3 papers
cs.CL2026
No Prompt Left Behind: Exploiting Zero-Variance Prompts in LLM Reinforcement Learning via Entropy-Guided Advantage Shaping
Thanh-Long V. Le, Myeongho Jeon, Kim Vu +2
Reinforcement Learning with Verifiable Rewards (RLVR) is a powerful framework for improving the reasoning abilities of Large Language Models (LLMs). However, current methods such a…
cs.LG2025
Weak-to-Strong Generalization under Distribution Shifts
Myeongho Jeon, Jan Sobotka, Suhwan Choi +1
As future superhuman models become increasingly complex, accurately supervising their behavior may exceed human capabilities. Recent works have demonstrated that in such scenarios,…
cs.LG2025
An Analysis of Model Robustness across Concurrent Distribution Shifts
Myeongho Jeon, Suhwan Choi, Hyoje Lee +1
Machine learning models, meticulously optimized for source data, often fail to predict target data when faced with distribution shifts (DSs). Previous benchmarking studies, though…