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Hongning Wang

Hongning Wang has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Bias, fairness & safety; often with Minlie Huang, Pei Ke, Aohan Zeng.

2 papers in our library · 2023–2024

OpenAlex · ORCID · Wikidata · h-index 34 · 202 works · 4,713 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 781 times in our library · 8 more in our library without a page yet · ⭐ Paper Stars ranking: #4757

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

🎓Tsinghua UniversityBeijing · China2008–2026 · 43 paperscurrent🎓University of VirginiaCharlottesville · United States2014–2025 · 106 papersEmployment since 2014 · Associate Professor, Computer Science🎓University of Illinois Urbana-ChampaignUrbana · United States2010–2014 · 18 papers🎓Sichuan UniversityChengdu · China2015–2023 · 7 papers🔬State Key Laboratory of Intelligent Technology and SystemsBeijing2008–2009 · 4 papers🎓Oregon State UniversityCorvallis · United States2022–2024 · 3 papers
🏛️University of Illinois at Urbana-ChampaignUrbana · United States2009–2012Education 2009–2012 · PhD, Computer Science

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 11 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 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20241 paperDefending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization20231 paperCritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation

 Papers

The most cited first (OpenAlex and our library).

  1. Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization (2024 · 112 citations)
    The paper argues that jailbreaking attacks on LLMs succeed because models are tuned for two competing objectives, helpfulness and safety, without being told which one wins when they clash.
  2. CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation (2023 · 68 citations)
    LLM-based evaluators trained on critiques that GPT-4 produces through direct prompting often give vague, generic judgments. The problem is worst when no reference answer is available. This paper presents Eval-Instruct, a pipeline for building more informative training data for critique generation.

All works

10 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Defending Large Language Models Against Jailbreaking Attacks Through Goal PrioritizationZhexin Zhang, Junxiao Yang, Pei Ke, et al.Annual Meeting of the Association for Computational Linguistics (ACL) · 112 citations
  2. Black-Box Prompt Optimization: Aligning Large Language Models without Model Training · original ↗ · no summary yet · Proceedings of the 62nd Annual Meeting of the Association for Computational…Jiale Cheng et al.2024 · 70 citations
  3. CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model GenerationPei Ke, Bosi Wen, Zhuoer Feng, et al.arXiv:2311.18702 · 68 citations
  4. ChatGLM-RLHF: Practices of Aligning Large Language Models with Human Feedback · original ↗ · no summary yet · arXiv:2404.00934Zhenyu Hou et al.2024 · 15 citations
  5. Glyph: Scaling Context Windows via Visual-Text Compression · original ↗ · no summary yet · Proceedings of the 64th Annual Meeting of the Association for Computational…Jiale Cheng et al.2026 · 6 citations
  6. How Should We Enhance the Safety of Large Reasoning Models: An Empirical Study · original ↗ · no summary yet · Proceedings of the 64th Annual Meeting of the Association for Computational…Zhexin Zhang et al.2026 · 5 citations
  7. IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation · original ↗ · no summary yet · Proceedings of the 64th Annual Meeting of the Association for Computational…Bosi Wen et al.2026 · 1 citation
  8. IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation · original ↗ · no summary yet · Proceedings of the 64th Annual Meeting of the Association for Computational…Bosi Wen et al.2026 · 1 citation
  9. LASA: Language-Agnostic Semantic Alignment at the Semantic Bottleneck for LLM Safety · original ↗ · no summary yet · Proceedings of the 64th Annual Meeting of the Association for Computational…Junxiao Yang et al.2026
  10. Data Efficient RLVR via Off-Policy Influence Guidance · original ↗ · no summary yet · Proceedings of the 64th Annual Meeting of the Association for Computational…Erle Zhu et al.2026

 Co-authors here

12 of 13 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 781 times (of the 141,840 papers whose bibliographies we read); 44 citing papers with a page here →.

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