MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation (2025 · 75 citations)
Evaluating LLMs across languages has two gaps. Demanding reasoning benchmarks such as MMLU-Pro exist mainly in English. Multilingual suites like Global-MMLU combine translation sources of uneven quality and pose easier questions. The authors address both with MMLU-ProX, which carries the ten-option, reasoning-heavy…
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models (2025 · 11 citations)
Vision-language models (VLMs) can state in plain language how sure they are of an answer. This study asks whether that stated confidence actually tracks how often they are correct. The authors evaluate verbalized calibration across three model families: instruction-tuned, text-reasoning, and visual-reasoning…
Thinking Out Loud: Do Reasoning Models Know When They're Right? (2025 · 9 citations)
The paper asks whether large reasoning models (LRMs), which display apparent self-reflection in long chains of thought, also report their own confidence more accurately.
The Confidence Dichotomy: Analyzing and Mitigating Miscalibration in Tool-Use Agents (2026 · 2 citations)
The paper asks whether tool use always worsens how well LLM agents' stated confidence matches their real accuracy, or whether the effect depends on the tool.
Code-Switching Information Retrieval: Benchmarks, Analysis, and the Limits of Current Retrievers (2026 · 1 citation)
Search engines and RAG pipelines are mostly built and tested on single-language queries, yet many bilingual users mix languages when they search.
How to Improve LLMs' Performance on Specific Languages: A Perspective on LLM-Derived Language Similarity (2026)
LLMs perform unevenly across languages. When target-language training data is scarce, practitioners usually pick a related "donor" language for fine-tuning based on linguistic typology. This work questions whether typology matches how models themselves perceive language similarity. The authors propose three…
Taming Object Hallucinations with Verified Atomic Confidence Estimation (2026)
Multimodal LLMs often describe objects, properties or relations that are not in the image. They are also easily swayed by small changes in how a question is worded. The authors propose TACO, a training-free pipeline that has the model check its own answers, with no external detectors or captioners. TACO works in four…

All works

11 works of theirs in our library, the most cited first; 7 with a page here, the others link their original until we summarise them.

MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model EvaluationConference on Empirical Methods in Natural Language Processing (EMNLP)Weihao Xuan, Rui Yang, Heli Qi, et al.2025 · 75 citations
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.2025 · 11 citations
Thinking Out Loud: Do Reasoning Models Know When They're Right?Conference on Empirical Methods in Natural Language Processing (EMNLP)Qingcheng Zeng, Weihao Xuan, Leyang Cui, et al.2025 · 9 citations
Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards ↗arXiv (Cornell University) · no summary yetFang Wu et al.2025 · 3 citations
The Confidence Dichotomy: Analyzing and Mitigating Miscalibration in Tool-Use AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.2026 · 2 citations
Code-Switching Information Retrieval: Benchmarks, Analysis, and the Limits of Current RetrieversFindings of the Association for Computational LinguisticsQingcheng Zeng, Yuheng Lu, Zeqi Zhou, et al.2026 · 1 citation
How to Improve LLMs' Performance on Specific Languages: A Perspective on LLM-Derived Language SimilarityAnnual Meeting of the Association for Computational Linguistics (ACL)Xinhe Shi, Qingcheng Zeng, Weihao Xuan, et al.2026
Taming Object Hallucinations with Verified Atomic Confidence EstimationConference of the European Chapter of the Association for Computational Linguistics (EACL)Jiarui Liu, Weihao Xuan, Zhijing Jin, et al.2026
Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations ↗arXiv (Cornell University) · no summary yetJunjue Wang et al.2026
Deciphering Fingerprints of 3D Molecular Surfaces for Accurate Epitope Prediction ↗arXiv (Cornell University) · no summary yetFang Wu et al.2026
Proteo-R1: Reasoning Foundation Models for De Novo Protein Design ↗arXiv (Cornell University) · no summary yetFang Wu et al.2026

Co-authors here

12 of 17 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

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Papers of our library cite their works 83 times (of the 149,439 papers whose bibliographies we read); 25 citing papers with a page here →.

Updated 1 November 2026

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Weihao Xuan

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