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cs.CL2024
A Data-Centric Approach to Detecting and Mitigating Demographic Bias in Pediatric Mental Health Text: A Case Study in Anxiety Detection
Julia Ive, Paulina Bondaronek, Vishal Yadav +10
Introduction: Healthcare AI models often inherit biases from their training data. While efforts have primarily targeted bias in structured data, mental health heavily depends on un…
cs.CL2024
Safe Training with Sensitive In-domain Data: Leveraging Data Fragmentation To Mitigate Linkage Attacks
Mariia Ignashina, Julia Ive
Current text generation models are trained using real data which can potentially contain sensitive information, such as confidential patient information and the like. Under certain…