5 citations · 13 across the 16 of their papers we have counts for
17 papers
Improving scDiffusion with Sparsity-Biased Classifier-Free Guidance
Yu Song, Hao Sun, Ikuko Nishikawa +1
Single-cell RNA sequencing (scRNA-seq) has become an essential tool in modern cellular biology, and generating accurate synthetic scRNA-seq data is becoming increasingly important.…
SAM+D: Parameter-Efficient Dimensional Lifting of SAM-Family Models via Depth-Routed LoRA and Depth Shifting
Yu Song, Hao Sun, Shiyu Teng +2
Existing methods for adapting 2D foundation models such as SAM to 3D volumes either process slices independently---ignoring inter-slice context---or require substantial architectur…
MIRTH: Mutual-Information Reasoning with Temporal Hubs for Vision-Language-Action Agents
Hao Sun, Yu Song, Shiyu Teng +2
VLA models have emerged as a powerful paradigm for transferring semantic knowledge from web-scale data to physical robotic control. However, current single-frame architectures suff…
Drag within Prior Distribution: Text-Conditioned Point-Based Image Editing within Distribution Constraints
Haoyang Hu, Masataka Seo, Yen-Wei Chen
Diffusion-based point editing methods have gained significant traction in image editing tasks due to their ability to manipulate image semantics and fine details by applying locali…
EPIC: Efficient Prompt Interaction for Text-Image Classification
Xinyao Yu, Hao Sun, Zeyu Ling +5
In recent years, large-scale pre-trained multimodal models (LMMs) generally emerge to integrate the vision and language modalities, achieving considerable success in multimodal tas…
SemSim: Revisiting Weak-to-Strong Consistency from a Semantic Similarity Perspective for Semi-supervised Medical Image Segmentation
Shiao Xie, Hongyi Wang, Ziwei Niu +4
Semi-supervised learning (SSL) for medical image segmentation is a challenging yet highly practical task, which reduces reliance on large-scale labeled dataset by leveraging unlabe…
Deep Self-Cleansing for Medical Image Segmentation with Noisy Labels
Jiahua Dong, Yue Zhang, Qiuli Wang +7
Medical image segmentation is crucial in the field of medical imaging, aiding in disease diagnosis and surgical planning. Most established segmentation methods rely on supervised d…
M2OST: Many-to-one Regression for Predicting Spatial Transcriptomics from Digital Pathology Images
Hongyi Wang, Xiuju Du, Jing Liu +3
The advancement of Spatial Transcriptomics (ST) has facilitated the spatially-aware profiling of gene expressions based on histopathology images. Although ST data offers valuable i…
Language-guided Scale-aware MedSegmentor for Lesion Segmentation in Medical Imaging
Shuyi Ouyang, Jinyang Zhang, Xiangye Lin +4
In clinical practice, segmenting specific lesions based on the needs of physicians can significantly enhance diagnostic accuracy and treatment efficiency. However, conventional les…
One Framework to Rule Them All: Unifying Multimodal Tasks with LLM Neural-Tuning
Hao Sun, Yu Song, Jiaqing Liu +3
Large-scale models have exhibited remarkable capabilities across diverse domains, including automated medical services and intelligent customer support. However, as most large mode…
HSVLT: Hierarchical Scale-Aware Vision-Language Transformer for Multi-Label Image Classification
Shuyi Ouyang, Hongyi Wang, Ziwei Niu +6
The task of multi-label image classification involves recognizing multiple objects within a single image. Considering both valuable semantic information contained in the labels and…
Multimodal Infusion Tuning for Large Models
Hao Sun, Yu Song, Xinyao Yu +3
Recent advancements in large-scale models have showcased remarkable generalization capabilities in various tasks. However, integrating multimodal processing into these models prese…
A Survey on Domain Generalization for Medical Image Analysis
Ziwei Niu, Shuyi Ouyang, Shiao Xie +2
Medical Image Analysis (MedIA) has emerged as a crucial tool in computer-aided diagnosis systems, particularly with the advancement of deep learning (DL) in recent years. However,…
Memory-Inspired Temporal Prompt Interaction for Text-Image Classification
Xinyao Yu, Hao Sun, Ziwei Niu +4
In recent years, large-scale pre-trained multimodal models (LMM) generally emerge to integrate the vision and language modalities, achieving considerable success in various natural…
M2ORT: Many-To-One Regression Transformer for Spatial Transcriptomics Prediction from Histopathology Images
Hongyi Wang, Xiuju Du, Jing Liu +3
The advancement of Spatial Transcriptomics (ST) has facilitated the spatially-aware profiling of gene expressions based on histopathology images. Although ST data offers valuable i…
Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Bag-Level Classifier is a Good Instance-Level Teacher
Hongyi Wang, Luyang Luo, Fang Wang +5
Multiple Instance Learning (MIL) has demonstrated promise in Whole Slide Image (WSI) classification. However, a major challenge persists due to the high computational cost associat…
Modality-invariant and Specific Prompting for Multimodal Human Perception Understanding
Hao Sun, Ziwei Niu, Xinyao Yu +3
Understanding human perceptions presents a formidable multimodal challenge for computers, encompassing aspects such as sentiment tendencies and sense of humor. While various method…