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Jianing Zhu

Jianing Zhu has 2 papers in our library, in 2023–2026, most of them on Language models & pretraining, Bias, fairness & safety; often with Ahmed Abbasi, Bo Han, Bo Li.

2 papers in our library · 2023–2026

OpenAlex · ORCID · h-index 8 · 29 works · 203 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 126 times in our library · ⭐ Paper Stars ranking: #7244

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

🎓Tianjin UniversityTianjin · China2025–2026 · 2 paperscurrent🎓Xi'an University of Architecture and TechnologyXi'an · China2010–2025 · 7 papers🎓Hong Kong Baptist UniversityHong Kong · China2023–2024 · 5 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 9 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 5The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksBias, fairness & safety · 1 work

 Works by year

2020s

20261 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. DeepInception: Hypnotize Large Language Model to Be Jailbreaker (2023 · 141 citations)
    Safety-aligned LLMs can still be manipulated into producing harmful output. However, many existing jailbreaks depend on white-box optimization or expensive prompt search, and models usually refuse requests that state malicious intent openly. The authors propose DeepInception, a training-free, black-box attack…
  2. Copyright Detective: A Forensic System to Evidence LLMs Flickering Copyright Leakage Risks (2026)
    Copyright Detective is an interactive forensic tool for collecting evidence that LLMs may reproduce copyrighted material.

 Co-authors here

12 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 126 times (of the 149,439 papers whose bibliographies we read); 36 citing papers with a page here →.

Updated

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