshi Kojima

Paper Name Status Topic Category Year Conference Author Summary Link
0 Large Language Models are Zero-Shot Reasoners Pending Generative, Question-Answering, Text Tips & Tricks, Zero-shot-learning 2022 arXiv Takeshi Kojima, Yusuke Iwasawa link

Tal Ridnik

Paper Name Status Topic Category Year Conference Author Summary Link
0 Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering Pending Large-Language-Models Prompting, Tips & Tricks 2024 arXiv Dedy Kredo, Itamar Friedman, Tal Ridnik This paper introduces AlphaCodium, a novel test-based, multi-stage, code-oriented iterative approach for improving the performance of Language Model Models (LLMs) on code generation tasks. link

Tero Karras

Paper Name Status Topic Category Year Conference Author Summary Link
0 StyleGAN: A Style-Based Generator Architecture for Generative Adversarial Networks Pending GANs, Image 2019 CVPR Samuli Laine, Tero Karras, Timo Aila link
1 Progressive Growing of GANs for Improved Quality, Stability, and Variation Pending GANs, Image Tips & Tricks 2018 ICLR Jaakko Lehtinen, Samuli Laine, Tero Karras, Timo Aila link

Thomas Schumm

Paper Name Status Topic Category Year Conference Author Summary Link
0 BEGAN: Boundary Equilibrium Generative Adversarial Networks Pending GANs, Image 2017 arXiv David Berthelot, Luke Metz, Thomas Schumm link

Thomas Unterthiner

Paper Name Status Topic Category Year Conference Author Summary Link
0 Self-Normalizing Neural Networks Pending Activation Function, Tabular Optimizations, Tips & Tricks 2017 NIPS Andreas Mayr, Günter Klambauer, Thomas Unterthiner link

Tim Salimans

Paper Name Status Topic Category Year Conference Author Summary Link
0 Improved Techniques for Training GANs Pending GANs, Image Semi-Supervised 2016 NIPS Alec Radford, Ian Goodfellow, Tim Salimans, Vicki Cheung, Wojciech Zaremba, Xi Chen link

Timo Aila

Paper Name Status Topic Category Year Conference Author Summary Link
0 StyleGAN: A Style-Based Generator Architecture for Generative Adversarial Networks Pending GANs, Image 2019 CVPR Samuli Laine, Tero Karras, Timo Aila link
1 Progressive Growing of GANs for Improved Quality, Stability, and Variation Pending GANs, Image Tips & Tricks 2018 ICLR Jaakko Lehtinen, Samuli Laine, Tero Karras, Timo Aila link

Timothy Dozat

Paper Name Status Topic Category Year Conference Author Summary Link
0 NADAM: Incorporating Nesterov Momentum into Adam Pending NNs, Optimizers Comparison 2016 Timothy Dozat link

Tinghui Zhou

Paper Name Status Topic Category Year Conference Author Summary Link
0 Pix2Pix: Image-to-Image Translation with Conditional Adversarial Nets Read GANs, Image 2017 CVPR Alexei A. Efros, Jun-Yan Zhu, Phillip Isola, Tinghui Zhou Image to image translation using Conditional GANs and dataset of image pairs from one domain to another. link

Tomas Mikolov

Paper Name Status Topic Category Year Conference Author Summary Link
0 Word2Vec: Efficient Estimation of Word Representations in Vector Space Pending Text Embeddings, Tips & Tricks 2013 arXiv Greg Corrado, Jeffrey Dean, Kai Chen, Tomas Mikolov link

Tong He

Paper Name Status Topic Category Year Conference Author Summary Link
0 Bag of Tricks for Image Classification with Convolutional Neural Networks Read CV , Image Optimizations, Tips & Tricks 2018 arXiv Tong He, Zhi Zhang Shows a dozen tricks (mixup, label smoothing, etc.) to improve CNN accuracy and training time. link

Toshiki Kataoka

Paper Name Status Topic Category Year Conference Author Summary Link
0 Spectral Normalization for GANs Pending GANs, Normalization Optimizations 2018 arXiv Masanori Koyama, Takeru Miyato, Toshiki Kataoka, Yuichi Yoshida link

Tristan Yang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Deep Double Descent: Where Bigger Models and More Data Hurt Pending NNs 2019 arXiv Boaz Barak, Gal Kaplun, Ilya Sutskever, Preetum Nakkiran, Tristan Yang, Yamini Bansal link

Vicki Cheung

Paper Name Status Topic Category Year Conference Author Summary Link
0 Improved Techniques for Training GANs Pending GANs, Image Semi-Supervised 2016 NIPS Alec Radford, Ian Goodfellow, Tim Salimans, Vicki Cheung, Wojciech Zaremba, Xi Chen link

Wei Lin

Paper Name Status Topic Category Year Conference Author Summary Link
0 One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information Extraction Pending Image , Text 2020 arXiv Jun Huang, Mengli Cheng, Minghui Qiu, Wei Lin, Xing Shi link

Wei Liu

Paper Name Status Topic Category Year Conference Author Summary Link
0 Inception-v1 (Going Deeper With Convolutions) Read CNNs, CV , Image Architecture 2015 CVPR Christian Szegedy, Wei Liu Propose the use of 1x1 conv operations to reduce the number of parameters in a deep and wide CNN link
1 T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Read Attention, Text , Transformers 2020 JMLR Colin Raffel, Noam Shazeer, Peter J. Liu, Wei Liu, Yanqi Zhou Presents a Text-to-Text transformer model with multi-task learning capabilities, simultaneously solving problems such as machine translation, document summarization, question answering, and classification tasks. link

Wieland Brendel

Paper Name Status Topic Category Year Conference Author Summary Link
0 Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet Reading CNNs, CV , Image 2019 arXiv Matthias Bethge, Wieland Brendel link

Wojciech Zaremba

Paper Name Status Topic Category Year Conference Author Summary Link
0 Improved Techniques for Training GANs Pending GANs, Image Semi-Supervised 2016 NIPS Alec Radford, Ian Goodfellow, Tim Salimans, Vicki Cheung, Wojciech Zaremba, Xi Chen link

Xi Chen

Paper Name Status Topic Category Year Conference Author Summary Link
0 Improved Techniques for Training GANs Pending GANs, Image Semi-Supervised 2016 NIPS Alec Radford, Ian Goodfellow, Tim Salimans, Vicki Cheung, Wojciech Zaremba, Xi Chen link

Xian Li

Paper Name Status Topic Category Year Conference Author Summary Link
0 Self-Alignment with Instruction Backtranslation Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning 2023 arXiv Jason Weston, Mike Lewis, Ping Yu, Xian Li The paper introduces a scalable method called "instruction backtranslation" to create a high-quality instruction-following language model. This method involves self-augmentation and self-curation of training examples generated from web documents, resulting in a model that outperforms others in its category without relying on distillation data, showcasing its effective self-alignment capability. link

Xiangyu Zhang

Paper Name Status Topic Category Year Conference Author Summary Link
0 ResNet (Deep Residual Learning for Image Recognition) Read CNNs, CV , Image Architecture 2016 CVPR Kaiming He, Xiangyu Zhang Introduces Residual or Skip Connections to allow increase in the depth of a DNN link

Xiaofei Sun

Paper Name Status Topic Category Year Conference Author Summary Link
0 Interpreting Deep Learning Models in Natural Language Processing: A Review Pending Text Comparison, Visualization 2021 arXiv Diyi Yang, Xiaofei Sun link

Xing Shi

Paper Name Status Topic Category Year Conference Author Summary Link
0 One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information Extraction Pending Image , Text 2020 arXiv Jun Huang, Mengli Cheng, Minghui Qiu, Wei Lin, Xing Shi link

Xu Jiang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Training language models to follow instructions with human feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Semi-Supervised 2022 arXiv Carroll L. Wainwright, Diogo Almeida, Jan Leike, Jeff Wu, Long Ouyang, Pamela Mishkin, Paul Christiano, Ryan Lowe, Xu Jiang This paper presents InstructGPT, a model fine-tuned with human feedback to better align with user intent across various tasks. Despite having significantly fewer parameters than larger models, InstructGPT outperforms them in human evaluations, demonstrating improved truthfulness, reduced toxicity, and minimal performance regressions on public NLP datasets, highlighting the potential of fine-tuning with human feedback for enhancing language model alignment with human intent. link

Xuezhi Wang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Chain of Thought Prompting Elicits Reasoning in Large Language Models Pending Question-Answering, Text , Transformers 2022 arXiv Denny Zhou, Jason Wei, Xuezhi Wang link

Xun Huang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Arbitrary Style Transfer in Real-Time With Adaptive Instance Normalization Pending CNNs, Image 2017 ICCV Serge Belongie, Xun Huang link

Yamini Bansal

Paper Name Status Topic Category Year Conference Author Summary Link
0 Deep Double Descent: Where Bigger Models and More Data Hurt Pending NNs 2019 arXiv Boaz Barak, Gal Kaplun, Ilya Sutskever, Preetum Nakkiran, Tristan Yang, Yamini Bansal link

Yanghua Jin

Paper Name Status Topic Category Year Conference Author Summary Link
0 AnimeGAN: Towards the Automatic Anime Characters Creation with Generative Adversarial Networks Pending GANs, Image 2017 NIPS Jiakai Zhang, Minjun Li, Yanghua Jin link

Yanqi Zhou

Paper Name Status Topic Category Year Conference Author Summary Link
0 T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Read Attention, Text , Transformers 2020 JMLR Colin Raffel, Noam Shazeer, Peter J. Liu, Wei Liu, Yanqi Zhou Presents a Text-to-Text transformer model with multi-task learning capabilities, simultaneously solving problems such as machine translation, document summarization, question answering, and classification tasks. link

Yejin Choi

Paper Name Status Topic Category Year Conference Author Summary Link
0 ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning Pending AGI, Dataset, Text 2019 AAAI Maarten Sap, Noah A. Smith, Ronan Le Bras, Yejin Choi link
1 COMET: Commonsense Transformers for Automatic Knowledge Graph Construction Pending AGI, Text , Transformers 2019 ACL Antoine Bosselut, Hannah Rashkin, Yejin Choi link
2 VisualCOMET: Reasoning about the Dynamic Context of a Still Image Pending AGI, Dataset, Image , Text , Transformers 2020 ECCV Ali Farhadi, Chandra Bhagavatula, Jae Sung Park, Yejin Choi link
3 Symbolic Knowledge Distillation: from General Language Models to Commonsense Models Pending Dataset, Text , Transformers Optimizations, Tips & Tricks 2021 arXiv Chandra Bhagavatula, Jack Hessel, Peter West, Yejin Choi link

Ygor Rebouças Serpa

Paper Name Status Topic Category Year Conference Author Summary Link
0 A Comprehensive Guide on Activation Functions This week Activation Function 2020 Blog Ygor Rebouças Serpa link

Yifan Jiang

Paper Name Status Topic Category Year Conference Author Summary Link
0 TransGAN: Two Transformers Can Make One Strong GAN Pending GANs, Image , Transformers Architecture 2021 arXiv Shiyu Chang, Yifan Jiang, Zhangyang Wang link

Yin Cui

Paper Name Status Topic Category Year Conference Author Summary Link
0 Class-Balanced Loss Based on Effective Number of Samples Pending Loss Function Tips & Tricks 2019 CVPR Menglin Jia, Yin Cui link

Yinfei Yang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Language-Agnostic BERT Sentence Embedding Read Attention, Siamese Network, Text , Transformers Embeddings 2020 arXiv Fangxiaoyu Feng, Yinfei Yang A BERT model with multilingual sentence embeddings learned over 112 languages and Zero-shot learning over unseen languages. link

Yipeng Qin

Paper Name Status Topic Category Year Conference Author Summary Link
0 Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space? Pending GANs, Image 2019 ICCV Peter Wonka, Rameen Abdal, Yipeng Qin link

Yuan Cao

Paper Name Status Topic Category Year Conference Author Summary Link
0 ReAct: Synergizing Reasoning and Acting in Language Models Pending Generative, Large-Language-Models, Text Optimizations, Tips & Tricks 2023 ICLR Dian Yu, Izhak Shafran, Jeffrey Zhao, Karthik Narasimhan, Nan Du, Shunyu Yao, Yuan Cao This paper introduces ReAct, a novel approach that leverages Large Language Models (LLMs) to interleave reasoning traces and task-specific actions. ReAct outperforms existing methods on various language and decision-making tasks, addressing issues like hallucination, error propagation, and improving human interpretability and trustworthiness. link

Yuichi Yoshida

Paper Name Status Topic Category Year Conference Author Summary Link
0 Spectral Normalization for GANs Pending GANs, Normalization Optimizations 2018 arXiv Masanori Koyama, Takeru Miyato, Toshiki Kataoka, Yuichi Yoshida link

Yunjey Choi

Paper Name Status Topic Category Year Conference Author Summary Link
0 StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation Pending GANs, Image 2018 CVPR Jaegul Choo, Jung-Woo Ha, Minje Choi, Munyoung Kim, Sunghun Kim, Yunjey Choi link

Yuntao Ba

Paper Name Status Topic Category Year Conference Author Summary Link
0 Constitutional AI: Harmlessness from AI Feedback Pending Generative, Large-Language-Models, Training Method Instruction-Finetuning, Reinforcement-Learning, Unsupervised 2022 arXiv Jared Kaplan, Yuntao Ba The paper introduces Constitutional AI, a method for training a safe AI assistant without human-labeled data on harmful outputs. It combines supervised learning and reinforcement learning phases, enabling the AI to engage with harmful queries by explaining its objections, thus improving control, transparency, and human-judged performance with minimal human oversight. link

Yusuke Iwasawa

Paper Name Status Topic Category Year Conference Author Summary Link
0 Large Language Models are Zero-Shot Reasoners Pending Generative, Question-Answering, Text Tips & Tricks, Zero-shot-learning 2022 arXiv Takeshi Kojima, Yusuke Iwasawa link

Yuxin Wu

Paper Name Status Topic Category Year Conference Author Summary Link
0 Group Normalization Pending NNs, Normalization Optimizations 2018 arXiv Kaiming He, Yuxin Wu link

Zhangyang Wang

Paper Name Status Topic Category Year Conference Author Summary Link
0 TransGAN: Two Transformers Can Make One Strong GAN Pending GANs, Image , Transformers Architecture 2021 arXiv Shiyu Chang, Yifan Jiang, Zhangyang Wang link

Zhen Tan

Paper Name Status Topic Category Year Conference Author Summary Link
0 Large Language Models for Data Annotation: A Survey This week Dataset, Generative, Large-Language-Models Prompting, Tips & Tricks 2024 arXiv Alimohammad Beigi, Zhen Tan link

Zhi Zhang

Paper Name Status Topic Category Year Conference Author Summary Link
0 Bag of Tricks for Image Classification with Convolutional Neural Networks Read CV , Image Optimizations, Tips & Tricks 2018 arXiv Tong He, Zhi Zhang Shows a dozen tricks (mixup, label smoothing, etc.) to improve CNN accuracy and training time. link

Ziad Al-Halah

Paper Name Status Topic Category Year Conference Author Summary Link
0 Occupancy Anticipation for Efficient Exploration and Navigation Pending CNNs, Image Reinforcement-Learning 2020 ECCV Kristen Grauman, Santhosh K. Ramakrishnan, Ziad Al-Halah link

Łukasz Kaiser

Paper Name Status Topic Category Year Conference Author Summary Link
0 Attention is All you Need Read Attention, Text , Transformers Architecture 2017 NIPS Ashish Vaswani, Illia Polosukhin, Noam Shazeer, Łukasz Kaiser Talks about Transformer architecture which brings SOTA performance for different tasks in NLP link