Papers by Carissa Lin
Towards Fair and Efficient De-identification: Quantifying the Efficiency and Generalizability of De-identification Approaches (2026.findings-eacl)
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| Challenge: | a recent study has not examined their generalizability between formats, cultures, and genders. |
| Approach: | They evaluate large language models (LLMs) and small LLMs at clinical de-identification . they show that smaller models achieve comparable performance while substantially reducing inference cost . |
| Outcome: | The proposed models outperform larger models in de-identification tasks with limited data . the models can be fine-tuned with limited datasets to outperformed larger models . |