Search Results for author: Kyra Yee

Found 8 papers, 4 papers with code

Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms

no code implementations15 Jul 2023 Organizers Of QueerInAI, Nathan Dennler, Anaelia Ovalle, Ashwin Singh, Luca Soldaini, Arjun Subramonian, Huy Tu, William Agnew, Avijit Ghosh, Kyra Yee, Irene Font Peradejordi, Zeerak Talat, Mayra Russo, Jess de Jesus de Pinho Pinhal

However, these auditing processes have been criticized for their failure to integrate the knowledge of marginalized communities and consider the power dynamics between auditors and the communities.

Random Isn't Always Fair: Candidate Set Imbalance and Exposure Inequality in Recommender Systems

no code implementations12 Sep 2022 Amanda Bower, Kristian Lum, Tomo Lazovich, Kyra Yee, Luca Belli

Traditionally, recommender systems operate by returning a user a set of items, ranked in order of estimated relevance to that user.

Fairness Recommendation Systems

Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

3 code implementations18 May 2021 Kyra Yee, Uthaipon Tantipongpipat, Shubhanshu Mishra

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.

Fairness Image Cropping

Language Models not just for Pre-training: Fast Online Neural Noisy Channel Modeling

1 code implementation WMT (EMNLP) 2020 Shruti Bhosale, Kyra Yee, Sergey Edunov, Michael Auli

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)

Machine Translation Translation

Simple and Effective Noisy Channel Modeling for Neural Machine Translation

1 code implementation IJCNLP 2019 Kyra Yee, Nathan Ng, Yann N. Dauphin, Michael Auli

Previous work on neural noisy channel modeling relied on latent variable models that incrementally process the source and target sentence.

Machine Translation Translation

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