8 papers
Constitutional On-Policy Safe Distillation
Ming Wen, Yuxuan Liu, Kun Yang +8
On-policy self-distillation (OPSD) has emerged as an efficient post-training paradigm by using a teacher conditioned on privileged information to provide dense token-level supervis…
Orthogonal Concept Erasure for Diffusion Models
Yuhao Sun, Lingyun Yu, Haoxiang Xu +3
Concept erasure has emerged as a promising approach to mitigate undesired or unsafe content in diffusion models, yet existing methods still face significant limitations. While trai…
Unraveling the Hidden Dynamical Structure in Recurrent Neural Policies
Jin Li, Yue Wu, Mengsha Huang +3
Recurrent neural policies are widely used in partially observable control and meta-RL tasks. Their abilities to maintain internal memory and adapt quickly to unseen scenarios have…
Multiplicative Orthogonal Sequential Editing for Language Models
Hao-Xiang Xu, Jun-Yu Ma, Ziqi Peng +3
Knowledge editing aims to efficiently modify the internal knowledge of large language models (LLMs) without compromising their other capabilities. The prevailing editing paradigm,…
UpSafeC: Upcycling for Controllable Safety in Large Language Models
Yuhao Sun, Zhuoer Xu, Shiwen Cui +4
Large Language Models (LLMs) have achieved remarkable progress across a wide range of tasks, but remain vulnerable to safety risks such as harmful content generation and jailbreak…
Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design
Yuhao Sun, Yihua Zhang, Gaowen Liu +2
With the increasing demand for the right to be forgotten, machine unlearning (MU) has emerged as a vital tool for enhancing trust and regulatory compliance by enabling the removal…
Be Careful When Fine-tuning On Open-Source LLMs: Your Fine-tuning Data Could Be Secretly Stolen!
Zhexin Zhang, Yuhao Sun, Junxiao Yang +4
Fine-tuning on open-source Large Language Models (LLMs) with proprietary data is now a standard practice for downstream developers to obtain task-specific LLMs. Surprisingly, we re…
DiffAM: Diffusion-based Adversarial Makeup Transfer for Facial Privacy Protection
Yuhao Sun, Lingyun Yu, Hongtao Xie +2
With the rapid development of face recognition (FR) systems, the privacy of face images on social media is facing severe challenges due to the abuse of unauthorized FR systems. Som…