4 citations · 5 across the 14 of their papers we have counts for
14 papers
MicroWorld: Empowering Multimodal Large Language Models to Bridge the Microscopic Domain Gap with Multimodal Attributed Property Graph
Manyu Li, Ruian He, Chenxi Ma +2
Multimodal large language models (MLLMs) show remarkable potential for scientific reasoning, yet their performance in specialized domains such as microscopy remains limited by the…
Equivariant Evidential Deep Learning for Interatomic Potentials
Zhongyao Wang, Taoyong Cui, Jiawen Zou +5
Uncertainty quantification (UQ) is critical for assessing the reliability of machine learning interatomic potentials (MLIPs) in molecular dynamics (MD) simulations, identifying ext…
Tabular Incremental Inference
Xinda Chen, Zhen Xing, Hanyu Zhang +2
Tabular data is a fundamental form of data structure. The evolution of table analysis tools reflects humanity's continuous progress in data acquisition, management, and processing.…
MicroVQA++: High-Quality Microscopy Reasoning Dataset with Weakly Supervised Graphs for Multimodal Large Language Model
Manyu Li, Ruian He, Chenxi Ma +2
Multimodal Large Language Models are increasingly applied to biomedical imaging, yet scientific reasoning for microscopy remains limited by the scarcity of large-scale, high-qualit…
MM-Skin: Enhancing Dermatology Vision-Language Model with an Image-Text Dataset Derived from Textbooks
Wenqi Zeng, Yuqi Sun, Chenxi Ma +2
Medical vision-language models (VLMs) have shown promise as clinical assistants across various medical fields. However, specialized dermatology VLM capable of delivering profession…
Unifying Segment Anything in Microscopy with Vision-Language Knowledge
Manyu Li, Ruian He, Zixian Zhang +3
Accurate segmentation of regions of interest in biomedical images holds substantial value in image analysis. Although several foundation models for biomedical segmentation have cur…
Scaling Laws for Data-Efficient Visual Transfer Learning
Wenxuan Yang, Qingqu Wei, Chenxi Ma +2
Current scaling laws for visual AI models focus predominantly on large-scale pretraining, leaving a critical gap in understanding how performance scales for data-constrained downst…
Non-Uniform Class-Wise Coreset Selection for Vision Model Fine-tuning
Hanyu Zhang, Zhen Xing, Ruian He +4
Coreset selection aims to identify a small yet highly informative subset of data, thereby enabling more efficient model training while reducing storage overhead. Recently, this cap…
FacialFlowNet: Advancing Facial Optical Flow Estimation with a Diverse Dataset and a Decomposed Model
Jianzhi Lu, Ruian He, Shili Zhou +2
Facial movements play a crucial role in conveying altitude and intentions, and facial optical flow provides a dynamic and detailed representation of it. However, the scarcity of da…
A Self-Supervised Paradigm for Data-Efficient Medical Foundation Model Pre-training: V-information Optimization Framework
Wenxuan Yang, Hanyu Zhang, Weimin Tan +2
Self-supervised pre-training medical foundation models on large-scale datasets demonstrate exceptional performance. Recent research challenges this common paradigm by introducing d…
Addressing Imbalance for Class Incremental Learning in Medical Image Classification
Xuze Hao, Wenqian Ni, Xuhao Jiang +2
Deep convolutional neural networks have made significant breakthroughs in medical image classification, under the assumption that training samples from all classes are simultaneous…
Context-Aware Iteration Policy Network for Efficient Optical Flow Estimation
Ri Cheng, Ruian He, Xuhao Jiang +3
Existing recurrent optical flow estimation networks are computationally expensive since they use a fixed large number of iterations to update the flow field for each sample. An eff…
A Medical Data-Effective Learning Benchmark for Highly Efficient Pre-training of Foundation Models
Wenxuan Yang, Weimin Tan, Yuqi Sun +1
Foundation models, pre-trained on massive datasets, have achieved unprecedented generalizability. However, is it truly necessary to involve such vast amounts of data in pre-trainin…
Low-latency Space-time Supersampling for Real-time Rendering
Ruian He, Shili Zhou, Yuqi Sun +3
With the rise of real-time rendering and the evolution of display devices, there is a growing demand for post-processing methods that offer high-resolution content in a high frame…