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Unsupervised Federated Domain Adaptation for Segmentation of MRI Images
Our approach enables the transfer of knowledge from several annotated source domains to adapt a model for effective use in an unannotated target domain.
HALO: An Ontology for Representing and Categorizing Hallucinations in Large Language Models
Recent progress in generative AI, including large language models (LLMs) like ChatGPT, has opened up significant opportunities in fields ranging from natural language processing to knowledge discovery and data mining.
Cost-Efficient Prompt Engineering for Unsupervised Entity Resolution
We use an extensive set of experimental results to show that an LLM like GPT3. 5 is viable for high-performing unsupervised ER, and interestingly, that more complicated and detailed (and hence, expensive) prompting methods do not necessarily outperform simpler approaches.
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