2 citations · 3 across the 5 of their papers we have counts for
5 papers
Predicting Juror Predisposition Using Machine Learning: A Comparative Study of Human and Algorithmic Jury Selection
Ashwin Murthy, Ramesh Krishnamaneni, Sean Chacon +2
Prior studies on the effectiveness of professional jury consultants in predicting juror proclivities have yielded mixed results, and few have rigorously evaluated consultant perfor…
GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languages
Spencer Rarrick, Ranjita Naik, Sundar Poudel +1
Neural Machine Translation (NMT) continues to improve in quality and adoption, yet the inadvertent perpetuation of gender bias remains a significant concern. Despite numerous studi…
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran +5
We study the ability of state-of-the art models to answer constraint satisfaction queries for information retrieval (e.g., 'a list of ice cream shops in San Diego'). In the past, s…
Social Biases through the Text-to-Image Generation Lens
Ranjita Naik, Besmira Nushi
Text-to-Image (T2I) generation is enabling new applications that support creators, designers, and general end users of productivity software by generating illustrative content with…
GATE: A Challenge Set for Gender-Ambiguous Translation Examples
Spencer Rarrick, Ranjita Naik, Varun Mathur +2
Although recent years have brought significant progress in improving translation of unambiguously gendered sentences, translation of ambiguously gendered input remains relatively u…