Chandler May

Adapting Coreference Resolution Models through Active Learning

2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Neural coreference resolution models trained on one dataset may not transfer to new, lowresource domains. Active learning mitigates this problem by sampling a small subset of data for annotators to label. While active learning is …

Social Bias in Elicited Natural Language Inferences

2017

We analyze the Stanford Natural Language Inference (SNLI) corpus in an investigation of bias and stereotyping in NLP data. The human-elicitation protocol employed in the construction of the SNLI makes it prone to amplifying bias …