11 citations · 26 across the 16 of their papers we have counts for
4 papers · 2 filters
Don't Overthink it. Preferring Shorter Thinking Chains for Improved LLM Reasoning
Michael Hassid, Gabriel Synnaeve, Yossi Adi +1
Reasoning large language models (LLMs) heavily rely on scaling test-time compute to perform complex reasoning tasks by generating extensive "thinking" chains. While demonstrating i…
Scaling Analysis of Interleaved Speech-Text Language Models
Gallil Maimon, Michael Hassid, Amit Roth +1
Existing Speech Language Model (SLM) scaling analysis paints a bleak picture. It predicts that SLMs require much more compute and data compared to text, leading some to question th…
More Documents, Same Length: Isolating the Challenge of Multiple Documents in RAG
Shahar Levy, Nir Mazor, Lihi Shalmon +2
Retrieval-Augmented Generation (RAG) enhances the accuracy of Large Language Model (LLM) responses by leveraging relevant external documents during generation. Although previous st…
On Pruning State-Space LLMs
Tamer Ghattas, Michael Hassid, Roy Schwartz
Recent work proposed state-space models (SSMs) as an efficient alternative to transformer-based LLMs. Can these models be pruned to further reduce their computation costs? We adapt…