2.2k citations · 6.2k across the 59 of their papers we have counts for
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Continual Contrastive Finetuning Improves Low-Resource Relation Extraction
Wenxuan Zhou, Sheng Zhang, Tristan Naumann +2
Relation extraction (RE), which has relied on structurally annotated corpora for model training, has been particularly challenging in low-resource scenarios and domains. Recent lit…
The Fourth Catalog of Active Galactic Nuclei Detected by the Fermi Large Area Telescope -- Data Release 3
LAT collaboration, Marco Ajello, Luca Baldini +100
An incremental version of the fourth catalog of active galactic nuclei (AGNs) detected by the Fermi-Large Area Telescope is presented. This version (4LAC-DR3) derives from the thir…
BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining
Renqian Luo, Liai Sun, Yingce Xia +4
Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main…
Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning
Sheng Zhang, Hao Cheng, Jianfeng Gao +1
We present a bi-encoder framework for named entity recognition (NER), which applies contrastive learning to map candidate text spans and entity types into the same vector represent…
Making the Most of Text Semantics to Improve Biomedical Vision--Language Processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur +9
Multi-modal data abounds in biomedicine, such as radiology images and reports. Interpreting this data at scale is essential for improving clinical care and accelerating clinical re…
Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision
Sam Preston, Mu Wei, Rajesh Rao +11
Objective: The majority of detailed patient information in real-world data (RWD) is only consistently available in free-text clinical documents. Manual curation is expensive and ti…