6 papers
WorldBagel: Uncovering the Power of Unified Multimodal Models for Vision-Language-Action-World Modeling
Zelin Zhao, Min Shi, Bo Yuan +5
World models aim to capture environment dynamics in ways that support perception, reasoning, and action, and have recently become a central direction in Vision-Language-Action-Worl…
Beyond a Single Frame: Multi-Frame Spatially Grounded Reasoning Across Volumetric MRI
Lama Moukheiber, Caleb M. Yeung, Haotian Xue +3
Spatial reasoning and visual grounding are core capabilities for vision-language models (VLMs), yet most medical VLMs produce predictions without transparent reasoning or spatial e…
Immune2V: Image Immunization Against Dual-Stream Image-to-Video Generation
Zeqian Long, Ozgur Kara, Haotian Xue +2
Image-to-video (I2V) generation has the potential for societal harm because it enables the unauthorized animation of static images to create realistic deepfakes. While existing def…
Laplacian Multi-scale Flow Matching for Generative Modeling
Zelin Zhao, Petr Molodyk, Haotian Xue +1
In this paper, we present Laplacian multiscale flow matching (LapFlow), a novel framework that enhances flow matching by leveraging multi-scale representations for image generative…
MoGAN: Improving Motion Quality in Video Diffusion via Few-Step Motion Adversarial Post-Training
Haotian Xue, Qi Chen, Zhonghao Wang +4
Video diffusion models achieve strong frame-level fidelity but still struggle with motion coherence, dynamics and realism, often producing jitter, ghosting, or implausible dynamics…
Point-It-Out: Benchmarking Embodied Reasoning for Vision Language Models in Multi-Stage Visual Grounding
Haotian Xue, Yunhao Ge, Yu Zeng +4
Vision-Language Models (VLMs) have demonstrated impressive world knowledge across a wide range of tasks, making them promising candidates for embodied reasoning applications. Howev…