most citedBioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine

30 citations · 85 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20241 cited

RCooper: A Real-world Large-scale Dataset for Roadside Cooperative Perception

Ruiyang Hao, Siqi Fan, Yingru Dai +7

The value of roadside perception, which could extend the boundaries of autonomous driving and traffic management, has gradually become more prominent and acknowledged in recent yea…

cs.CV202310 cited

Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection

Haibao Yu, Yingjuan Tang, Enze Xie +3

Cooperatively utilizing both ego-vehicle and infrastructure sensor data can significantly enhance autonomous driving perception abilities. However, the uncertain temporal asynchron…

cs.CE202330 cited

BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine

Yizhen Luo, Jiahuan Zhang, Siqi Fan +4

Foundation models (FMs) have exhibited remarkable performance across a wide range of downstream tasks in many domains. Nevertheless, general-purpose FMs often face challenges when…

q-bio.BM202312 cited

MolFM: A Multimodal Molecular Foundation Model

Yizhen Luo, Kai Yang, Massimo Hong +2

Molecular knowledge resides within three different modalities of information sources: molecular structures, biomedical documents, and knowledge bases. Effective incorporation of mo…

cs.CE202314 cited

Large-Scale Cell Representation Learning via Divide-and-Conquer Contrastive Learning

Suyuan Zhao, Jiahuan Zhang, Zaiqing Nie

Single-cell RNA sequencing (scRNA-seq) data is a potent tool for comprehending the "language of life" and can provide insights into various downstream biomedical tasks. Large-scale…

cs.CV20234 cited

V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecasting

Haibao Yu, Wenxian Yang, Hongzhi Ruan +11

Utilizing infrastructure and vehicle-side information to track and forecast the behaviors of surrounding traffic participants can significantly improve decision-making and safety i…