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cs.LG2026
GRLO: Towards Generalizable Reinforcement Learning in Open-Ended Environments from Zero
Shangjian Yin, Yu Fu, Yue Dong +1
Post-training has become a crucial step for unlocking the capabilities of large language models, with reinforcement learning (RL) emerging as a critical paradigm. Recent RL-based p…
cs.LG2026
Reducing the Safety Tax in LLM Safety Alignment with On-Policy Self-Distillation
Yu Fu, Longxuan Yu, Haz Sameen Shahgir +4
Safety alignment often improves robustness to harmful queries at the cost of reasoning ability, a tradeoff known as the safety tax. A common cause is distributional mismatch: super…
cs.LG2025
MACE: A Hybrid LLM Serving System with Colocated SLO-aware Continuous Retraining Alignment
Yufei Li, Yu Fu, Yue Dong +1
Large language models (LLMs) deployed on edge servers are increasingly used in latency-sensitive applications such as personalized assistants, recommendation, and content moderatio…