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Collaborations and top research areas from the last five years

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  • AIDB: a Sparsely Materialized Database for Queries using Machine Learning

    Jin, T., Mittal, A., Mo, C., Fang, J., Zhang, C., Dai, T. & Kang, D., Jun 9 2024, Proceedings of the 8th Workshop on Data Management for End-to-End Machine Learning, DEEM 2024 - In conjunction with the 2024 ACM SIGMOD/PODS Conference. Association for Computing Machinery, p. 23-28 6 p. (Proceedings of the 8th Workshop on Data Management for End-to-End Machine Learning, DEEM 2024 - In conjunction with the 2024 ACM SIGMOD/PODS Conference).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks

    Kang, D., Li, X., Stoica, I., Guestrin, C., Zaharia, M. & Hashimoto, T., 2024, Proceedings - 45th IEEE Symposium on Security and Privacy Workshops, SPW 2024. Institute of Electrical and Electronics Engineers Inc., p. 132-143 12 p. (Proceedings - 45th IEEE Symposium on Security and Privacy Workshops, SPW 2024).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
  • Removing RLHF Protections in GPT-4 via Fine-Tuning

    Zhan, Q., Fang, R., Bindu, R., Gupta, A., Hashimoto, T. & Kang, D., 2024, p. 681-687. 7 p.

    Research output: Contribution to conferencePaperpeer-review

  • tailwiz: Empowering Domain Experts with Easy-to-Use, Task-Specific Natural Language Processing Models

    Dai, T., Peters, A., Gelbach, J. B., Engstrom, D. F. & Kang, D., Jun 9 2024, Proceedings of the 8th Workshop on Data Management for End-to-End Machine Learning, DEEM 2024 - In conjunction with the 2024 ACM SIGMOD/PODS Conference. Association for Computing Machinery, p. 12-22 11 p. (Proceedings of the 8th Workshop on Data Management for End-to-End Machine Learning, DEEM 2024 - In conjunction with the 2024 ACM SIGMOD/PODS Conference).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • ZKML: An Optimizing System for ML Inference in Zero-Knowledge Proofs

    Chen, B. J., Waiwitlikhit, S., Stoica, I. & Kang, D., Apr 22 2024, EuroSys 2024 - Proceedings of the 2024 European Conference on Computer Systems. Association for Computing Machinery, p. 560-574 15 p. (EuroSys 2024 - Proceedings of the 2024 European Conference on Computer Systems).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution