443 citations · 554 across the 16 of their papers we have counts for
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cs.LG2026
Correctness-Optimized Residual Activation Lens (CORAL): Transferrable and Calibration-Aware Inference-Time Steering
Miranda Muqing Miao, Young-Min Cho, Lyle Ungar
Large language models (LLMs) exhibit persistent miscalibration, especially after instruction tuning and preference alignment. Modified training objectives can improve calibration,…
cs.LG2020★ 14 cited
Generalized SHAP: Generating multiple types of explanations in machine learning
Dillon Bowen, Lyle Ungar
Many important questions about a model cannot be answered just by explaining how much each feature contributes to its output. To answer a broader set of questions, we generalize a…
cs.LG2009★ 1 cited
Transfer Learning Using Feature Selection
Paramveer S. Dhillon, Dean Foster, Lyle Ungar
We present three related ways of using Transfer Learning to improve feature selection. The three methods address different problems, and hence share different kinds of information…