8 papers
ThinkJEPA: Empowering Latent World Models with Large Vision-Language Reasoning Model
Haichao Zhang, Yijiang Li, Shwai He +5
Recent progress in latent world models (e.g., V-JEPA2) has shown promising capability in forecasting future world states from video observations. Nevertheless, dense prediction fro…
PhyGround: Benchmarking Physical Reasoning in Generative World Models
Juyi Lin, Arash Akbari, Yumei He +13
Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern real-world dynamics. However, ev…
Demystifying When Pruning Works via Representation Hierarchies
Shwai He, Guoheng Sun, Haichao Zhang +2
Network pruning, which removes less important parameters or architectures, is often expected to improve efficiency while preserving performance. However, this expectation does not…
Out-of-Sight Embodied Agents: Multimodal Tracking, Sensor Fusion, and Trajectory Forecasting
Haichao Zhang, Yi Xu, Yun Fu
Trajectory prediction is a fundamental problem in computer vision, vision-language-action models, world models, and autonomous systems, with broad impact on autonomous driving, rob…
LinkedOut: Linking World Knowledge Representation Out of Video LLM for Next-Generation Video Recommendation
Haichao Zhang, Yao Lu, Lichen Wang +4
Video Large Language Models (VLLMs) unlock world-knowledge-aware video understanding through pretraining on internet-scale data and have already shown promise on tasks such as movi…
Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection
Haichao Zhang, Can Qin, Yu Yin +1
Camouflaged objects that blend into natural scenes pose significant challenges for deep-learning models to detect and synthesize. While camouflaged object detection is a crucial ta…