8 papers
Preventive Care Recommendations by Large Language Models
Eden Avnat, Elia Yanko, Ori Yoran +1
Preventive care services (PCS) extend life, yet physicians often underprioritize highly effective interventions such as lifestyle modifications (Zhang et al., JAMA Network Open 202…
Self-Execution Simulation Improves Coding Models
Gallil Maimon, Ori Yoran, Felix Kreuk +4
A promising research direction in enabling LLMs to generate consistently correct code involves addressing their inability to properly estimate program execution, particularly for c…
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…
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations
Daniela Gottesman, Alon Gilae-Dotan, Ido Cohen +4
Language models (LMs) increasingly drive real-world applications that require world knowledge. However, the internal processes through which models turn data into representations o…
Preventing Rogue Agents Improves Multi-Agent Collaboration
Ohav Barbi, Ori Yoran, Mor Geva
Multi-agent systems, where specialized agents collaborate to solve a shared task hold great potential, from increased modularity to simulating complex environments. However, they a…
The KoLMogorov Test: Compression by Code Generation
Ori Yoran, Kunhao Zheng, Fabian Gloeckle +3
Compression is at the heart of intelligence. A theoretically optimal way to compress any sequence of data is to find the shortest program that outputs that sequence and then halts.…