297 citations · 297 across the 10 of their papers we have counts for
3 papers · 2 filters
Post-training is (Massive) Supervised Learning
Michael Hassid, Yossi Adi, Roy Schwartz
The prevailing paradigm for training LLMs has evolved to rely on a massive post-training phase consisting of SFT and RL. In this position paper, we argue that this methodology effe…
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…
LLMs versus the Halting Problem: Characterizing Program Termination Reasoning
Oren Sultan, Jordi Armengol-Estape, Pascal Kesseli +4
Determining whether a program terminates is a central problem in computer science. Turing's Halting Problem established termination as undecidable, showing that no algorithm can un…