94 citations · 206 across the 66 of their papers we have counts for
30 papers · 1 filter
Towards Unified Molecule-Enhanced Pathology Image Representation Learning via Integrating Spatial Transcriptomics
Minghao Han, Dingkang Yang, Jiabei Cheng +4
Recent advancements in multimodal pre-training models have significantly advanced computational pathology. However, current approaches predominantly rely on visual-language models,…
Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning
Mingcheng Li, Dingkang Yang, Yang Liu +11
Multimodal Sentiment Analysis (MSA) is an important research area that aims to understand and recognize human sentiment through multiple modalities. The complementary information p…
MedAide: Information Fusion and Anatomy of Medical Intents via LLM-based Agent Collaboration
Dingkang Yang, Jinjie Wei, Mingcheng Li +8
In healthcare intelligence, the ability to fuse heterogeneous, multi-intent information from diverse clinical sources is fundamental to building reliable decision-making systems. L…
PhysHand: A Hand Simulation Model with Physiological Geometry, Physical Deformation, and Accurate Contact Handling
Mingyang Sun, Dongliang Kou, Ruisheng Yuan +7
In virtual Hand-Object Interaction (HOI) scenarios, the authenticity of the hand's deformation is important to immersive experience, such as natural manipulation or tactile feedbac…
MaskBEV: Towards A Unified Framework for BEV Detection and Map Segmentation
Xiao Zhao, Xukun Zhang, Dingkang Yang +4
Accurate and robust multimodal multi-task perception is crucial for modern autonomous driving systems. However, current multimodal perception research follows independent paradigms…
HybridOcc: NeRF Enhanced Transformer-based Multi-Camera 3D Occupancy Prediction
Xiao Zhao, Bo Chen, Mingyang Sun +7
Vision-based 3D semantic scene completion (SSC) describes autonomous driving scenes through 3D volume representations. However, the occlusion of invisible voxels by scene surfaces…
Faster Diffusion Action Segmentation
Shuaibing Wang, Shunli Wang, Mingcheng Li +4
Temporal Action Segmentation (TAS) is an essential task in video analysis, aiming to segment and classify continuous frames into distinct action segments. However, the ambiguous bo…
Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators
Dingkang Yang, Dongling Xiao, Jinjie Wei +4
Despite their remarkable capabilities, Large Language Models (LLMs) are prone to generate responses that contradict verifiable facts, i.e., unfaithful hallucination content. Existi…
MSCPT: Few-shot Whole Slide Image Classification with Multi-scale and Context-focused Prompt Tuning
Minghao Han, Linhao Qu, Dingkang Yang +3
Multiple instance learning (MIL) has become a standard paradigm for the weakly supervised classification of whole slide images (WSIs). However, this paradigm relies on using a larg…
Large Vision-Language Models as Emotion Recognizers in Context Awareness
Yuxuan Lei, Dingkang Yang, Zhaoyu Chen +3
Context-aware emotion recognition (CAER) is a complex and significant task that requires perceiving emotions from various contextual cues. Previous approaches primarily focus on de…
Pathology-knowledge Enhanced Multi-instance Prompt Learning for Few-shot Whole Slide Image Classification
Linhao Qu, Dingkang Yang, Dan Huang +4
Current multi-instance learning algorithms for pathology image analysis often require a substantial number of Whole Slide Images for effective training but exhibit suboptimal perfo…
Towards Context-Aware Emotion Recognition Debiasing from a Causal Demystification Perspective via De-confounded Training
Dingkang Yang, Kun Yang, Haopeng Kuang +3
Understanding emotions from diverse contexts has received widespread attention in computer vision communities. The core philosophy of Context-Aware Emotion Recognition (CAER) is to…
Self-Cooperation Knowledge Distillation for Novel Class Discovery
Yuzheng Wang, Zhaoyu Chen, Dingkang Yang +2
Novel Class Discovery (NCD) aims to discover unknown and novel classes in an unlabeled set by leveraging knowledge already learned about known classes. Existing works focus on inst…
Asynchronous Multimodal Video Sequence Fusion via Learning Modality-Exclusive and -Agnostic Representations
Dingkang Yang, Mingcheng Li, Linhao Qu +4
Understanding human intentions (e.g., emotions) from videos has received considerable attention recently. Video streams generally constitute a blend of temporal data stemming from…
Skip and Skip: Segmenting Medical Images with Prompts
Jiawei Chen, Dingkang Yang, Yuxuan Lei +1
Most medical image lesion segmentation methods rely on hand-crafted accurate annotations of the original image for supervised learning. Recently, a series of weakly supervised or u…
CoMT: Chain-of-Medical-Thought Reduces Hallucination in Medical Report Generation
Yue Jiang, Jiawei Chen, Dingkang Yang +5
Automatic medical report generation (MRG), which possesses significant research value as it can aid radiologists in clinical diagnosis and report composition, has garnered increasi…
Detecting and Evaluating Medical Hallucinations in Large Vision Language Models
Jiawei Chen, Dingkang Yang, Tong Wu +7
Large Vision Language Models (LVLMs) are increasingly integral to healthcare applications, including medical visual question answering and imaging report generation. While these mo…
PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications
Dingkang Yang, Jinjie Wei, Dongling Xiao +11
Developing intelligent pediatric consultation systems offers promising prospects for improving diagnostic efficiency, especially in China, where healthcare resources are scarce. De…
SMCD: High Realism Motion Style Transfer via Mamba-based Diffusion
Ziyun Qian, Zeyu Xiao, Xingliang Jin +6
Motion style transfer is a significant research direction in the field of computer vision, enabling virtual digital humans to rapidly switch between different styles of the same mo…
Multi-Scale Heterogeneity-Aware Hypergraph Representation for Histopathology Whole Slide Images
Minghao Han, Xukun Zhang, Dingkang Yang +4
Survival prediction is a complex ordinal regression task that aims to predict the survival coefficient ranking among a cohort of patients, typically achieved by analyzing patients'…
Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models
Jiawei Chen, Dingkang Yang, Yue Jiang +4
In the realm of Medical Visual Language Models (Med-VLMs), the quest for universal efficient fine-tuning mechanisms remains paramount, especially given researchers in interdiscipli…
Correlation-Decoupled Knowledge Distillation for Multimodal Sentiment Analysis with Incomplete Modalities
Mingcheng Li, Dingkang Yang, Xiao Zhao +7
Multimodal sentiment analysis (MSA) aims to understand human sentiment through multimodal data. Most MSA efforts are based on the assumption of modality completeness. However, in r…
De-confounded Data-free Knowledge Distillation for Handling Distribution Shifts
Yuzheng Wang, Dingkang Yang, Zhaoyu Chen +5
Data-Free Knowledge Distillation (DFKD) is a promising task to train high-performance small models to enhance actual deployment without relying on the original training data. Exist…
Can LLMs' Tuning Methods Work in Medical Multimodal Domain?
Jiawei Chen, Yue Jiang, Dingkang Yang +4
While Large Language Models (LLMs) excel in world knowledge understanding, adapting them to specific subfields requires precise adjustments. Due to the model's vast scale, traditio…