7 citations · 20 across the 10 of their papers we have counts for
14 papers
Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Language
Jimin Mun, Emily Allaway, Akhila Yerukola +3
Counterspeech, i.e., responses to counteract potential harms of hateful speech, has become an increasingly popular solution to address online hate speech without censorship. Howeve…
Towards Countering Essentialism through Social Bias Reasoning
Emily Allaway, Nina Taneja, Sarah-Jane Leslie +1
Essentialist beliefs (i.e., believing that members of the same group are fundamentally alike) play a central role in social stereotypes and can lead to harm when left unchallenged.…
Legal and Political Stance Detection of SCOTUS Language
Noah Bergam, Emily Allaway, Kathleen McKeown
We analyze publicly available US Supreme Court documents using automated stance detection. In the first phase of our work, we investigate the extent to which the Court's public-fac…
SafeText: A Benchmark for Exploring Physical Safety in Language Models
Sharon Levy, Emily Allaway, Melanie Subbiah +4
Understanding what constitutes safe text is an important issue in natural language processing and can often prevent the deployment of models deemed harmful and unsafe. One such typ…
Mitigating Covertly Unsafe Text within Natural Language Systems
Alex Mei, Anisha Kabir, Sharon Levy +7
An increasingly prevalent problem for intelligent technologies is text safety, as uncontrolled systems may generate recommendations to their users that lead to injury or life-threa…
Seeded Hierarchical Clustering for Expert-Crafted Taxonomies
Anish Saha, Amith Ananthram, Emily Allaway +2
Practitioners from many disciplines (e.g., political science) use expert-crafted taxonomies to make sense of large, unlabeled corpora. In this work, we study Seeded Hierarchical Cl…
Penguins Don't Fly: Reasoning about Generics through Instantiations and Exceptions
Emily Allaway, Jena D. Hwang, Chandra Bhagavatula +3
Generics express generalizations about the world (e.g., birds can fly) that are not universally true (e.g., newborn birds and penguins cannot fly). Commonsense knowledge bases, use…
Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic
António Câmara, Nina Taneja, Tamjeed Azad +2
As natural language processing systems become more widespread, it is necessary to address fairness issues in their implementation and deployment to ensure that their negative impac…
Adversarial Learning for Zero-Shot Stance Detection on Social Media
Emily Allaway, Malavika Srikanth, Kathleen McKeown
Stance detection on social media can help to identify and understand slanted news or commentary in everyday life. In this work, we propose a new model for zero-shot stance detectio…
Does Putting a Linguist in the Loop Improve NLU Data Collection?
Alicia Parrish, William Huang, Omar Agha +7
Many crowdsourced NLP datasets contain systematic gaps and biases that are identified only after data collection is complete. Identifying these issues from early data samples durin…
Event Guided Denoising for Multilingual Relation Learning
Amith Ananthram, Emily Allaway, Kathleen McKeown
General purpose relation extraction has recently seen considerable gains in part due to a massively data-intensive distant supervision technique from Soares et al. (2019) that prod…
Zero-Shot Stance Detection: A Dataset and Model using Generalized Topic Representations
Emily Allaway, Kathleen McKeown
Stance detection is an important component of understanding hidden influences in everyday life. Since there are thousands of potential topics to take a stance on, most with little…
A Unified Feature Representation for Lexical Connotations
Emily Allaway, Kathleen McKeown
Ideological attitudes and stance are often expressed through subtle meanings of words and phrases. Understanding these connotations is critical to recognizing the cultural and emot…
Event2Mind: Commonsense Inference on Events, Intents, and Reactions
Hannah Rashkin, Maarten Sap, Emily Allaway +2
We investigate a new commonsense inference task: given an event described in a short free-form text ("X drinks coffee in the morning"), a system reasons about the likely intents ("…