3 papers
cs.CV2026
ThinkAfford: Affordance-Centric Reasoning for Fine-Grained 3D Grounding in Cluttered Scenes
Xinrui Lin, Sha Zhang, Shumin Wang +3
Task-driven 3D affordance grounding aims to localize the functional region in a cluttered 3D scene that enables an action specified by a natural-language instruction. Existing meth…
cs.LG2026
On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
Shumin Wang, Yuexiang Xie, Wenhao Zhang +4
Entropy serves as a critical metric for measuring the diversity of outputs generated by large language models (LLMs), providing valuable insights into their exploration capabilitie…
cs.CV2025
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving
Shumin Wang, Zhuoran Yang, Lidian Wang +7
The significant achievements of pre-trained models leveraging large volumes of data in the field of NLP and 2D vision inspire us to explore the potential of extensive data pre-trai…