ariafyy / rag_survey

RAG

RAG (Retrieved-Augmented Generation) for LLM:

A Curated Collection

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.

Updates

• [2023-11-03] Repo initialization

Table of Content

• Papers
  • LLM-based
• Tools

RAG-papers

LLM-based

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) ACL 2023 Tutorial:Retrieval-based Language Models and Applications	Web, Github

Benchmarks

Paper	Links
1) RAGAS: Automated Evaluation of Retrieval Augmented Generation	Paper
2) Benchmarking Large Language Models in Retrieval-Augmented Generation	Paper

Language Agents

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

RAG-tools

Paper	Links

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Acknowledgement

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.

Star History

References

• CoALA: Awesome Language Agents: Github

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