4 papers
ThinkV2V: Unleashing the Reasoning Capability of MLLMs for Instruction-Guided Video Editing
Donghao Zhou, Haoyang He, Fan Zhang +10
Instruction-guided video editing has made significant progress, yet existing methods use multimodal large language models (MLLMs) primarily as semantic encoders, so they often fall…
PackLab: A Comprehensive Framework for Developing, Training, and Evaluating MLLMs in Robotic Bin Packing
Donghao Zhou, Jia-Hui Pan, Fan Zhang +6
Robotic bin packing requires long-horizon sequential decision-making, as each object placement affects the available space for subsequent packing. Existing methods primarily rely o…
OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining
Yuran Wang, Siqiao Huang, Mingleyang Li +21
World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Existing systems, however, are…
AgenticGen: Reward-Guided Agentic Video Generation for Advertising
Xingyuan Bu, Chengru Song, Hao Zhou +9
Advertising video generation is not only a video synthesis task, but also a product-conditioned reasoning problem whose success is measured by online business metrics. Recent video…