Author

Jiaqi Li

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Jul 2026

BLADE: Boundary-Expanded and Layer-Adaptive Dynamic Exit for Efficient LLM Reasoning

A lightweight framework that dynamically terminates reasoning by estimating whether the generated prefix is sufficient for correct answering and derives robust training labels through repeated answer completions is presented, demonstrating an effective approach to more efficient LLM reasoning.

Keshu Fu, Ke-Qin Peng, Jun Bai et al. · arXiv.org · 0 citations

#machine learning Preprint Aug 2026

ContinualSkillBench: Can LLM Agents Truly Evolve Their Capabilities?

ContinualSkillBench is introduced, a dynamic evaluation framework for in-context continual skill learning that shows that current in-context skill evolution mechanisms can support continual adaptation, but still struggle to consistently consolidate experience into robust and transferable skills.

Tianyi Guan, Yiding Wang, Haotong Yang et al. · 2 citations