Design biases in NLP systems, such as performance differences for differ...
Most existing stylistic text rewriting methods operate on a sentence lev...
Improving language model generations according to some user-defined qual...
The most meaningful connections between people are often fostered throug...
We present Queer in AI as a case study for community-led participatory d...
Essentialist beliefs (i.e., believing that members of the same group are...
AI systems are becoming increasingly intertwined with human life. In ord...
Toxic language detection systems often falsely flag text that contains
m...
What would it take to teach a machine to behave ethically? While broad
e...
Dialogue models trained on human conversations inadvertently learn to
ge...
Despite recent advances in natural language generation, it remains
chall...
Prior beliefs of readers impact the way in which they project meaning on...
As language models are trained on ever more text, researchers are turnin...
Language models (LMs) must be both safe and equitable to be responsibly
...
Biased associations have been a challenge in the development of classifi...
Social norms—the unspoken commonsense rules about acceptable social
beha...
Unconscious biases continue to be prevalent in modern text and media, ca...
Pretrained neural language models (LMs) are prone to generating racist,
...
Language has the power to reinforce stereotypes and project social biase...
We present the first comprehensive study on automatic knowledge base
con...
We introduce SocialIQa, the first large-scale benchmark for commonsense
...
We present ATOMIC, an atlas of everyday commonsense reasoning, organized...
We investigate a new commonsense inference task: given an event describe...
Understanding a narrative requires reading between the lines and reasoni...
We present Sounding Board, a social chatbot that won the 2017 Amazon Ale...
A writer's style depends not just on personal traits but also on her int...