7 papers
Paving the Way for Point Cloud Video Representation Learning Using A PDE Model
Zhuoxu Huang, Zhenkun Fan, Jungong Han +1
Investigating spatial-temporal correlations, specifically how spatial points vary over time, is crucial for understanding point cloud videos. Traditional methods, particularly flow…
Cognitive Pivot Points and Visual Anchoring: Unveiling and Rectifying Hallucinations in Multimodal Reasoning Models
Zhe Qian, Yanbiao Ma, Zhuohan Ouyang +7
Multimodal Large Reasoning Models (MLRMs) have achieved remarkable strides in visual reasoning through test time compute scaling, yet long chain reasoning remains prone to hallucin…
Reasoning emerges from constrained inference manifolds in large language models
Yanbiao Ma, Fei Luo, Linfeng Zhang +10
Reasoning in large language models is predominantly evaluated through labeled benchmarks, conflating task performance with the quality of internal inference. Here we study reasonin…
Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding
Chang Liu, Henghui Ding, Nikhila Ravi +40
This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, whi…
Reinforcing 3D Understanding in Point-VLMs via Geometric Reward Credit Assignment
Jingkun Chen, Ruoshi Xu, Mingqi Gao +2
Point-Vision-Language Models promise to empower embodied agents with executable spatial reasoning, yet they frequently succumb to geometric hallucination where predicted 3D structu…
Controllable Exploration in Hybrid-Policy RLVR for Multi-Modal Reasoning
Zhuoxu Huang, Mengxi Jia, Hao Sun +2
Reinforcement Learning with verifiable rewards (RLVR) has emerged as a primary learning paradigm for enhancing the reasoning capabilities of multi-modal large language models (MLLM…