98 citations · 102 across the 10 of their papers we have counts for
4 papers · 1 filter
Omitted Variable Bias in Language Models Under Distribution Shift
Victoria Lin, Louis-Philippe Morency, Eli Ben-Michael
Despite their impressive performance on a wide variety of tasks, modern language models remain susceptible to distribution shifts, exhibiting brittle behavior when evaluated on dat…
Optimizing Language Models for Human Preferences is a Causal Inference Problem
Victoria Lin, Eli Ben-Michael, Louis-Philippe Morency
As large language models (LLMs) see greater use in academic and commercial settings, there is increasing interest in methods that allow language models to generate texts aligned wi…
Counterfactual Augmentation for Multimodal Learning Under Presentation Bias
Victoria Lin, Louis-Philippe Morency, Dimitrios Dimitriadis +1
In real-world machine learning systems, labels are often derived from user behaviors that the system wishes to encourage. Over time, new models must be trained as new training exam…
SeedBERT: Recovering Annotator Rating Distributions from an Aggregated Label
Aneesha Sampath, Victoria Lin, Louis-Philippe Morency
Many machine learning tasks -- particularly those in affective computing -- are inherently subjective. When asked to classify facial expressions or to rate an individual's attracti…