activity
20242026
most citedSVGen: Interpretable Vector Graphics Generation with Large Language Models

4 citations · 11 across the 25 of their papers we have counts for

collaborators

27 papers

cs.CV2026

Semantic-Aware Temporal Adaptation for UAV Anti-UAV Tracking

Xiaozhen Qiao, Da Zhang, Yubin Guo +3

UAV Anti-UAV tracking is an emerging low-altitude security task for localizing an adversarial UAV using the onboard camera of a moving observer UAV. It differs from conventional UA…

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.LG2026

Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale

Yicheng Zou, Dongsheng Zhu, Lin Zhu +174

We introduce Intern-S1-Pro, the first one-trillion-parameter scientific multimodal foundation model. Scaling to this unprecedented size, the model delivers a comprehensive enhancem…

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

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.CV2026

AHAP: Reconstructing Arbitrary Humans from Arbitrary Perspectives with Geometric Priors

Xiaozhen Qiao, Wenjia Wang, Zhiyuan Zhao +4

Reconstructing 3D humans from images captured at multiple perspectives typically requires pre-calibration, like using checkerboards or MVS algorithms, which limits scalability and…

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.CV2026

UNICBench: UNIfied Counting Benchmark for MLLM

Chenggang Rong, Tao Han, Zhiyuan Zhao +5

Counting is a core capability for multimodal large language models (MLLMs), yet there is no unified counting dataset to rigorously evaluate this ability across image, text, and aud…

cs.AI2026

Do MLLMs Really See It: Reinforcing Visual Attention in Multimodal LLMs

Siqu Ou, Tianrui Wan, Zhiyuan Zhao +2

While chain-of-thought (CoT) reasoning has substantially improved multimodal large language models (MLLMs) on complex reasoning tasks, existing approaches largely rely on long text…

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★ 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

Real-Time Crowd Counting for Embedded Systems with Lightweight Architecture

Zhiyuan Zhao, Yubin Wen, Siyu Yang +3

Crowd counting is a task of estimating the number of the crowd through images, which is extremely valuable in the fields of intelligent security, urban planning, public safety mana…

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.LG2025★ 4 cited

SVGen: Interpretable Vector Graphics Generation with Large Language Models

Feiyu Wang, Zhiyuan Zhao, Yuandong Liu +4

Scalable Vector Graphics (SVG) is widely used in front-end development and UI/UX design due to its scalability, editability, and rendering efficiency. However, turning creative ide…

cs.CR2025

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security

Muzhi Dai, Shixuan Liu, Zhiyuan Zhao +3

The rapid advancement of multimodal large language models (MLLMs) has led to breakthroughs in various applications, yet their security remains a critical challenge. One pressing is…

cs.CR2025

LLMs Caught in the Crossfire: Malware Requests and Jailbreak Challenges

Haoyang Li, Huan Gao, Zhiyuan Zhao +3

The widespread adoption of Large Language Models (LLMs) has heightened concerns about their security, particularly their vulnerability to jailbreak attacks that leverage crafted pr…

cs.CL2025

WebUIBench: A Comprehensive Benchmark for Evaluating Multimodal Large Language Models in WebUI-to-Code

Zhiyu Lin, Zhengda Zhou, Zhiyuan Zhao +4

With the rapid advancement of Generative AI technology, Multimodal Large Language Models(MLLMs) have the potential to act as AI software engineers capable of executing complex web…

cs.CV2025

From Captions to Rewards (CAREVL): Leveraging Large Language Model Experts for Enhanced Reward Modeling in Large Vision-Language Models

Muzhi Dai, Jiashuo Sun, Zhiyuan Zhao +4

Aligning large vision-language models (LVLMs) with human preferences is challenging due to the scarcity of fine-grained, high-quality, and multimodal preference data without human…

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…