1 citations · 1 across the 3 of their papers we have counts for
5 papers
SAVLA: Symmetry-Aware Vision-Language-Action Models for Robotic Manipulation
Junle Li, Weixian Waylon Li, Fuxiang Wu +2
Vision-language-action (VLA) models have become the dominant paradigm for language-conditioned robot manipulation. However, although images and language instructions inherently enc…
IVR-R1: Refining Trajectories through Iterative Visual-Grounded Reasoning in Reinforcement Learning
Chenghao Li, Fusheng Hao, Xikai Zhang +5
Multimodal large language models via reinforcement learning (RL) have demonstrated remarkable capabilities in complex visual reasoning tasks, yet they remain limited in long-horizo…
Gradient-based Fine-Tuning through Pre-trained Model Regularization
Xuanbo Liu, Liu Liu, Fuxiang Wu +2
Large pre-trained models have demonstrated extensive applications across various fields. However, fine-tuning these models for specific downstream tasks demands significant computa…
SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation
Yanwei Ren, Haotian Zhang, Fuxiang Wu +4
Enhancing large language models by simply scaling up datasets has begun to yield diminishing returns, shifting the spotlight to data quality. Monte Carlo Tree Search (MCTS) has eme…
Human-imperceptible, Machine-recognizable Images
Fusheng Hao, Fengxiang He, Yikai Wang +4
Massive human-related data is collected to train neural networks for computer vision tasks. A major conflict is exposed relating to software engineers between better developing AI…