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Xudong Han

Xudong Han has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Bias, fairness & safety; often with Haonan Li, Preslav Nakov, Timothy Baldwin.

2 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 14 · 61 works · 472 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 144 times in our library · ⭐ Paper Stars ranking: #4806

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Southern University of Science and TechnologyShenzhen · China2021–2026 · 15 paperscurrent🎓Mohamed bin Zayed University of Artificial IntelligenceAbu Dhabi · United Arab Emirates2024–2026 · 4 paperscurrent🎓The University of MelbourneMelbourne · Australia2019–2023 · 11 papers🎓University of SussexBrighton · United Kingdom2024–2025 · 5 papers🎓Xidian UniversityXi'an · China2020–2025 · 5 papers🎓Hainan UniversityHaikou · China2018–2020 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 8 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksSafety Research · 2 worksSocial Sciences · 2 works

🧭 Topics 2Research subjects and languages the work is about.Bias, fairness & safety · 2 worksLanguage models & pretraining · 2 works

 Works by year

2020s

20241 paperDo-Not-Answer: Evaluating Safeguards in LLMs20231 paperDo-Not-Answer: A Dataset for Evaluating Safeguards in LLMs

 Papers

The most cited first (OpenAlex and our library).

  1. Do-Not-Answer: Evaluating Safeguards in LLMs (2024 · 91 citations)
    Open-source LLMs often ship without the safety layers that commercial systems have. Existing harmful-prompt collections tend to be small, proprietary, or unlabeled. This paper offers a cheap, public way to test whether a model refuses requests it should not fulfil.
  2. Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs (2023 · 76 citations)
    Open-source LLMs often ship without strong safety mechanisms, and earlier harmful-prompt collections were either private, narrow in scope, or lacked labeled model responses.

 Co-authors here

4 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.

 Cited by

Papers of our library cite their works 144 times (of the 141,840 papers whose bibliographies we read); 14 citing papers with a page here →.

Updated

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