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cs.LG2025
Mitigating Reward Over-optimization in Direct Alignment Algorithms with Importance Sampling
Phuc Minh Nguyen, Ngoc-Hieu Nguyen, Duy H. M. Nguyen +5
Direct Alignment Algorithms (DAAs) such as Direct Preference Optimization (DPO) have emerged as alternatives to the standard Reinforcement Learning from Human Feedback (RLHF) for a…
cs.LG2025
When Reasoning Meets Compression: Understanding the Effects of LLMs Compression on Large Reasoning Models
Nan Zhang, Eugene Kwek, Yusen Zhang +3
Compression methods, including quantization, distillation, and pruning, improve the computational efficiency of large reasoning models (LRMs). However, existing studies either fail…