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Guojun Yin

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Preprint Oct 2026

From Trajectories to Differentiated Skills: Cognitive Differentiation for Self-Improving Agents

Large language model (LLM) agents tackle complex tasks through reasoning and interaction with external environments. Agent skills provide persistent, transferable capabilities that guide task planning, inform contextual decisions, support tool use, and enable executable procedures. Yet existing skill-evolution methods...

Ye-Wei Zhao, De-Rong Xu, Wei Chen et al. · 0 citations
#artificial intelligence Preprint Oct 2026

On-Policy Self-Distillation with Teacher Evolution

This paper proposes Teacher-Evolution Self-Distillation (TESD), which enables the self-teacher to generate rollouts and receive environmental feedback based on task correctness and context independence and performs teacher-oriented optimization to continuously enhance the model's self-teaching capability during distill...

Shu-Fan Shen, Zhong-Ni Hou, Chao Bi et al. · 0 citations
#artificial intelligence Preprint Oct 2026

CALM: Conflict-Aware Lifecycle Memory Governance for Long-Horizon Language Agents

A memory can be outdated for present-day reasoning yet indispensable for reconstructing the past. Relevance-based retrieval overlooks this tension: semantic relevance, evidence-grounded validity, and query-specific eligibility are distinct. We propose CALM, a conflict-aware lifecycle memory governance framework that de...

Chang Li, Xian-Hao Ou, Xin Ma et al. · 0 citations
Preprint Oct 2026

LOOP: Recovery-Aligned Iterative Layer Pruning via On-Policy Distillation

Layer-level pruning is attractive for large language model (LLM) deployment as it reduces the model size while preserving a dense architecture that can be efficiently executed on standard hardware. Current methods typically follow a one-shot paradigm, which first removes selected layers to reach a target model size and...

Liang-Sheng Xu, Shu-Fan Shen, Zhong-Ni Hou et al. · 0 citations
Preprint Sep 2026

Tool Retrievers Are Underestimated: Annotation Expansion Reveals True Capability

The proposed ToolEX (Tool Equivalent eXpansion), a framework that automatically discovers and annotates the tool combinations functionally equivalent to the labeled ones, and confirms that the one-to-one problem extends beyond tool retrieval.

Yan-Yu Zhu, Chen-Heng Zhang, Shao-Shen Chen et al. · 0 citations
Preprint Aug 2026

Toward Plasticity-Preserving KL Regularization for Capability Retention in LLM Reinforcement Learning

Experiments in controlled multi-solution environments and continual post-training settings across multiple model scales demonstrate that CoKL achieves a more favorable balance between target-task improvement and prior-capability retention than existing regularization methods.

Li Wang, Xiao-Dong Lu, Xiao-Han Wang et al. · 0 citations
#machine learning Preprint Sep 2026

One Step, One Lead: Mitigating Higher-Order Interference in Multi-Domain Reinforcement Learning via Cross-Step Control

OSOL, which designates a focus domain at each iteration, uses the preceding checkpoint footprint to rank token-level rebound risk, and applies a drift-ranked, adaptively scaled correction within the standard GRPO update, is proposed, which suppresses the targeted cross-step output backtracking component.

Zi-Han Lin, Xiao-Han Wang, Jie Cao et al. · 1 citation
#artificial intelligence Conference Jan 2026

Beyond Dialogue Time: Temporal Semantic Memory for Personalized LLM Agents

Temporal Semantic Memory is proposed, a memory framework that models semantic time for point-wise memory and supports the construction and utilization of durative memory and incorporates the query's temporal intent on the semantic timeline.

Miao Su, Yu-Can Guo, Zhong-Ni Hou et al. · 12 citations
#artificial intelligence Preprint Aug 2026

ATLAS: Dual-Horizon Diagnostic Evaluation for Industrial Tool-Use Agents

This work proposes ATLAS, a dual-horizon diagnostic evaluation framework for industrial tool-use agents that instantiates LLM judge interfaces as executable signals with explicit evidence scopes and decision boundaries, and evaluates ATLAS on Meituan Xiaotuan production traffic.

Wei Chen, Pei-Lun Zhou, Zhao-Yu Hu et al. · 0 citations
Preprint Aug 2026

HiDiffTIR: Hierarchical Difficulty-Aware Policy Optimization for Multi-Turn Tool-Integrated Reasoning

HiDiffTIR is proposed, a Hierarchical Difficulty-aware policy optimization framework for multi-turn TIR that consistently improves multi-turn TIR performance and tool invocation accuracy over strong RL baselines, highlighting the necessity of difficulty-aware credit assignment for effective policy optimization in tool-...

Yu-Can Guo, Xiao-Han Wang, Miao Su et al. · 0 citations

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