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cs.LG2026
Denser Better: Limits of On-Policy Self-Distillation for Continual Post-Training
Meng Wang, Haohan Zhao, Wenzhuo Liu +7
Continual post-training enables foundation models to acquire new knowledge while preserving existing capabilities. Recent work suggests that on-policy learning can mitigate forgett…
cs.AI2026
Constraint-Aware Corrective Memory for Language-Based Drug Discovery Agents
Maochen Sun, Youzhi Zhang, Gaofeng Meng
Large language models are making autonomous drug discovery agents increasingly feasible, but reliable success in this setting is not determined by any single action or molecule. It…
cs.CL2026
Intent Mismatch Causes LLMs to Get Lost in Multi-Turn Conversation
Geng Liu, Fei Zhu, Rong Feng +3
Multi-turn conversation has emerged as a predominant interaction paradigm for Large Language Models (LLMs). Users often employ follow-up questions to refine their intent, expecting…