Lorenzo Jaime Yu Flores — accepted AI-conference papers

2025

Improving the Calibration of Confidence Scores in Text Generation Using the Output Distribution’s Characteristics

Lorenzo Jaime Yu Flores, Ori Ernst, Jackie CK Cheung

ACL 2025short

Well-calibrated model confidence scores can improve the usefulness of text generation models. For example, users can be prompted to review predictions with low confidence scores, to prevent models from returning bad or potentially dangerous predictions. However, confidence metrics are not always wel…

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2023

Medical Text Simplification: Optimizing for Readability with Unlikelihood Training and Reranked Beam Search Decoding

Lorenzo Jaime Yu Flores, Heyuan Huang, Kejian Shi, Sophie Chheang, Arman Cohan

EMNLP 2023short findings

Text simplification has emerged as an increasingly useful application of AI for bridging the communication gap in specialized fields such as medicine, where the lexicon is often dominated by technical jargon and complex constructs. Despite notable progress, methods in medical simplification sometime…

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