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cs.LG2026
Breaking Training Bottlenecks: Effective and Stable Reinforcement Learning for Coding Models
Zongqian Li, Shaohan Huang, Zewen Chi +5
Modern code generation models exhibit longer outputs, accelerated capability growth, and changed training dynamics, rendering traditional training methodologies, algorithms, and da…
cs.LG2026
From Human-Level AI Tales to AI Leveling Human Scales
Peter Romero, Fernando Martínez-Plumed, Zachary R. Tidler +11
Comparing AI models to "human level" is often misleading when benchmark scores are incommensurate or human baselines are drawn from a narrow population. To address this, we propose…