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cs.CL2025
debiaSAE: Benchmarking and Mitigating Vision-Language Model Bias
Kuleen Sasse, Shan Chen, Jackson Pond +2
As Vision Language Models (VLMs) gain widespread use, their fairness remains under-explored. In this paper, we analyze demographic biases across five models and six datasets. We fi…
cs.CL2024
Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks
Jack Gallifant, Shan Chen, Pedro Moreira +7
Medical knowledge is context-dependent and requires consistent reasoning across various natural language expressions of semantically equivalent phrases. This is particularly crucia…