13 citations · 26 across the 18 of their papers we have counts for
19 papers
CARE: Causally-Aligned Reasoning Exploration for Medical Large Language Models
Yucheng Zhou, Peng Luo, Qianning Wang +2
Large Language Models (LLMs) have shown strong potential for medical reasoning, yet the scarcity and cost of expert-annotated data constrain their progress. While reinforcement lea…
Compatibility-Aware Dynamic Fine-Tuning for Large Language Models
Yucheng Zhou, Junwei Sheng, Qianning Wang +1
Supervised Fine-Tuning (SFT) is the predominant paradigm for aligning large language models (LLMs), yet it suffers from optimization instability and limited generalization. Recent…
World Models Meet Language Models: On the Complementarity of Concrete and Abstract Reasoning
Yucheng Zhou, Wei Tao, Yiwen Guo +1
World models and multimodal large language models (MLLMs) provide complementary capabilities for predicting future outcomes from static visual observations. World models can genera…
CogOmniControl: Reasoning-Driven Controllable Video Generation via Creative Intent Cognition
Hongji Yang, Songlian Li, Yucheng Zhou +4
Recent diffusion models achieve strong photorealism and fluency in video generation, yet remain fragile under abstract, sparse or complex conditions, leading to poor performance in…
Multimodal Large Language Models for Multi-Subject In-Context Image Generation
Yucheng Zhou, Dubing Chen, Huan Zheng +1
Recent advances in text-to-image (T2I) generation have enabled visually coherent image synthesis from descriptions, but generating images containing multiple given subjects remains…
Accelerating Training of Autoregressive Video Generation Models via Local Optimization with Representation Continuity
Yucheng Zhou, Jianbing Shen
Autoregressive models have shown superior performance and efficiency in image generation, but remain constrained by high computational costs and prolonged training times in video g…
From Broad Exploration to Stable Synthesis: Entropy-Guided Optimization for Autoregressive Image Generation
Han Song, Yucheng Zhou, Jianbing Shen +1
Combining Chain-of-Thought (CoT) with Reinforcement Learning (RL) improves text-to-image (T2I) generation, yet the underlying interaction between CoT's exploration and RL's optimiz…
HanMoVLM: Large Vision-Language Models for Professional Artistic Painting Evaluation
Hongji Yang, Yucheng Zhou, Wencheng Han +3
While Large Vision-Language Models (VLMs) demonstrate impressive general visual capabilities, they remain artistically blind and unable to offer professional evaluation of artworks…
Clinical Cognition Alignment for Gastrointestinal Diagnosis with Multimodal LLMs
Huan Zheng, Yucheng Zhou, Tianyi Yan +6
Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in medical image analysis. However, their application in gastrointestinal endoscopy is currently hin…
Condition Errors Refinement in Autoregressive Image Generation with Diffusion Loss
Yucheng Zhou, Hao Li, Jianbing Shen
Recent studies have explored autoregressive models for image generation, with promising results, and have combined diffusion models with autoregressive frameworks to optimize image…
Sim4Seg: Boosting Multimodal Multi-disease Medical Diagnosis Segmentation with Region-Aware Vision-Language Similarity Masks
Lingran Song, Yucheng Zhou, Jianbing Shen
Despite significant progress in pixel-level medical image analysis, existing medical image segmentation models rarely explore medical segmentation and diagnosis tasks jointly. Howe…
MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration
Yucheng Zhou, Lingran Song, Jianbing Shen
Recent advancements in medical Large Language Models (LLMs) have showcased their powerful reasoning and diagnostic capabilities. Despite their success, current unified multimodal m…
Self-Rewarding Large Vision-Language Models for Optimizing Prompts in Text-to-Image Generation
Hongji Yang, Yucheng Zhou, Wencheng Han +1
Text-to-image models are powerful for producing high-quality images based on given text prompts, but crafting these prompts often requires specialized vocabulary. To address this,…
DC-ControlNet: Decoupling Inter- and Intra-Element Conditions in Image Generation with Diffusion Models
Hongji Yang, Wencheng Han, Yucheng Zhou +1
In this paper, we introduce DC (Decouple)-ControlNet, a highly flexible and precisely controllable framework for multi-condition image generation. The core idea behind DC-ControlNe…
Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback
Yucheng Zhou, Lingran Song, Jianbing Shen
Existing Medical Large Vision-Language Models (Med-LVLMs), encapsulating extensive medical knowledge, demonstrate excellent capabilities in understanding medical images. However, t…
Diffusion Model with Representation Alignment for Protein Inverse Folding
Chenglin Wang, Yucheng Zhou, Zijie Zhai +2
Protein inverse folding is a fundamental problem in bioinformatics, aiming to recover the amino acid sequences from a given protein backbone structure. Despite the success of exist…
Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models
Yucheng Zhou, Zhi Rao, Jun Wan +1
Large Vision-Language Models (LVLMs) excel in cross-model tasks but experience performance declines in long-context reasoning due to overreliance on textual information and reduced…
Visual In-Context Learning for Large Vision-Language Models
Yucheng Zhou, Xiang Li, Qianning Wang +1
In Large Visual Language Models (LVLMs), the efficacy of In-Context Learning (ICL) remains limited by challenges in cross-modal interactions and representation disparities. To over…
Thread of Thought Unraveling Chaotic Contexts
Yucheng Zhou, Xiubo Geng, Tao Shen +4
Large Language Models (LLMs) have ushered in a transformative era in the field of natural language processing, excelling in tasks related to text comprehension and generation. Neve…