Local Success Does Not Compose: Benchmarking Large Language Models for Compositional Formal Verification
ICLR, 2026
LLM evaluation, domain reasoning, and multi-agent systems
Ph.D. Student, Nanyang Technological University
Email: xin019@e.ntu.edu.sg
I am a Ph.D. student at Nanyang Technological University (NTU), advised by Prof. Chau Yuen. My research develops benchmarks, training methods, and agent systems for verifiable and domain-specific reasoning in Large Language Models (LLMs).
Previously at MSRA, MEGVII, and Gausium Robotics, I led perception projects from prototype to deployment across SLAM, VIO, and radio/vision stacks.
I received my M.E. from Peking University and my B.E. from Northeastern University, China.
Open to Collaboration: If you are interested in academic collaboration on LLMs, agents, or engineering applications, please email me at xin019@e.ntu.edu.sg.
(* indicates equal contribution. For a full list, please see my Google Scholar ⤻.)
Local Success Does Not Compose: Benchmarking Large Language Models for Compositional Formal Verification
ICLR, 2026
Re:Form: Reducing Human Priors in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny
TMLR, 2026
WirelessMathLM: Teaching Mathematical Reasoning for LLMs in Wireless Communications with Reinforcement Learning
arXiv, 2025
Beyond Correctness: Evaluating Subjective Writing Preferences Across Cultures
arXiv, 2025
LACP: LLM Agent Communication Protocol Requires Urgent Standardization
AI4NextG @ NeurIPS, 2025
WirelessMathBench: A Mathematical Modeling Benchmark for LLMs in Wireless Communications
Findings of ACL, 2025
TransPathNet: A Two-Stage Framework for Indoor Radio Map Prediction
ICASSP, 2025
Co-Planar Parametrization for Stereo-SLAM and Visual-Inertial Odometry
IEEE Robotics and Automation Letters (RA-L), 2020
Leveraging Planar Regularities for Point-Line Visual-Inertial Odometry
IROS, 2020