NeurIPS 2026 D&B
AndroidReality: How Far Are Mobile Agents from the Real World?
Conference on Neural Information Processing Systems, Datasets & Benchmarks Track
Publications
* Equal contribution. You can also find my articles on Google Scholar.
2026
AACL 2026
Diverse Reasoning Paths Matter: Symbolic Equivalence Augmentation for Enhancing RL Exploration
Conference of the Asia-Pacific Chapter of the ACL (Main)
AACL 2026
AACL 2026
Detect Before You Disambiguate: Perturbation-Based Input Ambiguity Detection in LLMs
Conference of the Asia-Pacific Chapter of the ACL (Main)
IROS 2026
PlantShade: Predicting Plant Shadows for Lighting-Aware Robotic Agricultural Operation
IEEE/RSJ International Conference on Intelligent Robots and Systems
EMNLP 2026
LangMARL: Natural Language Multi-Agent Reinforcement Learning
Conference on Empirical Methods in Natural Language Processing (Main)
EMNLP 2026 Findings
MASkills: Continual Skills Optimization for Multi-Agent LLM Systems
Findings of the Conference on Empirical Methods in Natural Language Processing
ICML 2026
Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution
International Conference on Machine Learning
KDD 2026 Blue Sky
The Sim-to-Real Gap of Foundation Model Agents: A Unified MDP Perspective
ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Blue Sky Track
ICML 2026 Position
Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering
International Conference on Machine Learning, Position Paper Track
ACL 2026 Findings
Uncertainty Quantification of Large Language Models through Multi-Dimensional Responses
Findings of the Annual Meeting of the Association for Computational Linguistics
PAKDD 2026
Oral
SELAUR: Self Evolving LLM Agent via Uncertainty-aware Rewards
Pacific-Asia Conference on Knowledge Discovery and Data Mining
EACL 2026 Findings
Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignment
Findings of the Conference of the European Chapter of the ACL
2025
KDD 2025
Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey
ACM SIGKDD Conference on Knowledge Discovery and Data Mining
KDD 2025
Is Your Explanation Reliable: Confidence-Aware Explanation on Graph Neural Networks
ACM SIGKDD Conference on Knowledge Discovery and Data Mining
COLM 2025
Understanding the Uncertainty of LLM Explanations: A Perspective Based on Reasoning Topology
Conference on Language Modeling
ICCPS 2025
ICCPS 2025
🏆 Best Artifact Award
Uncertainty Quantification for Physics-Informed Traffic Graph Networks
ACM/IEEE International Conference on Cyber-Physical Systems
ICCPS 2025
ICCPS 2025
Reproducible and Low-cost Sim-to-Real Environment for Traffic Signal Control
ACM/IEEE International Conference on Cyber-Physical Systems
arXiv 2025
MCQA-Eval: Efficient Confidence Evaluation in NLG with Gold-Standard Correctness Labels
arXiv preprint arXiv:2502.14268
2024
M.Sc. Thesis
M.Sc. Thesis
The Effectiveness of GNNs for Node Classification: The Significance of Side Information
Master's thesis, University of British Columbia