20 citations · 71 across the 10 of their papers we have counts for
10 papers
A Keyword Based Approach to Understanding the Overpenalization of Marginalized Groups by English Marginal Abuse Models on Twitter
Kyra Yee, Alice Schoenauer Sebag, Olivia Redfield +3
Harmful content detection models tend to have higher false positive rates for content from marginalized groups. In the context of marginal abuse modeling on Twitter, such dispropor…
On Measures of Biases and Harms in NLP
Sunipa Dev, Emily Sheng, Jieyu Zhao +8
Recent studies show that Natural Language Processing (NLP) technologies propagate societal biases about demographic groups associated with attributes such as gender, race, and nati…
Societal Biases in Language Generation: Progress and Challenges
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan +1
Technology for language generation has advanced rapidly, spurred by advancements in pre-training large models on massive amounts of data and the need for intelligent agents to comm…
Revealing Persona Biases in Dialogue Systems
Emily Sheng, Josh Arnold, Zhou Yu +2
Dialogue systems in the form of chatbots and personal assistants are being increasingly integrated into people's lives. Modern dialogue systems may consider adopting anthropomorphi…
Investigating Societal Biases in a Poetry Composition System
Emily Sheng, David Uthus
There is a growing collection of work analyzing and mitigating societal biases in language understanding, generation, and retrieval tasks, though examining biases in creative tasks…
"Nice Try, Kiddo": Investigating Ad Hominems in Dialogue Responses
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan +1
Ad hominem attacks are those that target some feature of a person's character instead of the position the person is maintaining. These attacks are harmful because they propagate im…
Towards Controllable Biases in Language Generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan +1
We present a general approach towards controllable societal biases in natural language generation (NLG). Building upon the idea of adversarial triggers, we develop a method to indu…
The Woman Worked as a Babysitter: On Biases in Language Generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan +1
We present a systematic study of biases in natural language generation (NLG) by analyzing text generated from prompts that contain mentions of different demographic groups. In this…
A Byte-sized Approach to Named Entity Recognition
Emily Sheng, Prem Natarajan
In biomedical literature, it is common for entity boundaries to not align with word boundaries. Therefore, effective identification of entity spans requires approaches capable of c…
An Investigation into the Pedagogical Features of Documents
Emily Sheng, Prem Natarajan, Jonathan Gordon +1
Characterizing the content of a technical document in terms of its learning utility can be useful for applications related to education, such as generating reading lists from large…