Papers by Nicholas Derby
Large Language Models with Temporal Reasoning for Longitudinal Clinical Summarization and Prediction (2025.findings-emnlp)
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Maya Kruse, Shiyue Hu, Nicholas Derby, Yifu Wu, Samantha Stonbraker, Bingsheng Yao, Dakuo Wang, Elizabeth M. Goldberg, Yanjun Gao
| Challenge: | Recent advances in large language models have shown potential in clinical text summarization, but their ability to handle long patient trajectories with multi-modal data spread across time remains underexplored. |
| Approach: | They evaluate open-source large language models, their Retrieval Augmented Generation variants and chain-of-thought prompting on long-context clinical summarization and prediction. |
| Outcome: | The proposed models can synthesize structured and unstructured EHR data while reasoning over temporal coherence. |
Development of Community-Oriented Text-to-Speech Models for Māori ‘Avaiki Nui (Cook Islands Māori) (2024.lrec-main)
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Jesin James, Rolando Coto-Solano, Sally Akevai Nicholas, Joshua Zhu, Bovey Yu, Fuki Babasaki, Jenny Tyler Wang, Nicholas Derby
| Challenge: | Text-to-speech synthesis is used to transform text into a synthesized voice for a specific language. |
| Approach: | They describe the development of a text-to-speech system for Mori ‘Avaiki Nui (Cook Islands Mi) they used two approaches to train the system, the HMM-system MaryTTS and the deep learning system FastSpeech2 . |
| Outcome: | The proposed system is based on the HMM-system MaryTTS and the deep learning system FastSpeech2 . the ground truth voice had the highest quality, but the fastspeech 2 voice had a significantly higher quality than the MaryTTs synthesized recordings. |