1 citations · 3 across the 8 of their papers we have counts for
3 papers · 2 filters
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…
Dynamic Speculation Lookahead Accelerates Speculative Decoding of Large Language Models
Jonathan Mamou, Oren Pereg, Daniel Korat +4
Speculative decoding is commonly used for reducing the inference latency of large language models. Its effectiveness depends highly on the speculation lookahead (SL)-the number of…
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…