119 citations · 265 across the 13 of their papers we have counts for
4 papers · 1 filter
Ground-Truth, Whose Truth? -- Examining the Challenges with Annotating Toxic Text Datasets
Kofi Arhin, Ioana Baldini, Dennis Wei +2
The use of machine learning (ML)-based language models (LMs) to monitor content online is on the rise. For toxic text identification, task-specific fine-tuning of these models are…
Your fairness may vary: Pretrained language model fairness in toxic text classification
Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy +2
The popularity of pretrained language models in natural language processing systems calls for a careful evaluation of such models in down-stream tasks, which have a higher potentia…
Biomedical Interpretable Entity Representations
Diego Garcia-Olano, Yasumasa Onoe, Ioana Baldini +3
Pre-trained language models induce dense entity representations that offer strong performance on entity-centric NLP tasks, but such representations are not immediately interpretabl…
Automated Meta-Analysis: A Causal Learning Perspective
Lu Cheng, Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney +1
Meta-analysis is a systematic approach for understanding a phenomenon by analyzing the results of many previously published experimental studies. It is central to deriving conclusi…