Publications

Anshuman Suri, Xiao Zhang, David Evans (2024). Do Parameters Reveal More than Loss for Membership Inference?. In HiLD, ICML 2024.

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Michael Duan, Anshuman Suri, Niloofar Mireshghallah, Sewon Min, Weijia Shi, Luke Zettlemoyer, Yulia Tsvetkov, Yejin Choi, David Evans, Hannaneh Hajishirzi (2024). Do Membership Inference Attacks Work on Large Language Models?. In Conference on Language Modeling (COLM), 2024.

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Fnu Suya, Anshuman Suri, Tingwei Zhang, Jingtao Hong, Yuan Tian, David Evans (2023). SoK: Pitfalls in Evaluating Black-Box Attacks. In SaTML 2024.

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Valentin Hartmann, Anshuman Suri, Vincent Bindschaedler, David Evans, Shruti Tople, Robert West (2023). SoK: Memorization in General-Purpose Large Language Models. In arXiv.

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Yulong Tian, Fnu Suya, Anshuman Suri, Fengyuan Xu, David Evans (2023). Manipulating Transfer Learning for Property Inference. In CVPR 2023.

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Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin (2022). SoK: Let The Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning. In S&P, 2023.

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Anshuman Suri, Yifu Lu, Yanjin Chen, David Evans (2022). Dissecting Distribution Inference. In SaTML 2023.

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Anshuman Suri, David Evans (2022). Formalizing and Estimating Distribution Inference Risks. In PETS, 2022.

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Anshuman Suri, Pallika Kanani, Virendra J. Marathe, Daniel W. Peterson (2022). Subject Membership Inference Attacks in Federated Learning. In arXiv.

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Anshuman Suri, David Evans (2021). Formalizing Distribution Inference Risks. In TPDP, ICML 2021.

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Fnu Suya, Saeed Mahloujifar, Anshuman Suri, David Evans, Yuan Tian (2021). Model-Targeted Poisoning Attacks with Provable Convergence. In ICML, 2021.

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Parag Agrawal, Tulasi Menon, Aya Kamel, Michel Naim, Chaikesh Chouragade, Gurvinder Singh, Rohan Kulkarni, Anshuman Suri, Sahithi Katakam, Vineet Pratik, Prakul Bansal, Simerpreet Kaur, Neha Rajput, Anand Duggal, Achraf Chalabi, Prashant Choudhari, Somi Reddy Satti, Niranjan Nayak (2020). QnAMaker : Data to Bot in 2 Minutes. In WWW 2020 (Demo Track).

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Anshuman Suri, David Evans (2020). One Neuron to Fool Them All. In arXiv.

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Anshuman Suri, Mayank Vatsa, Richa Singh (2020). A2-LINK: Recognizing Disguised Faces via Active Learning and Adversarial Noise Based Inter-Domain Knowledge. In T-BIOM.

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Deepak Vijaykeerthy, Anshuman Suri, Sameep Mehta, Ponnurangam Kumaraguru (2019). Hardening Deep Neural Networks via Adversarial Model Cascades. In IJCNN, 2019.

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Vighnesh Leonardo Shiv, Chris Quirk, Anshuman Suri, Xiang Gao, Khuram Shahid, Nithya Govindarajan, Yizhe Zhang, Jianfeng Gao, Michel Galley, Chris Brockett, Tulasi Menon, Bill Dolan (2019). Microsoft Icecaps: An Open-Source Toolkit for Conversation Modeling. In ACL, 2019 (Demo).

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Anshuman Suri, Mayank Vatsa, Richa Singh (2019). A-LINK: Recognizing Disguised Faces via Active Learning based Inter-Domain Knowledge. In BTAS 2019.

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Parag Agrawal, Anshuman Suri, Equal contribution (2019). NELEC at SemEval-2019 Task 3: Think Twice Before Going Deep. In SemEval, NAACL 2019.

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Parag Agrawal, Anshuman Suri, Tulasi Menon (2018). A Trustworthy, Responsible and Interpretable System to Handle Chit-Chat in Conversational Bots. In DEEPDIAL Workshop, AAAI 2018.

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Prateek Dewan, Anshuman Suri, Varun Bharadhwaj, Aditi Mithal, Ponnurangam Kumaraguru (2017). Towards Understanding Crisis Events On Online Social Networks Through Pictures. In ASONAM 2017.

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