3 papers
cs.LG2026
Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding
Xiao Xiang, David Restrepo, Hyewon Jeong +2
Electronic health records (EHR) arrive masked. Clinicians order measurements selectively, and any patient table thus contains only a subset of the values that characterize the unde…
cs.CY2026
Implicit Bias in LLMs for Transgender Populations
Micaela Hirsch, Marina Elichiry, Blas Radi +6
Large language models (LLMs) have been shown to exhibit biases against LGBTQ+ populations. While safety training may lessen explicit expressions of bias, previous work has shown th…
cs.HC2025
Performance Gains of LLMs With Humans in a World of LLMs Versus Humans
Lucas McCullum, Pelagie Ami Agassi, Leo Anthony Celi +6
Currently, a considerable research effort is devoted to comparing LLMs to a group of human experts, where the term "expert" is often ill-defined or variable, at best, in a state of…