Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs Paper • 2404.15676 • Published Apr 24
How faithful are RAG models? Quantifying the tug-of-war between RAG and LLMs' internal prior Paper • 2404.10198 • Published Apr 16 • 7
From Local to Global: A Graph RAG Approach to Query-Focused Summarization Paper • 2404.16130 • Published Apr 24 • 4
RAGGED: Towards Informed Design of Retrieval Augmented Generation Systems Paper • 2403.09040 • Published Mar 14 • 1
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts Paper • 2405.19893 • Published May 30 • 29
From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries Paper • 2406.12824 • Published Jun 18 • 20
ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities Paper • 2407.14482 • Published Jul 19 • 25
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore Paper • 2407.12854 • Published Jul 9 • 29
Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation Paper • 2409.12941 • Published Sep 19 • 23
StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurization Paper • 2410.08815 • Published Oct 11 • 43
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding Paper • 2411.04952 • Published Nov 7 • 28