collaborators

17 papers

cs.AI2026

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods

Hai Xia, Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider

Large neighborhood search normally selects a random subset of decision variables for iterative optimization. To efficiently solve various problems, researchers tend to design varia…

cs.CL2026

Calibrating Post-Training Feature Shifts for LLM Data Contamination Detection

Zhen Yang, Mengqi Wang, Gengda Zhao +3

Large language models (LLMs) are trained on massive and largely undisclosed corpora that may contain copyrighted or privacy-sensitive content. Data contamination detection (DCD) th…

cs.CL2026

SkillZip: Contract-Preserving Graph Compression for Scalable Agent Skill Libraries

Xingyu Tan, Xiaoyang Wang, Qing Liu +4

Large Language Models (LLMs) increasingly act as agents whose procedural knowledge is stored in reusable skill packages and loaded at inference time. As skill libraries grow, a cen…

cs.HC2026

LEGOUI: Designing with UI-DSL Bricks to Balance Transparency and Controllability

Yinsi Zhou, Mingyue Yuan, Hongyue Xu +8

Generative user interface design tools enable rapid prototyping but often operate as black boxes with limited transparency and controllability. When outputs diverge from the design…

cs.AI2026

HyperAgent: Planning and Acting over Tool-Schema Hypergraphs for Tool-Use LLM Agents

Zian Zhai, Xingyu Tan, Gaowang Zou +2

Large language model (LLM) agents increasingly rely on external tools to complete complex real-world tasks. However, reliable tool-use planning remains challenging due to the limit…

cs.AI2026

LLM-as-Judge in Education: A Curriculum-Grounded Marking Pipeline

Xiwei Xu, Chen Wang, Jacky Jiang +5

Generative AI and large language models (LLMs) are increasingly applied to question generation and automated assessment. However, deploying LLMs in preparation for high-stakes exam…