3 papers
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.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…
cs.LG2025
Semi-parametric Memory Consolidation: Towards Brain-like Deep Continual Learning
Geng Liu, Fei Zhu, Rong Feng +4
Humans and most animals inherently possess a distinctive capacity to continually acquire novel experiences and accumulate worldly knowledge over time. This ability, termed continua…