299 citations · 983 across the 34 of their papers we have counts for
4 papers · 1 filter
Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers
Jieyu Zhao, Xuezhi Wang, Yao Qin +2
Large pre-trained language models have shown remarkable performance over the past few years. These models, however, sometimes learn superficial features from the dataset and cannot…
A Human-ML Collaboration Framework for Improving Video Content Reviews
Meghana Deodhar, Xiao Ma, Yixin Cai +3
We deal with the problem of localized in-video taxonomic human annotation in the video content moderation domain, where the goal is to identify video segments that violate granular…
Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations
Flavien Prost, Ben Packer, Jilin Chen +9
There has been a flurry of research in recent years on notions of fairness in ranking and recommender systems, particularly on how to evaluate if a recommender allocates exposure e…
Flexible text generation for counterfactual fairness probing
Zee Fryer, Vera Axelrod, Ben Packer +3
A common approach for testing fairness issues in text-based classifiers is through the use of counterfactuals: does the classifier output change if a sensitive attribute in the inp…