2 citations · 4 across the 15 of their papers we have counts for
7 papers · 1 filter
ProPhy: Progressive Physical Alignment for Dynamic World Simulation
Zijun Wang, Panwen Hu, Jing Wang +7
Recent advances in video generation have shown remarkable potential for constructing world simulators. However, current models still struggle to produce physically consistent resul…
Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI
Kun Xiang, Terry Jingchen Zhang, Yinya Huang +13
The rapid advancement of embodied intelligence and world models has intensified efforts to integrate physical laws into AI systems, yet physical perception and symbolic physics rea…
LaVieID: Local Autoregressive Diffusion Transformers for Identity-Preserving Video Creation
Wenhui Song, Hanhui Li, Jiehui Huang +5
In this paper, we present LaVieID, a novel \underline{l}ocal \underline{a}utoregressive \underline{vi}d\underline{e}o diffusion framework designed to tackle the challenging \underl…
SyncLoop: A Multimodal Dual-Loop Framework for Self-Improving Mathematical Reasoning
Xiuwei Chen, Wentao Hu, Hanhui Li +9
Recent advances in multimodal large language models (MLLMs) have shown impressive reasoning capabilities. However, further enhancing existing MLLMs necessitates high-quality vision…
SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning
Kun Xiang, Heng Li, Terry Jingchen Zhang +11
We present SeePhys, a large-scale multimodal benchmark for LLM reasoning grounded in physics questions ranging from middle school to PhD qualifying exams. The benchmark covers 7 fu…
FireEdit: Fine-grained Instruction-based Image Editing via Region-aware Vision Language Model
Jun Zhou, Jiahao Li, Zunnan Xu +6
Currently, instruction-based image editing methods have made significant progress by leveraging the powerful cross-modal understanding capabilities of vision language models (VLMs)…
Can Atomic Step Decomposition Enhance the Self-structured Reasoning of Multimodal Large Models?
Kun Xiang, Zhili Liu, Zihao Jiang +13
In this paper, we address the challenging task of multimodal mathematical reasoning by incorporating the ability of "slow thinking" into multimodal large language models (MLLMs). O…