5 citations · 15 across the 29 of their papers we have counts for
9 papers · 1 filter
UniMoFlow: Grounding Instruction-Driven 3D Human Motion Editing in Generation
Yilei Hua, Beibei Jing, Ce Zheng +3
Instruction-driven editing of 3D human motion requires precise spatiotemporal localization, rich semantic grounding, and strict preservation of unmodified content. Existing methods…
PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization
Ying Tang, Dong Li, Youjia Zhang +3
Unifying the complementary strengths of diverse Vision Foundation Models (VFMs) into a single efficient model is highly desirable but challenged by the negative transfer inherent i…
CurEvo: Curriculum-Guided Self-Evolution for Video Understanding
Guiyi Zeng, Junqing Yu, Yi-Ping Phoebe Chen +3
Recent advances in self-evolution video understanding frameworks have demonstrated the potential of autonomous learning without human annotations. However, existing methods often s…
GateMOT: Q-Gated Attention for Dense Object Tracking
Mingjin Lv, Zelin Liu, Feifei Shao +4
While large models demonstrate the strong representational power of vanilla attention, this core mechanism cannot be directly applied to Dense Object Tracking: its quadratic all-to…
IntervenSim: Intervention-Aware Social Network Simulation for Opinion Dynamics
Yunyao Zhang, Zuocheng Ying, Xinglang Zhang +5
LLM-based social network simulation introduces a new computational approach for modeling event evolution in complex online environments. However, existing methods typically simulat…
Hypergraph-State Collaborative Reasoning for Multi-Object Tracking
Zikai Song, Junqing Yu, Yi-Ping Phoebe Chen +2
Motion reasoning serves as the cornerstone of multi-object tracking (MOT), as it enables consistent association of targets across frames. However, existing motion estimation approa…
Coupling Macro Dynamics and Micro States for Long-Horizon Social Simulation
Yunyao Zhang, Yihao Ai, Zuocheng Ying +4
Social network simulation aims to model collective opinion dynamics in large populations, but existing LLM-based simulators mainly focus on aggregate dynamics while largely ignorin…
Large Language Model as Token Compressor and Decompressor
Wenbing Li, Yiran Wang, Zikai Song +4
In this paper, we study whether an off-the-shelf LLM can be adapted into a discrete, variable-length token compressor and decompressor for long-context processing. To this end, we…
Logical Phase Transitions: Understanding Collapse in LLM Logical Reasoning
Xinglang Zhang, Yunyao Zhang, ZeLiang Chen +3
Symbolic logical reasoning is a critical yet underexplored capability of large language models (LLMs), providing reliable and verifiable decision-making in high-stakes domains such…