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- research-articleDecember 2024
Data augmented large language models for medical record generation: Data augmented large language...
AbstractWriting various medical records takes significant daily workload for physicians. Generative AI technique has the advantage in tasks of data-to-text generation and text summarization, and brings opportunities to reduce workload for physicians to ...
- ArticleAugust 2024
Stochastic Featurization for Active Learning
Trustworthy Artificial Intelligence for HealthcarePages 52–65https://doi.org/10.1007/978-3-031-67751-9_5AbstractIn recent years, the demand for high-quality data has intensified, particularly in the medical field where accurate data annotation is costly and critical. Active Learning (AL) has emerged as a pivotal approach in these scenarios, where selecting ...
- research-articleFebruary 2024
CoLAL: co-learning active learning for text classification
AAAI'24/IAAI'24/EAAI'24: Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial IntelligenceArticle No.: 1487, Pages 13337–13345https://doi.org/10.1609/aaai.v38i12.29235In the machine learning field, the challenge of effectively learning with limited data has become increasingly crucial. Active Learning (AL) algorithms play a significant role in this by enhancing model performance. We introduce a novel AL algorithm, ...
- research-articleOctober 2022
High-quality Task Division for Large-scale Entity Alignment
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge ManagementPages 1258–1268https://doi.org/10.1145/3511808.3557352Entity Alignment (EA) aims to match equivalent entities that refer to the same real-world objects and is a key step for Knowledge Graph (KG) fusion. Most neural EA models cannot be applied to large-scale real-life KGs due to their excessive consumption ...