11 citations · 26 across the 16 of their papers we have counts for
5 papers · 1 filter
CWM: An Open-Weights LLM for Research on Code Generation with World Models
FAIR CodeGen team, Jade Copet, Quentin Carbonneaux +48
We release Code World Model (CWM), a 32-billion-parameter open-weights LLM, to advance research on code generation with world models. To improve code understanding beyond what can…
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…