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.
- [2023-11-03] Repo initialization
| 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 |
| 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 |
| Paper | Links |
|---|
|
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.
- CoALA: Awesome Language Agents: Github
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