3 papers
cs.AI2025
RoRecomp: Enhancing Reasoning Efficiency via Rollout Response Recomposition in Reinforcement Learning
Gang Li, Yulei Qin, Xiaoyu Tan +6
Reinforcement learning with verifiable rewards (RLVR) has proven effective in eliciting complex reasoning in large language models (LLMs). However, standard RLVR training often lea…
cs.CV2025
MMARD: Improving the Min-Max Optimization Process in Adversarial Robustness Distillation
Yuzheng Wang, Zhaoyu Chen, Dingkang Yang +2
Adversarial Robustness Distillation (ARD) is a promising task to boost the robustness of small-capacity models with the guidance of the pre-trained robust teacher. The ARD can be s…
cs.CV2025
Boosting Adversarial Transferability with Spatial Adversarial Alignment
Zhaoyu Chen, Haijing Guo, Kaixun Jiang +6
Deep neural networks are vulnerable to adversarial examples that exhibit transferability across various models. Numerous approaches are proposed to enhance the transferability of a…