activity
20242026
most citedU3M: Unbiased Multiscale Modal Fusion Model for Multimodal Semantic Segmentation

3 citations · 6 across the 17 of their papers we have counts for

collaborators

19 papers

cs.CV2026

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation

Bingyu Li, Da Zhang, Tao Huo +3

Large Vision-Language Models (LVLMs) have shown strong visual understanding and language-guided grounding abilities, yet their capacity for multi-temporal visual reasoning remains…

cs.LG2026

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification

Da Zhang, Bingyu Li, Zhiyuan Zhao +3

Medical time series are central to healthcare, enabling continuous monitoring and supporting timely clinical decisions. Despite recent progress, existing methods struggle to jointl…

cs.CV2026

Perturbation-Regularized Open-Vocabulary Remote Sensing Segmentation with Unified Multi-Domain Evaluation

Bingyu Li, Tao Huo, Haocheng Dong +4

Open-vocabulary remote sensing image segmentation (OVRSIS) aims to segment text-specified categories beyond a fixed label space. Its key challenge is to maintain reliable pixel--te…

cs.CV2026

Reward-Aware Trajectory Shaping for Few-step Visual Generation

Rui Li, Bingyu Li, Yuanzhi Liang +3

Achieving high-fidelity generation in extremely few sampling steps has long been a central goal of generative modeling. Existing approaches largely rely on distillation-based frame…

cs.CV2026

Boosting Quantitive and Spatial Awareness for Zero-Shot Object Counting

Da Zhang, Bingyu Li, Feiyu Wang +2

Zero-shot object counting (ZSOC) aims to enumerate objects of arbitrary categories specified by text descriptions without requiring visual exemplars. However, existing methods ofte…

cs.CL2026

Mitigating Overthinking in Large Reasoning Language Models via Reasoning Path Deviation Monitoring

Weixin Guan, Liang Li, Jiapeng Liu +6

Large Reasoning Language Models (LRLMs) demonstrate impressive capabilities on complex tasks by utilizing long Chain-of-Thought reasoning. However, they are prone to overthinking,…

cs.CV2026

IntroSVG: Learning from Rendering Feedback for Text-to-SVG Generation via an Introspective Generator-Critic Framework

Feiyu Wang, Jiayuan Yang, Zhiyuan Zhao +4

Scalable Vector Graphics (SVG) are central to digital design due to their inherent scalability and editability. Despite significant advancements in content generation enabled by Vi…

cs.LG2025

FusAD: Time-Frequency Fusion with Adaptive Denoising for General Time Series Analysis

Da Zhang, Bingyu Li, Zhiyuan Zhao +3

Time series analysis plays a vital role in fields such as finance, healthcare, industry, and meteorology, underpinning key tasks including classification, forecasting, and anomaly…

cs.LG2025

UniDiff: A Unified Diffusion Framework for Multimodal Time Series Forecasting

Da Zhang, Bingyu Li, Zhuyuan Zhao +3

As multimodal data proliferates across diverse real-world applications, leveraging heterogeneous information such as texts and timestamps for accurate time series forecasting (TSF)…

cs.LG2025★ 1 cited

FAIM: Frequency-Aware Interactive Mamba for Time Series Classification

Da Zhang, Bingyu Li, Zhiyuan Zhao +4

Time series classification (TSC) is crucial in numerous real-world applications, such as environmental monitoring, medical diagnosis, and posture recognition. TSC tasks require mod…

cs.CV2025

Exploring the Underwater World Segmentation without Extra Training

Bingyu Li, Tao Huo, Da Zhang +3

Accurate segmentation of marine organisms is vital for biodiversity monitoring and ecological assessment, yet existing datasets and models remain largely limited to terrestrial sce…

cs.CV2025

UWBench: A Comprehensive Vision-Language Benchmark for Underwater Understanding

Da Zhang, Chenggang Rong, Bingyu Li +4

Large vision-language models (VLMs) have achieved remarkable success in natural scene understanding, yet their application to underwater environments remains largely unexplored. Un…

cs.CV2025

MARIS: Marine Open-Vocabulary Instance Segmentation with Geometric Enhancement and Semantic Alignment

Bingyu Li, Feiyu Wang, Da Zhang +3

Most existing underwater instance segmentation approaches are constrained by close-vocabulary prediction, limiting their ability to recognize novel marine categories. To support ev…

cs.CV2025

Exploring Efficient Open-Vocabulary Segmentation in the Remote Sensing

Bingyu Li, Haocheng Dong, Da Zhang +3

Open-Vocabulary Remote Sensing Image Segmentation (OVRSIS), an emerging task that adapts Open-Vocabulary Segmentation (OVS) to the remote sensing (RS) domain, remains underexplored…

cs.CV2025

FGAseg: Fine-Grained Pixel-Text Alignment for Open-Vocabulary Semantic Segmentation

Bingyu Li, Da Zhang, Zhiyuan Zhao +2

Open-vocabulary segmentation aims to identify and segment specific regions and objects based on text-based descriptions. A common solution is to leverage powerful vision-language m…

cs.CV2024

Quantum-inspired Interpretable Deep Learning Architecture for Text Sentiment Analysis

Bingyu Li, Da Zhang, Zhiyuan Zhao +2

Text has become the predominant form of communication on social media, embedding a wealth of emotional nuances. Consequently, the extraction of emotional information from text is o…

cs.CV2024★ 2 cited

StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation

Bingyu Li, Da Zhang, Zhiyuan Zhao +2

Multimodal semantic segmentation shows significant potential for enhancing segmentation accuracy in complex scenes. However, current methods often incorporate specialized feature f…

cs.CV2024★ 3 cited

U3M: Unbiased Multiscale Modal Fusion Model for Multimodal Semantic Segmentation

Bingyu Li, Da Zhang, Zhiyuan Zhao +2

Multimodal semantic segmentation is a pivotal component of computer vision and typically surpasses unimodal methods by utilizing rich information set from various sources.Current m…

cs.CV2024

CREST: Cross-modal Resonance through Evidential Deep Learning for Enhanced Zero-Shot Learning

Haojian Huang, Xiaozhen Qiao, Zhuo Chen +5

Zero-shot learning (ZSL) enables the recognition of novel classes by leveraging semantic knowledge transfer from known to unknown categories. This knowledge, typically encapsulated…