4 papers
Enhancing the Outcome Reward-based RL Training of MLLMs with Self-Consistency Sampling
Jiahao Wang, Weiye Xu, Aijun Yang +5
Outcome-reward reinforcement learning (RL) is a common and increasingly significant way to refine the step-by-step reasoning of multimodal large language models (MLLMs). In the mul…
VisuLogic: A Benchmark for Evaluating Visual Reasoning in Multi-modal Large Language Models
Weiye Xu, Jiahao Wang, Weiyun Wang +10
Visual reasoning is a core component of human intelligence and a critical capability for advanced multimodal models. Yet current reasoning evaluations of multimodal large language…
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Jinguo Zhu, Weiyun Wang, Zhe Chen +48
We introduce InternVL3, a significant advancement in the InternVL series featuring a native multimodal pre-training paradigm. Rather than adapting a text-only large language model…
PVC: Progressive Visual Token Compression for Unified Image and Video Processing in Large Vision-Language Models
Chenyu Yang, Xuan Dong, Xizhou Zhu +7
Large Vision-Language Models (VLMs) have been extended to understand both images and videos. Visual token compression is leveraged to reduce the considerable token length of visual…