collaborators

5 papers

cs.SE2026

Enhancing Software Engineering Through Closed-Loop Memory Optimization

Xuehang Guo, Zora Zhiruo Wang, Qingyun Wang +2

Large language models (LLMs) have enabled powerful software engineering (SE) agents capable of navigating complex codebases and resolving real-world issues. However, these agents r…

cs.AI2026

SciDER: Scientific Data-centric End-to-end Researcher

Ke Lin, Owais Aijaz, Yilin Lu +3

While large language models accelerate scientific discovery, existing agents face severe limitations in adaptability, domain generalization, and multimodal scalability, often strug…

cs.CL2026

When to Think, When to Speak: Learning Disclosure Policies for LLM Reasoning

Jiaqi Wei, Xuehang Guo, Pengfei Yu +5

In single-stream autoregressive interfaces, the same tokens both update the model state and constitute an irreversible public commitment. This coupling creates a silence tax: addit…

cs.DL2026

CiteGuard: Faithful Citation Attribution for LLMs via Retrieval-Augmented Validation

Yee Man Choi, Xuehang Guo, Yi R. Fung +1

Large Language Models (LLMs) have emerged as powerful assistants for scientific writing. However, concerns remain about the quality and reliability of the generated text, including…

cs.CL2026

Anagent For Enhancing Scientific Table & Figure Analysis

Xuehang Guo, Zhiyong Lu, Tom Hope +1

In scientific research, analysis requires accurately interpreting complex multimodal knowledge, integrating evidence from different sources, and drawing inferences grounded in doma…