Pengfei He
428 S Shaw Ln Rm 3308
East Lansing, MI, 48824
I am a PhD student major in Computer Science and Engineering and minor in Probability and Statistics, at Michigan State University.
My research interests are robustness and safety of machine learning models, optimization and machine learning foundations. Currently, I am interested in evaluate the robustness of self-/un-supervised learning models, including diffusion models, large language models and text-image foundation models. Looking forward to communicating with people from different fields!
Stay Hungry. Stay Foolish!
news
| Sep 20, 2024 | Two papers( Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis; On the generalization of training-based chatgpt detection methods) accepted to * |
|---|---|
| Jun 3, 2024 | I start a new position as Research Intern at Alibaba Group(US) in Bellevue, WA. |
| May 16, 2024 | We have two papers( Exploring Memorization in Fine-tuned Language Models; The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)) accepted to ACL2024! |
| Feb 6, 2024 | We preprint a paper: Data Poisoning for In-context Learning |
| Feb 6, 2024 | We preprint a paper: Superiority of Multi-Head Attention in In-Context Linear Regression |
| Feb 5, 2024 | We release our survey paper about copyright: Copyright Protection in Generative AI: A Technical Perspective |
| Jan 16, 2024 | Our paper: Sharpness-aware Data Poisoning Attack is accepted as Spotlight (5%) by ICLR2024! |
| Oct 11, 2023 | We preprint a paper: Exploring Memorization in Fine-tuned Language Models. |
| Oct 10, 2023 | We preprint a paper: On the Generalization of Training-based ChatGPT Detection Methods. |
| Oct 10, 2023 | We preprint a paper: FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. |