5 papers
Q-CueGraph: Query-Conditioned Visual Evidence Graphs for Multimodal Reasoning
Pengcheng Pan, Xinfang Zhang
Multimodal large language models (MLLMs) can miss fine details in a full image that they recognize in a closer view. Recovering this evidence requires deciding where to look and ho…
Head-Aware Visual Cropping: Enhancing Fine-Grained VQA with Attention-Guided Subimage
Junfei Xie, Peng Pan, Xulong Zhang
Multimodal Large Language Models (MLLMs) show strong performance in Visual Question Answering (VQA) but remain limited in fine-grained reasoning due to low-resolution inputs and no…
Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought
Tencent Hunyuan Team, Ao Liu, Botong Zhou +248
As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…
Establishing Rigorous and Cost-effective Clinical Trials for Artificial Intelligence Models
Wanling Gao, Yunyou Huang, Dandan Cui +22
A profound gap persists between artificial intelligence (AI) and clinical practice in medicine, primarily due to the lack of rigorous and cost-effective evaluation methodologies. S…
AI.vs.Clinician: Unveiling Intricate Interactions Between AI and Clinicians through an Open-Access Database
Wanling Gao, Yuan Liu, Zhuoming Yu +21
Artificial Intelligence (AI) plays a crucial role in medical field and has the potential to revolutionize healthcare practices. However, the success of AI models and their impacts…