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cs.LG2026
Does Compression Imply Generalization? A Minimum Description Length Perspective
Lincen Yang, Jiayang Shi, Nan Pu +4
A central question in modern learning theory is what notion of compression, if any, explains why over-parameterized neural networks generalize. Existing answers measure complexity…
cs.CV2026
SMILE: Self-Explainable Multimodal Information Bottleneck for Medical Diagnosis
Yuqing Yang, Alexander Schmatz, Zhaozhao Ma +3
Explainability is increasingly seen as a crucial requirement in AI-based medical diagnosis, particularly in safety-critical clinical decision-making. Most existing explainability m…
cs.LG2026
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning
Zhao Yang, Yuxuan Jiang, Ting-Chih Chen +18
Reinforcement learning (RL) has become central to LLM post-training, yet the methods that dominate current pipelines, PPO and GRPO, represent only a narrow slice of what RL offers.…