Prateek Mittal
Prateek Mittal has 5 papers in our library, in 2023–2026, most of them on Bias, fairness & safety, Language models & pretraining, Vision & language; often with Peter Henderson, Xiangyu Qi, Tinghao Xie.
OpenAlex · ORCID · Wikidata · h-index 43 · 225 works · 14,133 citations OpenAlex, 2026-10-14
📄 5 works in our library · 🔗 Cited 700 times in our library · 10 more in our library without a page yet · ⭐ Paper Stars ranking: #3256
Affiliations
Fields, topics and concepts
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Computer Science · 5 worksArtificial Intelligence · 5 worksSafety Research · 3 worksSocial Sciences · 3 worksArts and Humanities · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 2 works
🧭 Topics 3Research subjects and languages the work is about.Bias, fairness & safety · 5 worksLanguage models & pretraining · 2 worksVision & language · 1 work
Works by year
2020s
Papers
- 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. - Visual Adversarial Examples Jailbreak Aligned Large Language Models (2023 · 240 citations)
Adding image inputs to large language models creates new security risks. The authors argue that images are continuous and high-dimensional, which makes them much easier to manipulate adversarially than discrete text. Because these models can do so many things, a successful attack can do more than cause a… - Safety Alignment Should Be Made More Than Just a Few Tokens Deep (2024 · 97 citations)
The paper asks why safety-aligned LLMs are so easy to break, whether through adversarial suffixes, prefilling, tweaked decoding parameters, or a few steps of fine-tuning. - 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… - 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
- Analyzing Federated Learning through an Adversarial Lens ↗International Conference on Machine Learning · no summary yetArjun Nitin Bhagoji et al.2019 · 388 citations
- 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
- Visual Adversarial Examples Jailbreak Aligned Large Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceXiangyu Qi, Kaixuan Huang, Ashwinee Panda, et al.2023 · 240 citations
- Evolution of social-attribute networks ↗Internet Measurement Conference · no summary yetNeil Zhenqiang Gong et al.2012 · 170 citations
- Safety Alignment Should Be Made More Than Just a Few Tokens DeeparXiv:2406.05946Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.2024 · 97 citations
- Preserving Link Privacy in Social Network Based Systems ↗arXiv (Cornell University) · no summary yetPrateek Mittal, Charalampos Papamanthou, Dawn Xiaodong Song2012 · 91 citations
- Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank ModificationsarXiv:2402.05162Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.2024 · 66 citations
- Certifiably Robust RAG against Retrieval Corruption ↗IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) · no summary yetChong Xiang et al.2024 · 39 citations
- Evolution of Social-Attribute Networks: Measurements, Modeling, and Implications using Google+ ↗arXiv (Cornell University) · no summary yetNeil Zhenqiang Gong et al.2012 · 38 citations
- New Directions in Social Authentication ↗no summary yetSakshi Jain et al.2015 · 7 citations
- AI Risk Management Should Incorporate Both Safety and Security ↗arXiv (Cornell University) · no summary yetXiangyu Qi et al.2024 · 3 citations
- ASPIRE: iterative specification synthesis for security ↗Workshop on Hot Topics in Operating Systems · no summary yetKevin Zhijie Chen et al.2015 · 3 citations
- The Model Hears You: Audio Language Model Deployments Should Consider the Principle of Least Privilege ↗Proceedings of the AAAI/ACM Conference on AI Ethics and Society · no summary yetLuxi He et al.2025 · 1 citation
- VFIX: Facilitating Software Maintenance of Smart Contracts via Automatically Fixing Vulnerabilities ↗IEEE International Conference on Software Maintenance and Evolution (ICSME) · no summary yetPengcheng Fang et al.2024 · 1 citation
- 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
- Peter Henderson ×4
- Xiangyu Qi ×4
- Tinghao Xie ×3
- Ashwinee Panda ×2
- Kaixuan Huang ×2
- Mengdi Wang ×2
- Boyi Wei
- Li Chen
- Mengzhou Xia
- Pin-Yu Chen
- Ruoxi Jia
- Xiao Ma
Venues
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
- Proceedings of the AAAI Conference on Artificial Intelligence: Proceedings of the AAAI Conference on Artificial Intelligence 2023
- IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
- IEEE International Conference on Software Maintenance and Evolution (ICSME)
- International Conference on Machine Learning
- Internet Measurement Conference
- Proceedings of the AAAI/ACM Conference on AI Ethics and Society
- Workshop on Hot Topics in Operating Systems
Cited by
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