activity
20232026
most citedMETER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection

23 citations · 34 across the 13 of their papers we have counts for

collaborators

16 papers

cs.LG2026

Geometric Regularization for Long-Tailed Semi-Supervised Learning via Gaussian Feature Bridges

Hongyang He, Xinyuan Song, Yan Zhong +4

Real-world semi-supervised learning (SSL) often encounters significant challenges with long-tailed label distributions and noisy pseudo-labels, which hinder generalization and ampl…

cs.CV2026

MAU-GPT: Enhancing Multi-type Industrial Anomaly Understanding via Anomaly-aware and Generalist Experts Adaptation

Zhuonan Wang, Zhenxuan Fan, Siwen Tan +8

As industrial manufacturing scales, automating fine-grained product image analysis has become critical for quality control. However, existing approaches are hindered by limited dat…

cs.CV2026

Unified Personalized Understanding, Generating and Editing

Yu Zhong, Tianwei Lin, Ruike Zhu +9

Unified large multimodal models (LMMs) have achieved remarkable progress in general-purpose multimodal understanding and generation. However, they still operate under a ``one-size-…

cs.CV2026

AnyMS: Bottom-up Attention Decoupling for Layout-guided and Training-free Multi-subject Customization

Binhe Yu, Zhen Wang, Kexin Li +6

Multi-subject customization aims to synthesize multiple user-specified subjects into a coherent image. To address issues such as subjects missing or conflicts, recent works incorpo…

cs.CL2026

PILOT: Planning via Internalized Latent Optimization Trajectories for Large Language Models

Haoyu Zheng, Yun Zhu, Yuqian Yuan +4

Strategic planning is critical for multi-step reasoning, yet compact Large Language Models (LLMs) often lack the capacity to formulate global strategies, leading to error propagati…

cs.CL2025

Fast Thinking for Large Language Models

Haoyu Zheng, Zhuonan Wang, Yuqian Yuan +7

Reasoning-oriented Large Language Models (LLMs) often rely on generating explicit tokens step by step, and their effectiveness typically hinges on large-scale supervised fine-tunin…

cs.LG2025

TRiCo: Triadic Game-Theoretic Co-Training for Robust Semi-Supervised Learning

Hongyang He, Xinyuan Song, Yangfan He +5

We introduce TRiCo, a novel triadic game-theoretic co-training framework that rethinks the structure of semi-supervised learning by incorporating a teacher, two students, and an ad…

cs.CV2025★ 1 cited

Contrastive Prompt Clustering for Weakly Supervised Semantic Segmentation

Wangyu Wu, Zhenhong Chen, Xiaowen Ma +6

Weakly Supervised Semantic Segmentation (WSSS) with image-level labels has gained attention for its cost-effectiveness. Most existing methods emphasize inter-class separation, ofte…

cs.CL2025

Graft: Integrating the Domain Knowledge via Efficient Parameter Synergy for MLLMs

Yang Dai, Jianxiang An, Tianwei Lin +6

Multimodal Large Language Models (MLLMs) have achieved success across various domains. However, their applicability tends to degrade when confronted with different types of data in…

cs.CV2025

EOC-Bench: Can MLLMs Identify, Recall, and Forecast Objects in an Egocentric World?

Yuqian Yuan, Ronghao Dang, Long Li +8

The emergence of multimodal large language models (MLLMs) has driven breakthroughs in egocentric vision applications. These applications necessitate persistent, context-aware under…

cs.CL2025

MoA: Heterogeneous Mixture of Adapters for Parameter-Efficient Fine-Tuning of Large Language Models

Jie Cao, Tianwei Lin, Bo Yuan +7

Recent studies integrate Low-Rank Adaptation (LoRA) and Mixture-of-Experts (MoE) to further enhance the performance of parameter-efficient fine-tuning (PEFT) methods in Large Langu…

cs.LG2025

HeartcareGPT: A Unified Multimodal ECG Suite for Dual Signal-Image Modeling and Understanding

Yihan Xie, Sijing Li, Tianwei Lin +9

Although electrocardiograms (ECG) play a dominant role in cardiovascular diagnosis and treatment, their intrinsic data forms and representational patterns pose significant challeng…

cs.CV2025★ 2 cited

EyecareGPT: Boosting Comprehensive Ophthalmology Understanding with Tailored Dataset, Benchmark and Model

Sijing Li, Tianwei Lin, Lingshuai Lin +9

Medical Large Vision-Language Models (Med-LVLMs) demonstrate significant potential in healthcare, but their reliance on general medical data and coarse-grained global visual unders…

cs.CV2025★ 7 cited

HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation

Tianwei Lin, Wenqiao Zhang, Sijing Li +12

We present HealthGPT, a powerful Medical Large Vision-Language Model (Med-LVLM) that integrates medical visual comprehension and generation capabilities within a unified autoregres…

cs.LG2023★ 23 cited

METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection

Jiaqi Zhu, Shaofeng Cai, Fang Deng +2

Real-time analytics and decision-making require online anomaly detection (OAD) to handle drifts in data streams efficiently and effectively. Unfortunately, existing approaches are…

cs.CV2023★ 1 cited

CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation

Wenqiao Zhang, Changshuo Liu, Can Cui +1

Semi-supervised domain adaptation (SSDA) adapts a learner to a new domain by effectively utilizing source domain data and a few labeled target samples. It is a practical yet under-…