A curated list of retrieval-augmented generation (RAG) in large language models.
Suggest and discuss possible enhancements on the Potential Additions page.
Table of Content:
2024
-
Retrieval-Augmented Generation for Large Language Models: A Survey
Paper
Code
arXiv
-
Retrieval-Augmented Generation for Natural Language Processing: A Survey
Paper
arXiv
2023
- Benchmarking Large Language Models in Retrieval-Augmented Generation
Paper
arXiv
2022
- A Survey on Retrieval-Augmented Text Generation
Paper
arXiv
2024
-
Learning to Retrieve In-Context Examples for Large Language Models
Paper
Code
EACL
-
Reliable, Adaptable, and Attributable Language Models with Retrieval
Paper
arXiv
2023
-
Active Retrieval Augmented Generation
Paper
Code
EMNLP
Architecture
-
⭐ REPLUG: Retrieval-Augmented Black-Box Language Models
Paper
arXiv
Architecture
-
Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study
Paper
Code
EMNLP
-
InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining
Paper
Code
arXiv
-
Retrieve Anything To Augment Large Language Models
Paper
Code
arXiv
-
Reimagining Retrieval Augmented Language Models for Answering Queries
Paper
ACL
-
In-Context Retrieval-Augmented Language Models
Paper
Code
TACL
Architecture
-
Query Rewriting for Retrieval-Augmented Large Language Models
Paper
Code
EMNLP
-
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute
Paper
PMLR
-
Universal Information Extraction with Meta-Pretrained Self-Retrieval
Paper
Code
ACL
-
RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models
Paper
arXiv
-
Unlimiformer: Long-Range Transformers with Unlimited Length Input
Paper
Code
NeurIPS
Architecture
-
Nonparametric Masked Language Modeling
Paper
Code
ACL
Training
2022
-
Improving language models by retrieving from trillions of tokens
Paper
Blog
PMLR
Architecture
-
⭐ Atlas: Few-shot Learning with Retrieval Augmented Language Models
Paper
Code
Blog
Training
JMLR
-
You can't pick your neighbors, or can you? When and how to rely on retrieval in the kNN-LM
Paper
ACL
Architecture
-
Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval
Paper
Code
ICML
Architecture
-
Training Language Models with Memory Augmentation
Paper
EMNLP
Training
-
Unsupervised Dense Information Retrieval with Contrastive Learning
Paper
Code
arXiv
Training
-
Teaching language models to support answers with verified quotes
Paper
arXiv
Application
-
kNN-Prompt: Nearest Neighbor Zero-Shot Inference
Paper
Code
EMNLP
Application
2021
-
Efficient Nearest Neighbor Language Models
Paper
Code
EMNLP
Architecture
-
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention
Paper
Code
arXiv
Architecture
2020
-
⭐ REALM: Retrieval-Augmented Language Model Pre-Training
Paper
Code
HuggingFace
PMLR
Architecture
-
Generalization through Memorization: Nearest Neighbor Language Models
Paper
Code
ICLR
Architecture
-
Entities as Experts: Sparse Memory Access with Entity Supervision
Paper
EMNLP
Architecture
-
Dense Passage Retrieval for Open-Domain Question Answering
Paper
Code
EMNLP
Training
-
⭐ Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Paper
HuggingFace
NeurIPS
2024
2023
-
Stanford CS25: V3 I Retrieval Augmented Language Models
Douwe Kiela (2023)Lecture
Video
-
Building RAG-based LLM Applications for Production
Anyscale (2023)Tutorial
Blog
-
Multi-Vector Retriever for RAG on tables, text, and images
LangChain (2023)Tutorial
Blog
-
Retrieval-based Language Models and Applications
Asai et al. (2023)Tutorial
ACL
Website
Video
-
Advanced RAG Techniques: an Illustrated Overview
Ivan Ilin (2023)Tutorial
Blog
-
Retrieval Augmented Language Modeling
Melissa Dell (2023)Lecture
Video
2024
- Towards Knowledgeable Language Models
Zoey Sha Li, Manling Li, Michael JQ Zhang, Eunsol Choi, Mor Geva, Peter Hase
@ACL
2024, August 12-17
Website
-
LangChain
LangChain is a framework for developing applications powered by language models.
Website
-
LlamaIndex
LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models.
Website
-
Verba
Verba is an open-source application designed to offer an end-to-end, streamlined, and user-friendly interface for Retrieval-Augmented Generation (RAG) out of the box.
Website
-
NEUM
Open-source RAG framework optimized for large-scale and real-time data.
Website
-
Unstructured
Unstructured.io offers a powerful toolkit that handles the ingestion and data preprocessing step, allowing you to focus on the more exciting downstream steps in your machine learning pipeline. Unstructured has over a dozen data connectors that easily integrate with various data sources, including AWS S3, Discord, Slack, Wikipedia, and more.
Website
- Awesome LLM RAG
- Awesome RAG
- Awesome LLM with RAG
- RAG-Survey
- Awesome LLM Reader: A Repository of Retrieval-augmented LLMs