5 citations · 15 across the 29 of their papers we have counts for
29 papers
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…
Semantic-Aware Logical Reasoning via a Semiotic Framework
Yunyao Zhang, Xinglang Zhang, Junxi Sheng +5
Logical reasoning is a fundamental capability of large language models. However, existing studies often overlook the interaction between logical complexity and semantic complexity,…
Cross-Modality Masked Learning for Survival Prediction in ICI Treated NSCLC Patients
Qilong Xing, Zikai Song, Bingxin Gong +3
Accurate prognosis of non-small cell lung cancer (NSCLC) patients undergoing immunotherapy is essential for personalized treatment planning, enabling informed patient decisions, an…
MCA-RG: Enhancing LLMs with Medical Concept Alignment for Radiology Report Generation
Qilong Xing, Zikai Song, Youjia Zhang +3
Despite significant advancements in adapting Large Language Models (LLMs) for radiology report generation (RRG), clinical adoption remains challenging due to difficulties in accura…
MVP: Winning Solution to SMP Challenge 2025 Video Track
Liliang Ye, Yunyao Zhang, Yafeng Wu +4
Social media platforms serve as central hubs for content dissemination, opinion expression, and public engagement across diverse modalities. Accurately predicting the popularity of…
HyperFusion: Hierarchical Multimodal Ensemble Learning for Social Media Popularity Prediction
Liliang Ye, Yunyao Zhang, Yafeng Wu +4
Social media popularity prediction plays a crucial role in content optimization, marketing strategies, and user engagement enhancement across digital platforms. However, predicting…
LoRA-Mixer: Coordinate Modular LoRA Experts Through Serial Attention Routing
Wenbing Li, Zikai Song, Hang Zhou +3
Recent attempts to combine low-rank adaptation (LoRA) with mixture-of-experts (MoE) for multi-task adaptation of Large Language Models (LLMs) often replace whole attention/FFN laye…
CA-Diff: Collaborative Anatomy Diffusion for Brain Tissue Segmentation
Qilong Xing, Zikai Song, Yuteng Ye +5
Segmentation of brain structures from MRI is crucial for evaluating brain morphology, yet existing CNN and transformer-based methods struggle to delineate complex structures accura…
GA-S: Comprehensive Social Network Simulation with Group Agents
Yunyao Zhang, Zikai Song, Hang Zhou +4
Social network simulation is developed to provide a comprehensive understanding of social networks in the real world, which can be leveraged for a wide range of applications such a…
SF2T: Self-supervised Fragment Finetuning of Video-LLMs for Fine-Grained Understanding
Yangliu Hu, Zikai Song, Na Feng +4
Video-based Large Language Models (Video-LLMs) have witnessed substantial advancements in recent years, propelled by the advancement in multi-modal LLMs. Although these models have…
MSF: Efficient Diffusion Model Via Multi-Scale Latent Factorize
Haohang Xu, Longyu Chen, Yichen Zhang +2
While diffusion-based generative models have made significant strides in visual content creation, conventional approaches face computational challenges, especially for high-resolut…
Video Anomaly Detection with Motion and Appearance Guided Patch Diffusion Model
Hang Zhou, Jiale Cai, Yuteng Ye +5
A recent endeavor in one class of video anomaly detection is to leverage diffusion models and posit the task as a generation problem, where the diffusion model is trained to recove…
IP-MOT: Instance Prompt Learning for Cross-Domain Multi-Object Tracking
Run Luo, Zikai Song, Longze Chen +3
Multi-Object Tracking (MOT) aims to associate multiple objects across video frames and is a challenging vision task due to inherent complexities in the tracking environment. Most e…
Autogenic Language Embedding for Coherent Point Tracking
Zikai Song, Ying Tang, Run Luo +4
Point tracking is a challenging task in computer vision, aiming to establish point-wise correspondence across long video sequences. Recent advancements have primarily focused on te…
TIGER: Text-Instructed 3D Gaussian Retrieval and Coherent Editing
Teng Xu, Jiamin Chen, Peng Chen +3
Editing objects within a scene is a critical functionality required across a broad spectrum of applications in computer vision and graphics. As 3D Gaussian Splatting (3DGS) emerges…
Coupled Mamba: Enhanced Multi-modal Fusion with Coupled State Space Model
Wenbing Li, Hang Zhou, Junqing Yu +2
The essence of multi-modal fusion lies in exploiting the complementary information inherent in diverse modalities. However, prevalent fusion methods rely on traditional neural arch…