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Zesheng Shi

Zesheng Shi has 2 papers in our library, in 2025–2026, most of them on Bias, fairness & safety, Language models & pretraining, Reasoning; often with Jing Li, Min Zhang, Daojing He.

2 papers in our library · 2025–2026

OpenAlex · h-index 3 · 13 works · 16 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 19 times in our library · ⭐ Paper Stars ranking: #8898

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

🎓Nankai UniversityTianjin · China2023–2025 · 4 paperscurrent🎓Harbin Institute of TechnologyHarbin · China2025 · 1 papercurrent🎓University of Science and Technology of ChinaHefei · China1995–2002 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 3Research subjects and languages the work is about.Bias, fairness & safety · 2 worksLanguage models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Safety Alignment via Constrained Knowledge Unlearning (2025 · 13 citations)
    Aligned large language models still produce harmful content under jailbreak attacks. The authors argue this happens because standard defenses, such as continued safety training, teach models to refuse without removing the dangerous knowledge itself, and they can also erode general skills. They propose Constrained…
  2. Backdoors in RLVR: Jailbreak Backdoors in LLMs From Verifiable Reward (2026 · 10 citations)
    This paper presents what the authors describe as the first backdoor attack on Reinforcement Learning with Verifiable Rewards (RLVR), the training approach used to strengthen LLM reasoning in math and code.

 Co-authors here

8 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 19 times (of the 149,439 papers whose bibliographies we read); 11 citing papers with a page here →.

Updated

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