Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability. - Haotian Xue 002; Alexandre Araujo; Bin Hu 002; Yongxin Chen (NeurIPS, 2023)

Toward effective protection against diffusion-based mimicry through score distillation. - Haotian Xue 002; Chumeng Liang; Xiaoyu Wu; Yongxin Chen (ICLR, 2024)

Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies. - Yipu Chen; Haotian Xue 002; Yongxin Chen (NeurIPS, 2024)

RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance. - Jiaojiao Fan; Haotian Xue 002; Qinsheng Zhang; Yongxin Chen (NeurIPS, 2024)

QueST: Self-Supervised Skill Abstractions for Learning Continuous Control. - Atharva Mete; Haotian Xue 002; Albert Wilcox; Yongxin Chen; Animesh Garg (NeurIPS, 2024)

Pixel is a Barrier: Diffusion Models Are More Adversarially Robust Than We Think. - Haotian Xue 002; Yongxin Chen (CoRR, 2024)