Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs
Paper
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2404.15676
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Published
RAG
RAG research
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How faithful are RAG models? Quantifying the tug-of-war between RAG and LLMs' internal prior
Paper • 2404.10198 • Published • 7 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 73 -
FaaF: Facts as a Function for the evaluation of RAG systems
Paper • 2403.03888 • Published -
From Local to Global: A Graph RAG Approach to Query-Focused Summarization
Paper • 2404.16130 • Published • 6 -
RAGGED: Towards Informed Design of Retrieval Augmented Generation Systems
Paper • 2403.09040 • Published • 1 -
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts
Paper • 2405.19893 • Published • 32 -
CRAG -- Comprehensive RAG Benchmark
Paper • 2406.04744 • Published • 49 -
From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries
Paper • 2406.12824 • Published • 21 -
ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities
Paper • 2407.14482 • Published • 27 -
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore
Paper • 2407.12854 • Published • 32 -
Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation
Paper • 2409.12941 • Published • 25 -
StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurization
Paper • 2410.08815 • Published • 49 -
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding
Paper • 2411.04952 • Published • 30 -
ReaRAG: Knowledge-guided Reasoning Enhances Factuality of Large Reasoning Models with Iterative Retrieval Augmented Generation
Paper • 2503.21729 • Published • 28 -
Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models
Paper • 2505.04921 • Published • 175