--- title: "Yangsibo Huang — author profile and papers in our library" description: "Yangsibo Huang: 2 papers on Elamur Research (2023–2025), h-index 10 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/yangsibo-huang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yangsibo-huang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yangsibo Huang # Yangsibo Huang Yangsibo Huang has 2 papers in our library, in 2023–2025, 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/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/); often with [Bill Yuchen Lin](https://md.research.elamur.ai/free/en/authors/bill-yuchen-lin/), [Bo Li](https://md.research.elamur.ai/free/en/authors/bo-li/), [Chiyuan Zhang](https://md.research.elamur.ai/free/en/authors/chiyuan-zhang/). 2 papers in our library · 2023–2025 [OpenAlex](https://openalex.org/A5082426637) · [ORCID](https://orcid.org/0000-0002-0640-4845) · [Wikidata](https://www.wikidata.org/wiki/Q141203651) · [**h-index 10**](https://openalex.org/authors/A5082426637) · [50 works](https://openalex.org/works?filter=author.id:A5082426637) · [466 citations](https://openalex.org/works?filter=author.id:A5082426637&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yangsibo-huang/#papers) · [🔗 Cited 769 times in our library](https://md.research.elamur.ai/free/en/authors/yangsibo-huang/cited-by/) · [14 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #5563](https://md.research.elamur.ai/free/en/paper-stars/page/56/#star-5563) 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=Yangsibo+Huang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yangsibo+Huang) · [dblp](https://dblp.org/search?q=Yangsibo+Huang) · [ACL Anthology](https://aclanthology.org/search/?q=Yangsibo+Huang) ## Affiliations [🎓**Princeton University** Princeton · United States 2020–2025 · 24 papers](https://md.research.elamur.ai/free/en/universities/princeton-university/) · [🏢**Google** Mountain View · United States 2024–2025 · 5 papers](https://md.research.elamur.ai/free/en/companies/google/) · [🔬**Institute for Advanced Study** Princeton · United States 2020 · 2 papers](https://ror.org/00f809463) · [🎓**University of California, Los Angeles** Los Angeles · United States 2019–2020 · 2 papers](https://md.research.elamur.ai/free/en/universities/university-of-california-los-angeles/) 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 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/yangsibo-huang/year/2025/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/yangsibo-huang/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation](https://md.research.elamur.ai/free/en/papers/huang-2023-catastrophic-jailbreak-open-source-llms/)** *(2023 · 169 citations)* Safety tuning of open-source LLMs is usually checked under one fixed decoding setup. For example, LLaMA2 was assessed with top-p 0.9, temperature 0.1 and a system prompt. The authors argue that this narrow testing hides serious weaknesses. They introduce the generation exploitation attack, which changes no input… 2. **[On Memorization of Large Language Models in Logical Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2025-memorization-large-language-models-logical/)** *(2025 · 45 citations)* LLMs score well on hard reasoning benchmarks yet still fail on trivial questions. This raises the suspicion that some benchmark success comes from recalling familiar problems. The authors test this idea in a controlled setting. They define LiMem, a memorization score that multiplies a model's accuracy on a puzzle set… ## All works 16 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. **[Detecting Pretraining Data from Large Language Models ↗](https://arxiv.org/abs/2310.16789) arXiv:2310.16789 · no summary yet**Weijia Shi et al.*2023 · 224 citations* 2. [**Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation arXiv:2310.06987**Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-catastrophic-jailbreak-open-source-llms/) 3. **[SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal ↗](https://arxiv.org/abs/2406.14598) arXiv:2406.14598 · no summary yet**Tinghao Xie et al.*2024 · 87 citations* 4. **[Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications ↗](https://arxiv.org/abs/2402.05162) arXiv:2402.05162 · no summary yet**Boyi Wei et al.*2024 · 66 citations* 5. **[MUSE: Machine Unlearning Six-Way Evaluation for Language Models ↗](https://arxiv.org/abs/2407.06460) arXiv (Cornell University) · no summary yet**Weijia Shi et al.*2024 · 65 citations* 6. **[TextHide: Tackling Data Privacy in Language Understanding Tasks ↗](https://aclanthology.org/2020.findings-emnlp.123/) Findings of the Association for Computational Linguistics: EMNLP 2020 · no summary yet**Yangsibo Huang et al.*2020 · 62 citations* 7. **[Recovering Private Text in Federated Learning of Language Models ↗](https://doi.org/10.52202/068431-0590) neural information processing systems · no summary yet**Samyak Gupta et al.*2022 · 52 citations* 8. **[On Memorization of Large Language Models in Logical Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2025-memorization-large-language-models-logical/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.*2025 · 45 citations* 9. **[MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations ↗](https://arxiv.org/abs/2502.06453) arXiv:2502.06453 · no summary yet**Kaixuan Huang et al.*2025 · 42 citations* 10. **[Privacy Implications of Retrieval-Based Language Models ↗](https://aclanthology.org/2023.emnlp-main.921/) Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yet**Yangsibo Huang et al.*2023 · 38 citations* 11. **[Evaluating Copyright Takedown Methods for Language Models ↗](https://doi.org/10.52202/079017-4415) neural information processing systems · no summary yet**Boyi Wei et al.*2024 · 25 citations* 12. **[A Safe Harbor for AI Evaluation and Red Teaming ↗](https://arxiv.org/abs/2403.04893) arXiv (Cornell University) · no summary yet**Shayne Longpre et al.*2024 · 22 citations* 13. **[Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research ↗](https://doi.org/10.52202/085713-2990) neural information processing systems · no summary yet**A. Feder Cooper et al.*2025 · 17 citations* 14. **[Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice ↗](https://doi.org/10.2139/ssrn.5060253) SSRN Electronic Journal · no summary yet**A. Feder Cooper et al.*2025 · 12 citations* 15. **[Fantastic Copyrighted Beasts and How (Not) to Generate Them ↗](https://arxiv.org/abs/2406.14526) arXiv (Cornell University) · no summary yet**Luxi He et al.*2024 · 9 citations* 16. **[AI Risk Management Should Incorporate Both Safety and Security ↗](https://arxiv.org/abs/2405.19524) arXiv (Cornell University) · no summary yet**Xiangyu Qi et al.*2024 · 3 citations* ## Co-authors here 7 co-authors with a page, the most papers together first. - [Bill Yuchen Lin](https://md.research.elamur.ai/free/en/authors/bill-yuchen-lin/) - [Bo Li](https://md.research.elamur.ai/free/en/authors/bo-li/) - [Chiyuan Zhang](https://md.research.elamur.ai/free/en/authors/chiyuan-zhang/) - [Chulin Xie](https://md.research.elamur.ai/free/en/authors/chulin-xie/) - [Danqi Chen](https://md.research.elamur.ai/free/en/authors/danqi-chen/) - [Mengzhou Xia](https://md.research.elamur.ai/free/en/authors/mengzhou-xia/) - [Xinyun Chen](https://md.research.elamur.ai/free/en/authors/xinyun-chen/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - neural information processing systems ×3 - [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/): [IJCNLP 2025](https://md.research.elamur.ai/free/en/venues/ijcnlp/2025/) - Findings of the Association for Computational Linguistics: EMNLP 2020 - Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing - SSRN Electronic Journal ## Cited by Papers of our library cite their works 769 times (of the 149,439 papers whose bibliographies we read); [138 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yangsibo-huang/cited-by/). Updated 30 October 2026