13 citations · 17 across the 12 of their papers we have counts for
8 papers · 1 filter
HC-LLM: Historical-Constrained Large Language Models for Radiology Report Generation
Tengfei Liu, Jiapu Wang, Yongli Hu +5
Radiology report generation (RRG) models typically focus on individual exams, often overlooking the integration of historical visual or textual data, which is crucial for patient f…
Sitcom-Crafter: A Plot-Driven Human Motion Generation System in 3D Scenes
Jianqi Chen, Panwen Hu, Xiaojun Chang +3
Recent advancements in human motion synthesis have focused on specific types of motions, such as human-scene interaction, locomotion or human-human interaction, however, there is a…
Efficient Training of Large Vision Models via Advanced Automated Progressive Learning
Changlin Li, Jiawei Zhang, Sihao Lin +4
The rapid advancements in Large Vision Models (LVMs), such as Vision Transformers (ViTs) and diffusion models, have led to an increasing demand for computational resources, resulti…
Medical Report Generation Is A Multi-label Classification Problem
Yijian Fan, Zhenbang Yang, Rui Liu +2
Medical report generation is a critical task in healthcare that involves the automatic creation of detailed and accurate descriptions from medical images. Traditionally, this task…
Contrastive Learning with Counterfactual Explanations for Radiology Report Generation
Mingjie Li, Haokun Lin, Liang Qiu +4
Due to the common content of anatomy, radiology images with their corresponding reports exhibit high similarity. Such inherent data bias can predispose automatic report generation…
Teaching with Uncertainty: Unleashing the Potential of Knowledge Distillation in Object Detection
Junfei Yi, Jianxu Mao, Tengfei Liu +5
Knowledge distillation (KD) is a widely adopted and effective method for compressing models in object detection tasks. Particularly, feature-based distillation methods have shown r…
Predicting Genetic Mutation from Whole Slide Images via Biomedical-Linguistic Knowledge Enhanced Multi-label Classification
Gexin Huang, Chenfei Wu, Mingjie Li +6
Predicting genetic mutations from whole slide images is indispensable for cancer diagnosis. However, existing work training multiple binary classification models faces two challeng…
NavCoT: Boosting LLM-Based Vision-and-Language Navigation via Learning Disentangled Reasoning
Bingqian Lin, Yunshuang Nie, Ziming Wei +6
Vision-and-Language Navigation (VLN), as a crucial research problem of Embodied AI, requires an embodied agent to navigate through complex 3D environments following natural languag…