1 code implementation • EMNLP 2021 • Sahil Jayaram, Emily Allaway
As NLP systems become better at detecting opinions and beliefs from text, it is important to ensure not only that models are accurate but also that they arrive at their predictions in ways that align with human reasoning.
no code implementations • 31 Oct 2023 • Jimin Mun, Emily Allaway, Akhila Yerukola, Laura Vianna, Sarah-Jane Leslie, Maarten Sap
Counterspeech, i. e., responses to counteract potential harms of hateful speech, has become an increasingly popular solution to address online hate speech without censorship.
no code implementations • 28 Mar 2023 • Emily Allaway, Nina Taneja, Sarah-Jane Leslie, Maarten Sap
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.
1 code implementation • 21 Nov 2022 • Noah Bergam, Emily Allaway, Kathleen McKeown
As a natural extension of this political stance detection, we propose the more specialized task of legal stance detection with our new dataset SC-stance, which matches written opinions to legal questions.
no code implementations • 18 Oct 2022 • Sharon Levy, Emily Allaway, Melanie Subbiah, Lydia Chilton, Desmond Patton, Kathleen McKeown, William Yang Wang
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.
no code implementations • 17 Oct 2022 • Alex Mei, Anisha Kabir, Sharon Levy, Melanie Subbiah, Emily Allaway, John Judge, Desmond Patton, Bruce Bimber, Kathleen McKeown, William Yang Wang
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-threatening consequences.
no code implementations • 23 May 2022 • Emily Allaway, Jena D. Hwang, Chandra Bhagavatula, Kathleen McKeown, Doug Downey, Yejin Choi
Generics express generalizations about the world (e. g., birds can fly) that are not universally true (e. g., newborn birds and penguins cannot fly).
no code implementations • 23 May 2022 • Anish Saha, Amith Ananthram, Emily Allaway, Heng Ji, Kathleen McKeown
Practitioners from many disciplines (e. g., political science) use expert-crafted taxonomies to make sense of large, unlabeled corpora.
no code implementations • LTEDI (ACL) 2022 • António Câmara, Nina Taneja, Tamjeed Azad, Emily Allaway, Richard Zemel
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 impacts on society are understood and minimized.
1 code implementation • NAACL 2021 • Emily Allaway, Malavika Srikanth, Kathleen McKeown
Stance detection on social media can help to identify and understand slanted news or commentary in everyday life.
no code implementations • EMNLP 2021 • Emily Allaway, Shuai Wang, Miguel Ballesteros
Relating entities and events in text is a key component of natural language understanding.
coreference-resolution Cross Document Coreference Resolution +1
no code implementations • Findings (EMNLP) 2021 • Alicia Parrish, William Huang, Omar Agha, Soo-Hwan Lee, Nikita Nangia, Alex Warstadt, Karmanya Aggarwal, Emily Allaway, Tal Linzen, Samuel R. Bowman
We take natural language inference as a test case and ask whether it is beneficial to put a linguist `in the loop' during data collection to dynamically identify and address gaps in the data by introducing novel constraints on the task.
no code implementations • 4 Dec 2020 • 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 produces state-of-the-art results across many benchmarks.
no code implementations • COLING 2020 • 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 produces state-of-the-art results across many benchmarks.
1 code implementation • EMNLP 2020 • Emily Allaway, Kathleen McKeown
Stance detection is an important component of understanding hidden influences in everyday life.
no code implementations • EACL 2021 • Emily Allaway, Kathleen McKeown
Ideological attitudes and stance are often expressed through subtle meanings of words and phrases.
2 code implementations • 31 Oct 2018 • Maarten Sap, Ronan LeBras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, Yejin Choi
We present ATOMIC, an atlas of everyday commonsense reasoning, organized through 877k textual descriptions of inferential knowledge.
no code implementations • ACL 2018 • Hannah Rashkin, Maarten Sap, Emily Allaway, Noah A. Smith, Yejin Choi
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 ("X wants to stay awake") and reactions ("X feels alert") of the event's participants.
Ranked #1 on Common Sense Reasoning on Event2Mind test