39 citations · 87 across the 7 of their papers we have counts for
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cs.CL2024★ 1 cited
RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation
Daniel Fleischer, Moshe Berchansky, Moshe Wasserblat +1
Implementing Retrieval-Augmented Generation (RAG) systems is inherently complex, requiring deep understanding of data, use cases, and intricate design decisions. Additionally, eval…
cs.CL2024
CoTAR: Chain-of-Thought Attribution Reasoning with Multi-level Granularity
Moshe Berchansky, Daniel Fleischer, Moshe Wasserblat +1
State-of-the-art performance in QA tasks is currently achieved by systems employing Large Language Models (LLMs), however these models tend to hallucinate information in their resp…