Publications (19)
Recover to Predict: Progressive Retrospective Learning for Variable-Length Trajectory Prediction
Hao Zhou, Lu Qi, Jason Li +5
Trajectory prediction is critical for autonomous driving, enabling safe and efficient planning in dense, dynamic traffic. Most existing methods optimize prediction accuracy under f…
DLCA-Recon: Dynamic Loose Clothing Avatar Reconstruction from Monocular Videos
Chunjie Luo, Fei Luo, Yusen Wang +2
Reconstructing a dynamic human with loose clothing is an important but difficult task. To address this challenge, we propose a method named DLCA-Recon to create human avatars from…
MAVIS: Multi-Agent Video Retrieval via Structured Video Understanding
Jie Zhang, Qilang Ye, Hao Zhou +2
The dominant paradigm in video retrieval relies on embedding-based full-corpus scanning, which suffers from inherent computational inefficiency and the semantic asymmetry between i…
A Systematic Literature Review of Machine Learning Techniques for Observational Constraints in Cosmology
Luis Rojas, Sebastián Espinoza, Esteban González +2
This paper presents a systematic literature review focusing on the application of machine learning techniques for deriving observational constraints in cosmology. The goal is to ev…
RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation
Jindong Jiang, Lunan Zheng, Fei Luo +1
Indoor semantic segmentation has always been a difficult task in computer vision. In this paper, we propose an RGB-D residual encoder-decoder architecture, named RedNet, for indoor…
Neutron Time-Of-Flight Spectrometer Based on HIRFL for Studies of Spallation Reactions Related to ADS Project
Suyalatu Zhang, Zhiqiang Chen, Rui Han +8
A Neutron Time-Of-Flight (NTOF) spectrometer based on Heavy Ion Research Facility in Lanzhou (HIRFL) is developed for studies of neutron production of proton induced spallation rea…
Reasoning emerges from constrained inference manifolds in large language models
Yanbiao Ma, Fei Luo, Linfeng Zhang +10
Reasoning in large language models is predominantly evaluated through labeled benchmarks, conflating task performance with the quality of internal inference. Here we study reasonin…
Wi-Spike: A Low-power WiFi Human Multi-action Recognition Model with Spiking Neural Networks
Nengbo Zhang, Yao Ying, Lu Wang +3
WiFi-based human action recognition (HAR) has gained significant attention due to its non-intrusive and privacy-preserving nature. However, most existing WiFi sensing models predom…
SVSR: A Self-Verification and Self-Rectification Paradigm for Multimodal Reasoning
Zhe Qian, Nianbing Su, Zhonghua Wang +6
Current multimodal models often suffer from shallow reasoning, leading to errors caused by incomplete or inconsistent thought processes. To address this limitation, we propose Self…
Argus: Reorchestrating Static Analysis via a Multi-Agent Ensemble for Full-Chain Security Vulnerability Detection
Zi Liang, Qipeng Xie, Jun He +7
Recent advancements in Large Language Models (LLMs) have sparked interest in their application to Static Application Security Testing (SAST), primarily due to their superior contex…
Geometric Prior-Guided Federated Prompt Calibration
Fei Luo, Ziwei Zhao, Mingxuan Wang +5
Federated Prompt Learning (FPL) offers a parameter-efficient solution for collaboratively training large models, but its performance is severely hindered by data heterogeneity, whi…
Cognitive Pivot Points and Visual Anchoring: Unveiling and Rectifying Hallucinations in Multimodal Reasoning Models
Zhe Qian, Yanbiao Ma, Zhuohan Ouyang +7
Multimodal Large Reasoning Models (MLRMs) have achieved remarkable strides in visual reasoning through test time compute scaling, yet long chain reasoning remains prone to hallucin…
DGECN: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimation
Tuo Cao, Fei Luo, Yanping Fu +3
Monocular 6D pose estimation is a fundamental task in computer vision. Existing works often adopt a two-stage pipeline by establishing correspondences and utilizing a RANSAC algori…
FED-FSTQ: Fisher-Guided Token Quantization for Communication-Efficient Federated Fine-Tuning of LLMs on Edge Devices
Changyu Li, Shuanghong Huang, Jiashen Liu +5
Federated fine-tuning provides a practical route to adapt large language models (LLMs) on edge devices without centralizing private data. However, in mobile deployments, the traini…
Reliability-Calibrated Edge-IoT Early Fault Warning for Rotating Machinery with a Physics-Guided Tiny-Mamba Transformer
Changyu Li, Huabei Nie, Xiaoya Ni +4
Industrial Internet of Things (IIoT) systems increasingly rely on distributed vibration sensing to support predictive maintenance of rotating machinery. In practical deployments, h…
PI-TTA: Physics-Informed Source-Free Test-Time Adaptation for Robust Human Activity Recognition on Mobile Devices
Changyu Li, Lu Wang, Ming Lei +4
Source-free test-time adaptation (TTA) is appealing for mobile and wearable sensing because it enables on-device personalization from unlabeled test streams without centralizing pr…
CardiacMamba: A Multimodal RGB-RF Fusion Framework with State Space Models for Remote Physiological Measurement
Zheng Wu, Yiping Xie, Bo Zhao +4
Heart rate (HR) estimation via remote photoplethysmography (rPPG) offers a non-invasive solution for health monitoring. However, traditional single-modality approaches (RGB or Radi…
NeTO:Neural Reconstruction of Transparent Objects with Self-Occlusion Aware Refraction-Tracing
Zongcheng Li, Xiaoxiao Long, Yusen Wang +4
We present a novel method, called NeTO, for capturing 3D geometry of solid transparent objects from 2D images via volume rendering. Reconstructing transparent objects is a very cha…
From Perception to Cognition: A Survey of Vision-Language Interactive Reasoning in Multimodal Large Language Models
Chenyue Zhou, Mingxuan Wang, Yanbiao Ma +19
Multimodal Large Language Models (MLLMs) strive to achieve a profound, human-like understanding of and interaction with the physical world, but often exhibit a shallow and incohere…