--- title: "Xiaobao Wu — author profile and papers — Elamur Research" description: "Xiaobao Wu, Nanyang Technological University: 6 papers on Elamur Research (2023–2026), h-index 11 — affiliations, topics, co-authors and…" canonical: "https://research.elamur.ai/free/en/authors/xiaobao-wu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/xiaobao-wu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Xiaobao Wu # Xiaobao Wu Xiaobao Wu has 6 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Anh Tuan Luu](https://md.research.elamur.ai/free/en/authors/anh-tuan-luu/), [Liangming Pan](https://md.research.elamur.ai/free/en/authors/liangming-pan/), [William Yang Wang](https://md.research.elamur.ai/free/en/authors/william-yang-wang/). 6 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5011376608) · [ORCID](https://orcid.org/0000-0003-0076-3924) · [**h-index 11**](https://openalex.org/authors/A5011376608) · [63 works](https://openalex.org/works?filter=author.id:A5011376608) · [567 citations](https://openalex.org/works?filter=author.id:A5011376608&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/xiaobao-wu/#papers) · [🔗 Cited 151 times in our library](https://md.research.elamur.ai/free/en/authors/xiaobao-wu/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #5780](https://md.research.elamur.ai/free/en/paper-stars/page/58/#star-5780) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Xiaobao+Wu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Xiaobao+Wu) · [dblp](https://dblp.org/search?q=Xiaobao+Wu) · [ACL Anthology](https://aclanthology.org/search/?q=Xiaobao+Wu) ## Affiliations [🎓**Nanyang Technological University** Singapore · Singapore 2022–2026 · 46 papersEmployment 2025–2026*current*](https://md.research.elamur.ai/free/en/universities/nanyang-technological-university/) · [🎓**Shanghai Jiao Tong University** Shanghai · China 2025–2026 · 4 papersEmployment since 2026 · School of Computer Science*current*](https://md.research.elamur.ai/free/en/universities/shanghai-jiao-tong-university/) · [🎓**University of California, Santa Barbara** Santa Barbara · United States 2024–2025 · 4 papers](https://md.research.elamur.ai/free/en/universities/university-of-california-santa-barbara/) · [🎓**Tsinghua University** Beijing · China 2019–2021 · 4 papers](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 7 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Sociology and Political Science · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 3 Research subjects and languages the work is about.[Reasoning · 3 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Evaluation & benchmarks · 2 works](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/xiaobao-wu/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/xiaobao-wu/year/2025/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/xiaobao-wu/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Fact-Checking Complex Claims with Program-Guided Reasoning](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/)** *(2023 · 146 citations)* Verifying real-world claims often means combining several pieces of evidence through multi-step reasoning. 2. **[RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World Scenarios](https://md.research.elamur.ai/free/en/papers/zhou-2025-rulearena-benchmark-rule-guided-reasoning/)** *(2025 · 21 citations)* Benchmarks of LLM instruction-following mostly check style constraints such as format or length, or they test simple first-order logic. RuleArena instead tests whether models can reason under real regulations written in natural language. The authors gathered 95 rules from three domains: 3. **[AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledge](https://md.research.elamur.ai/free/en/papers/wu-2025-antileakbench-preventing-data-contamination-automatically/)** *(2025 · 12 citations)* Large language models are usually tested on public, static benchmarks, and those test items can leak into the training data of later models, which inflates their scores. 4. **[MUR: Momentum Uncertainty guided Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-mur-momentum-uncertainty-guided-reasoning/)** *(2026 · 8 citations)* Test-time scaling (TTS) makes LLMs reason better but tends to cause overthinking: extra compute goes to every reasoning step, including trivial ones. 5. **[P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-p2p-poison-poison-remedy-reliable/)** *(2026 · 3 citations)* Fine-tuning LLMs on third-party or outsourced data exposes them to data-poisoning backdoors. Most existing defenses filter or sanitize inputs and only work against particular trigger styles or task types. Onion targets character-level triggers, while PDB and PSIM are limited to classification. The authors propose… 6. **[Learning Uncertainty from Sequential Internal Dispersion in Large Language Models](https://md.research.elamur.ai/free/en/papers/srey-2026-learning-uncertainty-sequential-internal-dispersion/)** *(2026)* The paper tackles hallucination detection in LLMs through uncertainty estimation. Existing internal-state methods have two weaknesses. Some, such as Chain-of-Embeddings (CoE), assume a fixed way hidden states should evolve between layers. Others reduce a response to its last or average token and lose sequence-level… ## All works 7 works of theirs in our library, the most cited first; 6 with a page here, the others link their original until we summarise them. 1. **[Fact-Checking Complex Claims with Program-Guided Reasoning](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 146 citations* 2. **[Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling Decoder ↗](https://aclanthology.org/2020.emnlp-main.138/) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yet**Xiaobao Wu et al.*2020 · 84 citations* 3. **[RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World Scenarios](https://md.research.elamur.ai/free/en/papers/zhou-2025-rulearena-benchmark-rule-guided-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiwen Zhou, Wenyue Hua, Liangming Pan, et al.*2025 · 21 citations* 4. **[AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledge](https://md.research.elamur.ai/free/en/papers/wu-2025-antileakbench-preventing-data-contamination-automatically/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaobao Wu, Liangming Pan, Yuxi Xie, et al.*2025 · 12 citations* 5. **[MUR: Momentum Uncertainty guided Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-mur-momentum-uncertainty-guided-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hang Yan, Fangzhi Xu, Rongman Xu, et al.*2026 · 8 citations* 6. **[P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-p2p-poison-poison-remedy-reliable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuai Zhao, Xinyi Wu, Shiqian Zhao, et al.*2026 · 3 citations* 7. **[Learning Uncertainty from Sequential Internal Dispersion in Large Language Models](https://md.research.elamur.ai/free/en/papers/srey-2026-learning-uncertainty-sequential-internal-dispersion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.*2026* ## Co-authors here 12 of 21 co-authors with a page, the most papers together first. - [Anh Tuan Luu](https://md.research.elamur.ai/free/en/authors/anh-tuan-luu/) ×5 - [Liangming Pan](https://md.research.elamur.ai/free/en/authors/liangming-pan/) ×3 - [William Yang Wang](https://md.research.elamur.ai/free/en/authors/william-yang-wang/) ×3 - [Ruiwen Zhou](https://md.research.elamur.ai/free/en/authors/ruiwen-zhou/) ×2 - [Shuai Zhao](https://md.research.elamur.ai/free/en/authors/shuai-zhao/) ×2 - [Fangzhi Xu](https://md.research.elamur.ai/free/en/authors/fangzhi-xu/) - [Haiteng Zhao](https://md.research.elamur.ai/free/en/authors/haiteng-zhao/) - [Hang Yan](https://md.research.elamur.ai/free/en/authors/hang-yan/) - [Haoran Luo](https://md.research.elamur.ai/free/en/authors/haoran-luo/) - [Jian Zhang](https://md.research.elamur.ai/free/en/authors/jian-zhang/) - [Jun Liu](https://md.research.elamur.ai/free/en/authors/jun-liu/) - [Min-Yen Kan](https://md.research.elamur.ai/free/en/authors/min-yen-kan/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×5: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) ×2, [ACL 2023](https://md.research.elamur.ai/free/en/venues/acl/2023/) - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) - Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) ## Cited by Papers of our library cite their works 151 times (of the 149,439 papers whose bibliographies we read); [22 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/xiaobao-wu/cited-by/). Updated 1 November 2026