语言大模型 / LLM

Data distribution impacts the performance and generalisability of contrastive learning-based foundation models of electrocardiograms

Gul Rukh Khattak, Konstantinos Patlatzoglou, Joseph Barker, Libor Pastika, Boroumand Zeidaabadi, Ahmed El-Medany, Hesham Aggour, Yixiu Liang, Antonio H. Ribeiro, Jeffrey Annis, Antonio Luiz Pinho Ribeiro, Junbo Ge, Daniel B. Kramer, Jonathan W. Waks, Evan Brittain, Nicholas Peters, Fu Siong Ng, Arunashis Sau

专题命中 预训练与数据 ：foundation model(title,abstract)；pretraining(abstract)；分类 cs.AI、cs.LG

Comments Currently under review at npj Digital Medicine

Can Generative Geospatial Diffusion Models Excel as Discriminative Geospatial Foundation Models?

Yuru Jia, Valerio Marsocci, Ziyang Gong, Xue Yang, Maarten Vergauwen, Andrea Nascetti

机构 * KU Leuven（鲁汶大学） ； KTH（皇家理工学院） ； European Space Agency（欧洲航天局） ； Shanghai AI Lab（上海人工智能实验室） ； SJTU（上海交通大学） 纠错

专题命中 预训练与数据 ：foundation model(title,abstract)；pretraining(abstract)

Comments ICCV 2025, camera ready

Slaves to the Law of Large Numbers: An Asymptotic Equipartition Property for Perplexity in Generative Language Models

Tyler Bell, Avinash Mudireddy, Ivan Johnson-Eversoll, Soura Dasgupta, Raghu Mudumbai

机构 * University of Iowa（爱荷华大学） 纠错

专题命中 预训练与数据 ：language model(title,abstract)；分类 cs.CL、cs.AI

Scaling Arabic Medical Chatbots Using Synthetic Data: Enhancing Generative AI with Synthetic Patient Records

Abdulrahman Allam, Seif Ahmed, Ali Hamdi, Khaled Shaban

机构 * Dept. of Computer Science, Qatar University, Doha, Qatar（计算机科学系，卡塔尔大学，多哈） 纠错

专题命中 预训练与数据 ：large language model(abstract)；language model(abstract)；分类 cs.CL

Comments Accepted in AICCSA 2025

Segment Anything for Cell Tracking

Zhu Chen, Mert Edgü, Er Jin, Johannes Stegmaier

机构 * Institute of Imaging and Computer Vision, RWTH Aachen University, Germany（成像与计算机视觉研究所，亚琛工业大学，德国） 纠错

专题命中 预训练与数据 ：foundation model(abstract)