🧑‍🔬 Tinghao Xie

🏛️ Affiliations

🎓Princeton UniversityPrinceton · United States2022–2026 · 10 paperscurrent

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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! (2023 · 355 citations)
   Current safety alignment methods, such as instruction tuning and RLHF, constrain how a model behaves at inference time.
2. SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal (2024 · 87 citations)
   SORRY-Bench is a benchmark that measures how reliably aligned LLMs decline unsafe requests. The authors identify three weaknesses in earlier safety evaluations. Their category schemes are coarse and inconsistent, and they concentrate on a few topics such as fraud while barely testing others like self-harm. They…
3. Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications (2024 · 66 citations)
   Aligned LLMs can be jailbroken or lose their safeguards even after harmless fine-tuning. The authors ask whether this fragility can be traced to specific parts of the weights. Using the Llama2-chat family, they attribute behaviour to individual neurons and to low-rank components of weight matrices. They use two…
4. Red-Teaming NSFW Image Classifiers as Text-to-Image Safeguards (2026)
   This paper examines a weakness in NSFW image classifiers that act as output filters for text-to-image (T2I) generators.

All works

6 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!arXiv:2310.03693Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.2023 · 355 citations
2. SORRY-Bench: Systematically Evaluating Large Language Model Safety RefusalarXiv:2406.14598Tinghao Xie, Xiangyu Qi, Yi Zeng, et al.2024 · 87 citations
3. Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank ModificationsarXiv:2402.05162Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.2024 · 66 citations
4. Fantastic Copyrighted Beasts and How (Not) to Generate Them ↗arXiv (Cornell University) · no summary yetLuxi He et al.2024 · 9 citations
5. AI Risk Management Should Incorporate Both Safety and Security ↗arXiv (Cornell University) · no summary yetXiangyu Qi et al.2024 · 3 citations
6. Red-Teaming NSFW Image Classifiers as Text-to-Image SafeguardsFindings of the Association for Computational LinguisticsTinghao Xie, Yueqi Xie, Alireza Zareian, et al.2026

🤝 Co-authors here

12 of 18 co-authors with a page, the most papers together first.

• Prateek Mittal ×3
• Xiangyu Qi ×3
• Boyi Wei ×2
• Kaixuan Huang ×2
• Peter Henderson ×2
• Ruoxi Jia ×2
• Yangsibo Huang ×2
• Yi Zeng ×2
• Bo Li
• Dacheng Li
• Li Chen
• Luxi He

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026

🔗 Cited by

Papers of our library cite their works 470 times (of the 149,439 papers whose bibliographies we read); 105 citing papers with a page here →.

Updated 2 November 2026

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/tinghao-xie/