James Flemings

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Los Angeles, CA

Hello! I am a fourth-year CS PhD student at the University of Southern California advised by Murali Annavaram in the SCIP (Super Computing In Pocket) lab. I’m graciously funded by the NSF Graduate Research Fellowship. My research addresses privacy concerns in Large Language Models (LLMs). I focus on developing autonomous LLM-based agents capable of making personalized privacy decisions for users, leveraging sociotechnical frameworks to align agent behavior with user preferences and privacy norms.

Previously, I interned at Google in the Federated Learning and Analytics team during Summer 2025, investigating personalized privacy in agents. I also interned at TikTok during Summer 2024 in the Privacy Innovation Lab, exploring hallucination and privacy in langauge models. Before graduate school, I received my BS in computer science and mathematics at the University of Alaska Anchorage in 2022. While there, I pursued research in a wide range of areas, including monochromatic colorings, charged coupled devices, federated learning, and out of distribution data performance in language models.

News

Feb 01, 2026 Our paper “Personalizing Agent Privacy Decision via Logical Entailment” has been accepted to PETS 2026!
Jan 26, 2026 Our paper “Hubble: a Model Suite to Advance the Study of LLM Memorization” has been accepted to ICLR 2026!
May 15, 2025 Our paper “Estimating Privacy Leakage of Augmented Contextual Knowledge in Language Models” has been accepted to ACL 2025, Main!
Mar 11, 2025 I will be interning at Google as a student researcher this summer, working in the Federated Learning and Analytics team!
Jul 22, 2024 Gave two tech talks @ LinkedIn and TikTok on our work “Differentially Private Prediction of Large Language Models.”

Selected Publications

  1. PETS
    Personalizing Agent Privacy Decisions via Logical Entailment
    James Flemings, Ren Yi , Octavian Suciu , Kassem Fawaz , Murali Annavaram , and Marco Gruteser
    Proceedings of Privacy Enhancing Technologies, 2026
  2. ICLR
    Hubble: a Model Suite to Advance the Study of LLM Memorization
    Johnny Tian-Zheng Wei , Ameya Godbole , Mohammad Aflah Khan , Ryan Wang , Xiaoyuan Zhu , James Flemings, Nitya Kashyap , Krishna P Gummadi , Willie Neiswanger , and Robin Jia
    Proceedings of International Conference on Learning Representations, 2026
  3. ACL
    Estimating Privacy Leakage of Augmented Contextual Knowledge in Language Models
    James Flemings, Bo Jiang , Wanrong Zhang , Zafar Takhirov , and Murali Annavaram
    In Proceedings of ACL, 2025
  4. ACL
    Differentially Private Knowledge Distillation via Synthetic Text Generation
    James Flemings, and Murali Annavaram
    In Findings of ACL, 2024
  5. NAACL
    Differentially Private Next-Token Prediction of Large Language Models
    James Flemings, Meisam Razaviyayn , and Murali Annavaram
    In Proceedings of NAACL, 2024