140 citations · 294 across the 69 of their papers we have counts for
70 papers
Surface Keypoint Representation for Multi-Object and Articulated Human-Object Interaction Generation
Xiaogang Peng, Zeyu Han, Zichong Meng +4
Daily activities require humans to coordinate whole-body motion with the motion of surrounding objects. Despite recent progress in human-object interaction (HOI) generation, most e…
Parameter-Efficient Fine-Tuning for Spiking Point Cloud Models
Zihao Guo, Jihua Zhu, Yiding Sun +2
Spiking Neural Networks (SNNs) offer energy-efficient solutions for point cloud analysis on resource-constrained devices through event-driven computation. However, existing pre-tra…
SpikingMOT: A Spike-Driven Multi-Object Tracker
Yiding Sun, Xiangyang Yang, Dongxu Zhang +7
Multi-object tracking (MOT) plays a fundamental role in visual perception, where accurate trajectory prediction is essential for reliable target association under complex motion pa…
Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning
Leichao Dong, Dongxu Zhang, Yiding Sun +4
Large reasoning models often solve problems through long chain-of-thought (CoT) traces, yet much of this computation is spent on redundant derivations, repeated self-verification,…
SPARK: Susceptibility-Guided Profiling and Steering of Latent Reasoning States in Large Language Models
Dongxu Zhang, Yiding Sun, Zihao Guo +5
Reasoning failures in large language models (LLMs) are usually evaluated from final answers, but a wrong answer does not reveal why the model failed. The same incorrect output may…
GaussFusion: Towards Multimodal 3D Gaussian Pretraining
Zhixuan You, Jihua Zhu, Yiding Sun +5
3D Gaussian Splatting provides an explicit representation that jointly models geometry and appearance, serving as a scalable foundation for 3D representation learning. Existing pre…
Tri-Efficient Transfer Learning for Point Cloud Videos
Yiding Sun, Dongxu Zhang, Jihua Zhu +6
While point cloud foundation models have significantly advanced point cloud video understanding, existing parameter-efficient fine-tuning (PEFT) methods still suffer from two criti…
Diffusion Masked Pretraining for Dynamic Point Cloud
Zhuoyue Zhang, Jihua Zhu, Yiding Sun +4
Dynamic point cloud pretraining is still dominated by masked reconstruction objectives. However, these objectives inherit two key limitations. Existing methods inject ground-truth…
Mantis: Mamba-native Tuning is Efficient for 3D Point Cloud Foundation Models
Zihao Guo, Jihua Zhu, Yiding Sun +3
Pre-trained 3D point cloud foundation models (PFMs) have demonstrated strong transferability across diverse downstream tasks. However, full fine-tuning these models is computationa…
Beyond Factor Aggregation: Gauge-Aware Low-Rank Server Representations for Federated LoRA
Jinqian Chen, Chang Liu, Jihua Zhu
Federated LoRA enables parameter-efficient adaptation of large language models under decentralized data and limited client resources.However, directly averaging LoRA factors is rep…
Controllable Singing Style Conversion with Boundary-Aware Information Bottleneck
Zhetao Hu, Yiquan Zhou, Wenyu Wang +3
This paper presents the submission of the S4 team to the Singing Voice Conversion Challenge 2025 (SVCC2025)-a novel singing style conversion system that advances fine-grained style…
CMHANet: A Cross-Modal Hybrid Attention Network for Point Cloud Registration
Dongxu Zhang, Yingsen Wang, Yiding Sun +3
Robust point cloud registration is a fundamental task in 3D computer vision and geometric deep learning, essential for applications such as large-scale 3D reconstruction, augmented…
IGASA: Integrated Geometry-Aware and Skip-Attention Modules for Enhanced Point Cloud Registration
Dongxu Zhang, Jihua Zhu, Shiqi Li +4
Point cloud registration (PCR) is a fundamental task in 3D vision and provides essential support for applications such as autonomous driving, robotics, and environmental modeling.…
Not All Queries Need Deep Thought: CoFiCot for Adaptive Coarse-to-fine Stateful Refinement
Dongxu Zhang, Hongqiang Lin, Yiding Sun +4
Scaling test-time computation enhances LLM reasoning ability but faces a uniform computation paradox. Allocating identical resources leads to over-correction on simple tasks and in…
PointCoT: A Multi-modal Benchmark for Explicit 3D Geometric Reasoning
Dongxu Zhang, Yiding Sun, Pengcheng Li +12
While Multimodal Large Language Models (MLLMs) demonstrate proficiency in 2D scenes, extending their perceptual intelligence to 3D point cloud understanding remains a significant c…
FedPSA: Modeling Behavioral Staleness in Asynchronous Federated Learning
Chaoyi Lu, Yiding Sun, Zhichuan Yang +3
Asynchronous Federated Learning (AFL) has emerged as a significant research area in recent years. By not waiting for slower clients and executing the training process concurrently,…
Align then Adapt: Rethinking Parameter-Efficient Transfer Learning in 4D Perception
Yiding Sun, Jihua Zhu, Haozhe Cheng +4
Point cloud video understanding is critical for robotics as it accurately encodes motion and scene interaction. We recognize that 4D datasets are far scarcer than 3D ones, which ha…
Point-SRA: Self-Representation Alignment for 3D Representation Learning
Lintong Wei, Jian Lu, Haozhe Cheng +2
Masked autoencoders (MAE) have become a dominant paradigm in 3D representation learning, setting new performance benchmarks across various downstream tasks. Existing methods with f…
Chain-of-Thought Compression Should Not Be Blind: V-Skip for Efficient Multimodal Reasoning via Dual-Path Anchoring
Dongxu Zhang, Yiding Sun, Cheng Tan +4
While Chain-of-Thought (CoT) reasoning significantly enhances the performance of Multimodal Large Language Models (MLLMs), its autoregressive nature incurs prohibitive latency cons…
OpenUrban3D: Annotation-Free Open-Vocabulary Semantic Segmentation of Large-Scale Urban Point Clouds
Chongyu Wang, Kunlei Jing, Jihua Zhu +1
Open-vocabulary semantic segmentation enables models to recognize and segment objects from arbitrary natural language descriptions, offering the flexibility to handle novel, fine-g…
Not All Errors Are Created Equal: ASCoT Addresses Late-Stage Fragility in Efficient LLM Reasoning
Dongxu Zhang, Yujun Wu, Yiding Sun +5
While Chain-of-Thought (CoT) prompting empowers Large Language Models (LLMs), ensuring reasoning reliability remains an open challenge. Contrary to the prevailing cascading failure…
AFBS:Buffer Gradient Selection in Semi-asynchronous Federated Learning
Chaoyi Lu, Yiding Sun, Jinqian Chen +3
Asynchronous federated learning (AFL) accelerates training by eliminating the need to wait for stragglers, but its asynchronous nature introduces gradient staleness, where outdated…
Matching Distance and Geometric Distribution Aided Learning Multiview Point Cloud Registration
Shiqi Li, Jihua Zhu, Yifan Xie +2
Multiview point cloud registration plays a crucial role in robotics, automation, and computer vision fields. This paper concentrates on pose graph construction and motion synchroni…
AVENet: Disentangling Features by Approximating Average Features for Voice Conversion
Wenyu Wang, Yiquan Zhou, Jihua Zhu +3
Voice conversion (VC) has made progress in feature disentanglement, but it is still difficult to balance timbre and content information. This paper evaluates the pre-trained model…