2 papers
cs.AI2026
The Consensus Trap: Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotation
Sheza Munir, Benjamin Mah, Krisha Kalsi +5
In machine learning, "ground truth" refers to the assumed correct labels used to train and evaluate models. However, the foundational "ground truth" paradigm rests on a positivisti…
cs.HC2026
Designing Around Stigma: Human-Centered LLMs for Menstrual Health
Amna Shahnawaz, Ayesha Shafique, Ding Wang +1
Menstrual health education (MHE) in Pakistan is constrained by cultural taboos and inadequate formal curricula, leaving women with few trusted resources to lean on. In response to…