This repository is dedicated to curating high-quality papers, resources, and tools related to RAG in the context of Large Language Models (LLM). RAG bridges the gap between retrieval-based and generation-based methods, offering a promising approach for knowledge-intensive tasks.
| Name | Links |
|---|---|
| 1) RAGAS: Automated Evaluation of Retrieval Augmented Generation | Paper |
| 2) Benchmarking Large Language Models in Retrieval-Augmented Generation | Paper |
| Name | Links |
|---|---|
| 1) ACL 2023 Tutorial: Retrieval-based Language Models and Applications | Web, Github |
| Paper | Links |
|---|---|
| 1) RETRO : Improving language models by retrieving from trillions of tokens | Paper |
| 2) Atlas : Few-shot Learning with Retrieval Augmented Language Models | Paper, Github |
| 3) RALM : In-Context Retrieval-Augmented Language Models | Paper, Github |
| 4) Self-RAG : LLM-based Retrieval by generating and reflecting on retrieved passages | Paper, Github |
| 5) Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy | Paper |
| 6) Exploring the Integration Strategies of Retriever and Large Language Models | Paper |
| 7) Generator-Retriever-Generator: A Novel Approach to Open-domain Question Answering | Paper, Github |
| 8) REPLUG : Retrieval-Augmented Black-Box Language Models | Paper |
| 9) Surface-Based Retrieval Reduces Perplexity of Retrieval-Augmented Language Models | Paper, Github |
| 10) Retrieval-Generation Alignment for End-to-End Task-Oriented Dialogue System | Paper, Github |
| 11) Beam Retrieval: General End-to-End Retrieval for Multi-Hop Question Answering | Paper, Github |
| 12) Retrieval-Generation Synergy Augmented Large Language Models | Paper |
| 13) Enabling Large Language Models to Generate Text with Citations | Paper, Github |
| 14) Improving Language Models by Retrieving From Trillions of Tokens | Paper |
| 15) Internet-Augmented Language Models through Few-Shot Prompting for Open-Domain Question Answering | Paper |
| 16) Rethinking with Retrieval: Faithful Large Language Model Inference | Paper |
| 17) Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions | Paper |
| 18) Active Retrieval Augmented Generation | Paper |
| 19) Retrieve Anything To Augment Large Language Models | Paper |
| 20) ReAct: Synergizing Reasoning and Acting in Language Models | Paper |
| 21) Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback | Paper |
| 22) Teaching Language Models to Support Answers with Verified Quotes | Paper |
| 23) Augmented Language Models: a Survey | Paper |
| 24) LeanDojo: Theorem Proving with Retrieval-Augmented Language Models | Paper |
| 25) Retrieval-Augmented Multimodal Language Modeling | Paper |
| 26) RA-DIT: RETRIEVAL-AUGMENTED DUAL INSTRUCTION TUNING | Paper |
| 27) Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT | Paper |
| 28) Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In | Paper, Github |
| 29) Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question Answering | Paper, Github |
| 30) Self-Knowledge Guided Retrieval Augmentation for Large Language Models | Paper |
| Paper | Links |
|---|---|
| 1) Cognitive Architectures for Language Agents | Paper, Github |
| 2) Generative Agents: Interactive Simulacra of Human Behavior (grounding, reasoning, retrieval, learning) |
Paper, Github |
| 3) CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing (grounding, reasoning, retrieval) |
Paper, Github |
| 4) Voyager: An Open-Ended Embodied Agent with Large Language Models (grounding, reasoning, retrieval, learning) |
Paper, Github |
| 5) ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs (grounding, reasoning, retrieval) |
Paper, Github |
| 6) ExpeL: LLM Agents Are Experiential Learners (grounding, reasoning, retrieval, learning) |
Paper |
| 7) Synergistic Integration of Large Language Models and Cognitive Architectures for Robust AI: An Exploratory Analysis (grounding, reasoning, retrieval, learning) |
Paper |
- CoALA: Awesome Language Agents: Github
We welcome contributions! If you come across a relevant paper or resource that should be included, please open a pull request or issue. Ensure that your suggestions adhere to the repository's standards.