3 citations · 6 across the 11 of their papers we have counts for
13 papers
Learning from Unverified Peers via Shared Residual Distillation
Feiyang Chen, Runze Ma, Zichen Wang +4
A language model can generate several solutions to the same problem, some leading to correct answers and others to incorrect ones. Many post-training methods turn these trajectorie…
TRACE: Tractable Routing Autoencoder for Clinical ECG
Shunbo Jia, Runze Ma, Haonan Lyu +3
Deep learning has advanced automated electrocardiogram (ECG) diagnosis, but the field's most accurate models, foundation models pretrained on millions of recordings, are not decisi…
Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design
Xiaoliang Shi, Zichen Wang, Runze Ma +2
Antibodies are essential proteins that play a central role in immune recognition by binding specific antigen molecules. Although recent protein language models have enabled progres…
REALM: Retrospective Encoder Alignment for LFP Modeling
Peicheng Wu, Zhenyu Bu, Runze Ma +1
Spike activity has been the dominant neural signal for behavior decoding because its high spatiotemporal resolution supports accurate decoding. However, as intracortical brain-comp…
LiteMedCoT-VL: Parameter-Efficient Adaptation for Medical Visual Question Answering
Runze Ma, Shunbo Jia, Haonan Lyu +2
The reasoning gap between large and compact vision-language models (VLMs) limits the deployment of medical AI on portable clinical devices. Compact VLMs of 2-4B parameters can run…
BEAT-Net: Injecting Biomimetic Spatio-Temporal Priors for Interpretable ECG Diagnosis
Runze Ma, Haonan Lyu, Caizhi Liao +5
Automated electrocardiogram diagnosis using deep learning remains limited by signal-agnostic representations that treat multi-lead recordings as undifferentiated time-series or ima…
VCWorld: A Biological World Model for Virtual Cell Simulation
Zhijian Wei, Runze Ma, Zichen Wang +3
Virtual cell modeling aims to predict cellular responses to perturbations. Existing virtual cell models rely heavily on large-scale single-cell datasets, learning explicit mappings…
NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction
Zhongmin Li, Runze Ma, Jiahao Tan +2
Nucleotide sequence variation can induce significant shifts in functional fitness. Recent nucleotide foundation models promise to predict such fitness effects directly from sequenc…
ODesign: A World Model for Biomolecular Interaction Design
Odin Zhang, Xujun Zhang, Haitao Lin +34
Biomolecular interactions underpin almost all biological processes, and their rational design is central to programming new biological functions. Generative AI models have emerged…
Fitness aligned structural modeling enables scalable virtual screening with AuroBind
Zhongyue Zhang, Jiahua Rao, Jie Zhong +22
Most human proteins remain undrugged, over 96% of human proteins remain unexploited by approved therapeutics. While structure-based virtual screening promises to expand the druggab…
An Energy-Adaptive Elastic Equivariant Transformer Framework for Protein Structure Representation
Zhongyue Zhang, Runze Ma, Yanjie Huang +1
Structure-informed protein representation learning is essential for effective protein function annotation and \textit{de novo} design. However, the presence of inherent noise in bo…
RiboFlow: Conditional De Novo RNA Co-Design via Synergistic Flow Matching
Runze Ma, Zhongyue Zhang, Zichen Wang +4
Ribonucleic acid (RNA) binds to molecules to achieve specific biological functions. While generative models are advancing biomolecule design, existing methods for designing RNA tha…
Stacking-Enhanced Bagging Ensemble Learning for Breast Cancer Classification with CNN
Peihceng Wu, Runze Ma, Teoh Teik Toe
This paper proposes a CNN classification network based on Bagging and stacking ensemble learning methods for breast cancer classification. The model was trained and tested on the p…