Awesome RAG 📄🔍

A curated list of awesome resources for RAG (Retrieval Augmentation Generation) exploration.

Table of Contents

• Papers
• Blogposts

Papers

• RAG: Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks - An information retrieval augmented generation model that can be used for various knowledge-intensive NLP tasks. (Lewis, Patrick, et al. 2020)

• RA-DIT: Retrieval-Augmented Dual Instruction Tuning (RA-DIT) - Improve the performance of retrieval-augmented generation models by fine-tuning the retrieval and generation components jointly. (Khattar, Dheeraj, et al. 2021)

• CRAG - Corrective Retrieval Augmented Generation Llama Pack - Enhance the robustness of language model generation by evaluating and augmenting the relevance of retrieved documents through a an evaluator and large-scale web searches. (Shi-Qi Yan, Jia-Chen Gu, et al. 2024)

• Dense x Retrieval: What Retrieval Grnaularity Should We Use? - Improve dense retrieval by using a more fine-grained retrieval granularity as known as Propositions. (Tong Chen, et al. 2023)

• In-Context Learning for Extreme Multi-Label Classification - A retrieval-augmented generation model that can be used for extreme multi-label classification. (Karel, et al. 2021)

• Self-Discover: Large Language Models Self-Compose Reasoning Structures - A retrieval-augmented generation model that can be used for self-composing reasoning structures. (Pei, et al. 2021)

• SELF-RAG: LEARNING TO RETRIEVE, GENERATE, AND CRITIQUE THROUGH SELF-REFLECTION - A retrieval-augmented generation model that can be used for self-reflection. (Akari, et al. 2023)

• Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding - A retrieval-augmented generation model that can be used for table understanding. (Zilong, et al. 2024)

Contributing

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