5 papers
RPFQ-ViT: Rotated Phase-Frame Quantization for Extremely Low-Bit Weights in Vision Transformers
Mengyuan Fan, Bokai Huang, JiaMing Pan +4
Vision Transformers (ViTs) achieve strong performance on image recognition and mobile vision applications, but their high-dimensional linear projections and attention computations…
Teaching Vision-Language-Action Models What to See and Where to Look
Yuguang Yang, Canyu Chen, Zhewen Tan +10
Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving. However, existing VLAs' training relies heavily on text-centric visual q…
Devil is in Narrow Policy: Unleashing Exploration in Driving VLA Models
Canyu Chen, Yuguang Yang, Zhewen Tan +10
We identify a fundamental Narrow Policy limitation undermining the performance of autonomous VLA models, where driving Imitation Learning (IL) tends to collapse exploration and lim…
TriPlay-RL: Tri-Role Self-Play Reinforcement Learning for LLM Safety Alignment
Zhewen Tan, Wenhan Yu, Jianfeng Si +9
In recent years, safety risks associated with large language models have become increasingly prominent, highlighting the urgent need to mitigate the generation of toxic and harmful…
Efficient Switchable Safety Control in LLMs via Magic-Token-Guided Co-Training
Jianfeng Si, Lin Sun, Zhewen Tan +1
Current methods for content safety in Large Language Models (LLMs), such as Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF), often rely on multi-…