3 papers
cs.CL2026
Uncertainty Drives Social Bias Changes in Quantized Large Language Models
Stanley Z. Hua, Sanae Lotfi, Irene Y. Chen
Post-training quantization reduces the computational cost of large language models but fundamentally alters their social biases in ways that aggregate metrics fail to capture. We p…
cs.LG2025
Privacy-Preserving Dataset Combination
Keren Fuentes, Mimee Xu, Irene Chen
Access to diverse, high-quality datasets is crucial for machine learning model performance, yet data sharing remains limited by privacy concerns and competitive interests, particul…
cs.LG2025
DataS^3: Dataset Subset Selection for Specialization
Neha Hulkund, Alaa Maalouf, Levi Cai +15
In many real-world machine learning (ML) applications (e.g. detecting broken bones in x-ray images, detecting species in camera traps), in practice models need to perform well on s…