2 citations · 2 across the 18 of their papers we have counts for
9 papers · 2 filters
Adaptive Look, Flexible Thought: Learning How and How Long to Think in Multimodal Reasoning
Quanlin Chen, Xiuwei Chen, Kun Xiang +5
The introduction of long chain-of-thought (CoT) reasoning and external tools has substantially improved the performance of multimodal large language models (MLLMs) on general and r…
VR-JEPA: Learning Contrastive-State Latent Guidance for Generation-based Video Reasoning
Zehua Ma, Kun Xiang, Yunshuang Nie +9
Reasoning through video generation offers a promising path toward visual intelligence by modeling latent visual states and their dynamics. However, current video generation models…
Beyond the Eye: Efficient Multimodal Reasoning via Self-Regulated Implicit Visual Tools
Xiuwei Chen, Quanlin Chen, Wentao Hu +8
Recent multimodal large language models (MLLMs) have made remarkable progress on fine-grained perception tasks under the "Thinking with Images" (TwI) paradigm by iteratively perfor…
PhysEditWorld: A Large-Scale Dataset Toward Physics-Editable World Models
Bin Hu, Yanwen Ma, Jiehui Huang +14
Recent game world models can synthesize visually plausible, action-conditioned rollouts. However, their interaction behaviors often remain limited to exploratory or wandering traje…
Latent Visual States for Efficient Multimodal Reasoning
Xiuwei Chen, Wentao Hu, Yongxin Wang +8
The integration of visual evidence has significantly enhanced the capabilities of large multimodal models. However, this integration predominantly relies on generating discrete out…
Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving
Zisheng Chen, Yuping Qiu, Jianhua Han +6
Recent Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving by incorporating reasoning for better interpretability and planning quality. However, most ex…
MagicSeg: Open-World Segmentation Pretraining via Counterfactural Diffusion-Based Auto-Generation
Kaixin Cai, Pengzhen Ren, Jianhua Han +4
Open-world semantic segmentation presently relies significantly on extensive image-text pair datasets, which often suffer from a lack of fine-grained pixel annotations on sufficien…
RADAR: Revealing Asymmetric Development of Abilities in MLLM Pre-training
Yunshuang Nie, Bingqian Lin, Minzhe Niu +7
Pre-trained Multi-modal Large Language Models (MLLMs) provide a knowledge-rich foundation for post-training by leveraging their inherent perception and reasoning capabilities to so…
Thinking with Geometry: Active Geometry Integration for Spatial Reasoning
Haoyuan Li, Qihang Cao, Tao Tang +6
Recent progress in spatial reasoning with Multimodal Large Language Models (MLLMs) increasingly leverages geometric priors from 3D encoders. However, most existing integration stra…