1 citations · 1 across the 9 of their papers we have counts for
9 papers
Parallelized Autoregressive Decoding for Omni-Modal Dense Video Captioning
Wenzheng Zeng, Siyi Jiao, Chen Gao +2
Dense video captioning aims to generate temporally grounded descriptions of video events, benefiting both event-level video understanding and generation. In this domain, autoregres…
Supervise What Survives: Geometry-Guided VLA Adaptation from Synthetic Robot Videos
Danze Chen, Yanzhe Chen, Qiming Huang +3
Vision-Language-Action (VLA) models require large-scale video-action pairs, yet real teleoperation remains scarce. While generated robot videos offer a scalable alternative, existi…
ManiSoft: Towards Vision-Language Manipulation for Soft Continuum Robotics
Ziyu Wei, Luting Wang, Chen Gao +2
Most existing vision-language manipulation research targets rigid robotic arms, whose fixed morphology limits adaptability in cluttered or confined spaces. Soft robotic arms offer…
WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform
Yu Shang, Yinzhou Tang, Yiding Ma +26
World models have emerged as a central paradigm for embodied intelligence, enabling agents to predict action-conditioned future and reason about environmental dynamics. However, ex…
Escaping the Diversity Trap in Robotic Manipulation via Anchor-Centric Adaptation
Yanzhe Chen, Kevin Yuchen Ma, Qi Lv +4
While Vision-Language-Action (VLA) models offer broad general capabilities, deploying them on specific hardware requires real-world adaptation to bridge the embodiment gap. Since r…
EVOLVE-VLA: Test-Time Training from Environment Feedback for Vision-Language-Action Models
Zechen Bai, Chen Gao, Mike Zheng Shou
Achieving truly adaptive embodied intelligence requires agents that learn not just by imitating static demonstrations, but by continuously improving through environmental interacti…
PANDA: Towards Generalist Video Anomaly Detection via Agentic AI Engineer
Zhiwei Yang, Chen Gao, Mike Zheng Shou
Video anomaly detection (VAD) is a critical yet challenging task due to the complex and diverse nature of real-world scenarios. Previous methods typically rely on domain-specific t…
Reinforcement Learning for Large Model: A Survey
Weijia Wu, Chen Gao, Joya Chen +6
Recent advances at the intersection of reinforcement learning (RL) and visual intelligence have enabled agents that not only perceive complex visual scenes but also reason, generat…
AssistPDA: An Online Video Surveillance Assistant for Video Anomaly Prediction, Detection, and Analysis
Zhiwei Yang, Chen Gao, Jing Liu +3
The rapid advancements in large language models (LLMs) have spurred growing interest in LLM-based video anomaly detection (VAD). However, existing approaches predominantly focus on…