148 citations · 272 across the 17 of their papers we have counts for
4 papers · 1 filter
Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation
Emily Dinan, Angela Fan, Adina Williams +3
Models often easily learn biases present in the training data, and their predictions directly reflect this bias. We analyze gender bias in dialogue data, and examine how this bias…
Quantifying the Semantic Core of Gender Systems
Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin +2
Many of the world's languages employ grammatical gender on the lexeme. For example, in Spanish, the word for 'house' (casa) is feminine, whereas the word for 'paper' (papel) is mas…
Adversarial NLI: A New Benchmark for Natural Language Understanding
Yixin Nie, Adina Williams, Emily Dinan +3
We introduce a new large-scale NLI benchmark dataset, collected via an iterative, adversarial human-and-model-in-the-loop procedure. We show that training models on this new datase…
On the Idiosyncrasies of the Mandarin Chinese Classifier System
Shijia Liu, Hongyuan Mei, Adina Williams +1
While idiosyncrasies of the Chinese classifier system have been a richly studied topic among linguists (Adams and Conklin, 1973; Erbaugh, 1986; Lakoff, 1986), not much work has bee…