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Found 7 papers, 4 papers with code
A Keyword Based Approach to Understanding the Overpenalization of Marginalized Groups by English Marginal Abuse Models on Twitter
Harmful content detection models tend to have higher false positive rates for content from marginalized groups.
Random Isn't Always Fair: Candidate Set Imbalance and Exposure Inequality in Recommender Systems
Traditionally, recommender systems operate by returning a user a set of items, ranked in order of estimated relevance to that user.
Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
However, we demonstrate that formalized fairness metrics and quantitative analysis on their own are insufficient for capturing the risk of representational harm in automatic cropping.
Language Models not just for Pre-training: Fast Online Neural Noisy Channel Modeling
Pre-training models on vast quantities of unlabeled data has emerged as an effective approach to improving accuracy on many NLP tasks.
Ranked #1 on
Machine Translation
on WMT2016 Romanian-English
(using extra training data)
Simple and Effective Noisy Channel Modeling for Neural Machine Translation
Previous work on neural noisy channel modeling relied on latent variable models that incrementally process the source and target sentence.
Facebook FAIR's WMT19 News Translation Task Submission
This paper describes Facebook FAIR's submission to the WMT19 shared news translation task.
Ranked #1 on
Machine Translation
on WMT2019 English-German
