collaborators

14 papers

cs.CL2026

LatentSkill: From In-Context Textual Skills to In-Weight Latent Skills for LLM Agents

Aofan Yu, Chenyu Zhou, Tianyi Xu +8

Agent systems increasingly use textual skills to encode reusable task procedures, but injecting these skills into the prompt at every step incurs substantial context overhead and e…

cs.CL2026

Contexting as Recommendation: Evolutionary Collaborative Filtering for Context Engineering

Jiachen Zhu, Zhuoying Ou, Congmin Zheng +9

Large Language Models (LLMs) are highly sensitive to their input contexts, motivating the development of automated context engineering. However, existing methods predominantly trea…

cs.CL2026

Position: Academic Conferences are Potentially Facing Denominator Gaming Caused by Fully Automated Scientific Agents

Rong Shan, Te Gao, Hang Zheng +6

The implicit policy of maintaining relatively stable acceptance rates at top AI conferences, despite exponentially growing submissions, introduces a critical structural vulnerabili…

cs.CL2026

A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models

Congmin Zheng, Jiachen Zhu, Zhuoying Ou +8

Although Large Language Models (LLMs) exhibit advanced reasoning ability, conventional alignment remains largely dominated by outcome reward models (ORMs) that judge only final ans…

cs.SE2026

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering

Chenyu Zhou, Huacan Chai, Wenteng Chen +18

Large language model (LLM) agents are increasingly built less by changing model weights than by reorganizing the runtime around them. Capabilities that earlier systems expected the…

cs.IR2026

PhotoBench: Beyond Visual Matching Towards Personalized Intent-Driven Photo Retrieval

Tianyi Xu, Rong Shan, Junjie Wu +11

Personal photo albums are not merely collections of static images but living, ecological archives defined by temporal continuity, social entanglement, and rich metadata, which make…