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Team: PULSAR at ProbSum 2023: PULSAR: Pre-training with Extracted Healthcare Terms for Summarising Patients' Problems and Data Augmentation with Black-box Large Language Models.

, , , , , , , , , and . BioNLP@ACL, page 503-509. Association for Computational Linguistics, (2023)

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EDU-level Extractive Summarization with Varying Summary Lengths., , , , , and . EACL (Findings), page 1610-1622. Association for Computational Linguistics, (2023)Construction Cost Index Prediction: A Visibility Graph Network Method., , , , and . IJCNN, page 1-6. IEEE, (2021)PULSAR: Pre-training with Extracted Healthcare Terms for Summarising Patients' Problems and Data Augmentation with Black-box Large Language Models., , , , , , , , , and . CoRR, (2023)EDU-level Extractive Summarization with Varying Summary Lengths., , , , , and . CoRR, (2022)On Cross-Domain Pre-Trained Language Models for Clinical Text Mining: How Do They Perform on Data-Constrained Fine-Tuning?, , , and . CoRR, (2022)The Benefits of Network Externality by Social Network Site., and . IIAI-AAI, page 242-246. IEEE Computer Society, (2014)UPANets: Learning from the Universal Pixel Attention Neworks., , , , , , and . Entropy, 24 (9): 1243 (2022)Exploring the Value of Pre-trained Language Models for Clinical Named Entity Recognition., , , and . IEEE Big Data, page 3660-3669. IEEE, (2023)PULSAR at MEDIQA-Sum 2023: Large Language Models Augmented by Synthetic Dialogue Convert Patient Dialogues to Medical Records., , , , , , , , , and 1 other author(s). CLEF (Working Notes), volume 3497 of CEUR Workshop Proceedings, page 1668-1679. CEUR-WS.org, (2023)UPANets: Learning from the Universal Pixel Attention Networks., , , , , , , and . CoRR, (2021)