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cs.AI2026

CacheSpec: Finding the Sweet Spot for Small Models in Large Language Models

Jingquan Chen, Jie Feng, Jinghua Piao +2

Large language models (LLMs) are increasingly used for program-aided reasoning, agentic decision making, and structured task execution, but these settings often incur substantial i…

cs.AI2026

From Scoring to Acting: Outcome-Verified Comparative Self-Distillation for LLM Agents

Xu Xia, Jinghua Piao, Min Yang +3

Recent work on LLM agents is shifting from external capability elicitation to capability internalization, enabling agents to retain useful skills without retrieval at inference tim…

cs.AI2026

InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain

Tiancheng Han, Yong Li, Wuzhou Yu +2

Long-context tasks require LLMs to identify and preserve answer-relevant information from large contexts. Chunk-wise memory agents address this issue by sequentially reading docume…

cs.AI2026

SkillMaster: Toward Autonomous Skill Mastery in LLM Agents

Min Yang, Jinghua Piao, Xu Xia +4

Skills provide an effective mechanism for improving LLM agents on complex tasks, yet in existing agent frameworks, their creation, refinement, and selection are typically governed…

cs.AI2026

Towards Scalable Lightweight GUI Agents via Multi-role Orchestration

Ziwei Wang, Junjie Zheng, Leyang Yang +7

Autonomous Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) enable digital automation on end-user devices. While scaling both parameters an…

cs.AI2025

AutoQual: An LLM Agent for Automated Discovery of Interpretable Features for Review Quality Assessment

Xiaochong Lan, Jie Feng, Yinxing Liu +2

Ranking online reviews by their intrinsic quality is a critical task for e-commerce platforms and information services, impacting user experience and business outcomes. However, qu…