2.4k citations
- Beijing Academy of Artificial IntelligenceCN102 papers
- Shanghai Jiao Tong UniversityCN46 papers
- Chinese University of Hong KongHK26 papers
- Tsinghua UniversityCN25 papers
- Fudan UniversityCN21 papers
- Group Sense (China)CN17 papers
- Northwestern Polytechnical UniversityCN14 papers
- ShangHai JiAi Genetics & IVF InstituteCN14 papers
- University of Science and Technology of ChinaCN14 papers
- University of Hong KongHK13 papers
- Peking UniversityCN11 papers
- Tongji UniversityCN11 papers
182 papers
OmniPoser: Flexible Human Motion Recovery in the Wild with Masked Flow Matching
Minghao Liu, Tutian Tang
Recovering 3D human motion from sparse wearable sensors is challenging due to the inherent noise, occlusion, and instability of real-world tracking signals. Existing approaches are…
WAND: Learning Robust Navigation under Complex Wind Disturbances and Dense Obstacles for Quadrotors
Zhonghan Tang, Chenhui Li, Shuai Liang +5
Robust navigation in cluttered environments remains a fundamental challenge for quadrotors, particularly when strong wind disturbances arise, which perturb vehicle dynamics, limit…
Understanding Cognition-Induced Risks in Agentic AI Systems
Guanchu Wang, Qinuo Li, Mengnan Du +2
Frontier agentic systems powered by large language models (LLMs) exhibit human-like patterns of cognition. As these systems become deeply integrated across different domains, their…
Odin: Primitive-Level Synchronization for Distributed Point-Based Neural Rendering
Zhenxiang Ma, Zeyu He, Yuanzhen Zhou +6
Point-based neural rendering (PBNR) represents 3D scenes as explicit, trainable primitives and underpins high-quality reconstruction and emerging embodied AI and world-model pipeli…
DiTango: Cost-Effective Parallel Diffusion Generation with Selective Attention State Reuse
Yuyang Chen, Runxin Zhong, Zan Zong +3
Recent advances in AI-generated content have driven widespread adoption of Diffusion Transformers (DiTs) for high-resolution, long-duration content generation. While parallelizatio…
MLLM-DataEngine: Closing the Loop of Multimodal Instruction Tuning Data Generation
Zhiyuan Zhao, Bin Wang, Linke Ouyang +5
In this paper, we propose MLLM-DataEngine, a novel closed-loop system that bridges data generation, model training, and evaluation. Within each loop iteration, the MLLM-DataEngine…