16 citations · 18 across the 5 of their papers we have counts for
7 papers
MorphoSim: An Interactive, Controllable, and Editable Language-guided 4D World Simulator
Xuehai He, Shijie Zhou, Thivyanth Venkateswaran +4
World models that support controllable and editable spatiotemporal environments are valuable for robotics, enabling scalable training data, repro ducible evaluation, and flexible t…
VLM4D: Towards Spatiotemporal Awareness in Vision Language Models
Shijie Zhou, Alexander Vilesov, Xuehai He +7
Vision language models (VLMs) have shown remarkable capabilities in integrating linguistic and visual reasoning but remain fundamentally limited in understanding dynamic spatiotemp…
Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space
Zhen Zhang, Xuehai He, Weixiang Yan +5
Human cognition typically involves thinking through abstract, fluid concepts rather than strictly using discrete linguistic tokens. Current reasoning models, however, are constrain…
Mojito: Motion Trajectory and Intensity Control for Video Generation
Xuehai He, Shuohang Wang, Jianwei Yang +7
Recent advancements in diffusion models have shown great promise in producing high-quality video content. However, efficiently training video diffusion models capable of integratin…
FlexEControl: Flexible and Efficient Multimodal Control for Text-to-Image Generation
Xuehai He, Jian Zheng, Jacob Zhiyuan Fang +6
Controllable text-to-image (T2I) diffusion models generate images conditioned on both text prompts and semantic inputs of other modalities like edge maps. Nevertheless, current con…
Worse than Random? An Embarrassingly Simple Probing Evaluation of Large Multimodal Models in Medical VQA
Qianqi Yan, Xuehai He, Xiang Yue +1
Large Multimodal Models (LMMs) have shown remarkable progress in medical Visual Question Answering (Med-VQA), achieving high accuracy on existing benchmarks. However, their reliabi…
MiniGPT-5: Interleaved Vision-and-Language Generation via Generative Vokens
Kaizhi Zheng, Xuehai He, Xin Eric Wang
The effectiveness of Multimodal Large Language Models (MLLMs) demonstrates a profound capability in multimodal understanding. However, the simultaneous generation of images with co…