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

7 citations · 10 across the 6 of their papers we have counts for

collaborators

14 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…