Emily Allaway

I am a Chancellor's Fellow (=UK lecturer=US Assistant professor) at the University of Edinburgh in the School of Informatics. I am affiliated with ILCC (Institute for Language, Cognition, and Computation) and Edinburgh NLP.

I am interested in reasoning about and understanding implicit meaning in language. My recent work has focused on generics (a specific type of language generalization). This includes generics, non-monotonic reasoning, commonsense reasoning, and neuro-symbolic systems that incorporate ideas from linguistics. Specifically, at Edinburgh I will be working on developing interpretable neuro-symbolic methods to improve defeasible reasoning in computational systems. These methods will incorporate theoretically-grounded components into deep learning models. I will be using these methods to improve reasoning in real-world texts, including dialogues, argumentation, and text-based games.


If you are interested in collaborating, please contact me.


I will be recruiting a PhD student to start either winter or fall 2025.


I received my PhD in computer science from Columbia University where I worked with Prof. Kathleen McKeown. My thesis, “Understanding and Reasoning about Implicit Meaning in Language” focused on stance detection, as well as generics. During my PhD, I interned at AI2 (on the MOSAIC team, working with Jena Hwang and Chandra Bhagavatula) and at Amazon Science (working with Miguel Ballesteros and Shuai Wang). Prior to Columbia, I worked on commonsense reasoning as an undergraduate researcher with Prof. Yejin Choi at the University of Washington.

My CV is here.

Contact: emily.allaway@ed.ac.uk

Publications

  • Exceptions, Instantiations, and Overgeneralization: Insights into How Language Models Process Generics
    Emily Allaway, Chandra Bhagavatula, Jena D. Hwang, Kathleen McKeown, and Sarah-Jane Leslie.
    Computational Linguistics: Special Issue on Language Learning, Representation, and Processing in Humans and Machines, 2024.
    [pdf]
  • Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Language
    Jimin Mun, Emily Allaway, Akhila Yerukola, Laura Vianna, Sarah-Jane Leslie, Maarten Sap.
    [pdf]
  • Penguins Don't Fly: Reasoning about Generics through Instantiations and Exceptions
    Emily Allaway, Jena D. Hwang, Chandra Bhagavatula, Kathleen McKeown, Doug Downey, Yejin Choi.
    EACL 2023.
    [pdf]
  • Zero-Shot Stance Detection: Paradigms and Challenges
    Emily Allaway and Kathleen McKeown.
    Frontiers of Artificial Intelligence 2023.
    [pdf]
  • Towards Countering Essentialism through Social Bias Reasoning
    Emily Allaway, Nina Taneja, Sarah-Jane Leslie, Maarten Sap.
    NLP4PosImp Workshop, EMNLP 2022.
    [poster] [pdf]
  • Legal and Political Stance Detection of SCOTUS Language
    Noah Bergam, Emily Allaway, Kathleen McKeown.
    NLLP Workshop, EMNLP 2022.
    [pdf]
  • Seeded Hierarchical Clustering for Expert-Crafted Taxonomies
    Anish Saha, Amith Ananthram, Emily Allaway, Heng Ji, Kathleen McKeown.
    Findings EMNLP 2022.
    [pdf]
  • SafeText: A Benchmark for Exploring Physical Safety in Language Models
    Sharon Levy, Emily Allaway, Melanie Subbiah, Lydia Chilton, Desmond Patton, Kathleen McKeown, William Yang Wang.
    EMNLP 2022.
    [pdf]
  • Mitigating Covertly Unsafe Text within Natural Language Systems
    Alex Mei, Anisha Kabir, Sharon Levy, Melanie Subbiah, Emily Allaway, John Judge, Desmond Patton, Bruce Bimber, Kathleen McKeown, William Yang Wang.
    Findings EMNLP 2022.
    [pdf]
  • Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic
    António Câmara, Nina Taneja, Tamjeed Azad, Emily Allaway, Richard Zemel.
    LT-EDI Workshop, ACL 2022.
    [pdf]
  • Does Putting a Linguist in the Loop Improve NLU Data Collection?
    Alicia Parrish, William Huang, Omar Agha, Soo-Hwan Lee, Nikita Nangia, Alex Warstadt, Karmanya Aggarwal, Emily Allaway, Tal Linzen, and Samuel R. Bowman.
    Findings EMNLP 2021.
    [pdf]
  • Human Rationales as Attribution Priors for Explainable Stance Detection
    Sahil Jayaram and Emily Allaway.
    EMNLP 2021.
    [pdf] [code and data]
  • Sequential Cross-Document Coreference Resolution
    Emily Allaway, Shuai Wang, and Miguel Ballesteros.
    EMNLP 2021.
    [pdf]
  • Adversarial Learning for Zero-Shot Stance Detection on Social Media
    Emily Allaway*, Malavika Srikanth*, and Kathleen McKeown.
    NAACL 2021.
    [pdf] [code and data]
  • A Unified Feature Representation for Lexical Connotations
    Emily Allaway and Kathleen McKeown.
    EACL 2021.
    [pdf] [code and data] [poster]
  • Event-Guided Denoising for Multilingual Relation Learning
    Amith Ananthram, Emily Allaway, Kathleen McKeown.
    COLING 2020.
    [pdf] [code]
  • Zero-Shot Stance Detection: A Dataset and Model using Generalized Topic Representations
    Emily Allaway and Kathleen McKeown.
    EMNLP 2020.
    [pdf] [code and data] [poster]
  • GAIA at SM-KBP2019 - A Multi-media Multi-lingual Knowledge Extraction and Hypothesis Generation System
    Manling Li, Ying Lin, Ananya Subburathinam, Spencer Whitehead, Xiaoman Pan, Di Lu, Qingyun Wang, Tongtao Zhang, Lifu Huang, Heng Ji, Alireza Zareian, Hassan Akbari, Brian Chen, Bo Wu, Emily Allaway, Shih-Fu Chang, Kathleen McKeown, Yixiang Yao, Jennifer Chen, Eric Berquist, Kexuan Sun, Xujun Peng, Ryan Gabbard, Marjorie Freedman, Pedro Szekely, T.K. Satish Kumar, Arka Sadhu, Ram Nevatia, Miguel Rodriguez, Yifan Wang, Yang Bai, Ali Sadeghian, Daisy Zhe Wang.
    TAC 2019.
    [pdf]
  • ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning
    Maarten Sap, Ronan LeBras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A Smith, and Yejin Choi.
    AAAI 2019.
    [pdf] [Project Page]
  • GAIA - A Multi-media Multi-lingual Knowledge Extraction and Hypothesis Generation System
    Tongtao Zhang, Ananya Subburathinam, Ge Shi, Lifu Huang, Di Lu, Xiaoman Pan, Manling Li, Boliang Zhang, Qingyun Wang, Spencer Whitehead, Heng Ji, Alireza Zareian, Hassan Akbari, Brian Chen, Ruiqi Zhong, Steven Shao, Emily Allaway, Shih-Fu Chang, Kathleen McKeown, Dongyu Li, Xin Huang, Kexuan Sun, Xujun Peng, Ryan Gabbard, Marjorie Freedman, Mayank Kejriwal, Ram Nevatia, Pedro Szekely, T.K. Satish Kumar, Ali Sadeghian, Giacomo Bergami, Sourav Dutta, Miguel Rodriguez, Daisy Zhe Wang.
    In TAC 2018.
    [pdf]
  • Event2Mind: Commonsense Inference on Events, Intents, and Reactions
    Hannah Rashkin, Maarten Sap, Emily Allaway, Noah A. Smith and Yejin Choi
    ACL 2018.
    [pdf] [Project Page]

* denotes equal contribution

Teaching

  • Head Teaching Assistant: COMS 4705 - Introduction to Natural Language Processing
    Columbia University (Spring 2021)
  • Teaching Assistant: COMS 4705 - Introduction to Natural Language Processing
    Columbia University (Fall 2019)
  • Teaching Assistant Student Coordinator: CSE 14X - Computer Programming I and II
    University of Washington (Winter 2017, Spring 2017, Fall 2017)
  • Teaching Assistant: CSE 142 - Computer Programming I
    University of Washington (Spring 2015, Fall 2015, Winter 2016, Spring 2016, Fall 2016)

Advising

As an undergraduate student, I had wonderful graduate students as mentors and collaborators (Hannah Rashkin, Maarten Sap) and I am happy to work with dedicated undergraduate and masters students.

Past students:

  • Lauren Hong (Sept. 2022 - Dec. 2022) (co-advised with Elsbeth Turcan)
  • Lucy Wang (Sept. 2021 - Dec. 2022)
  • Noah Bergam (Jan. 2022 - Sept. 2022)
  • Anish Saha (Sept. 2021 - June 2022) (co-advised with Amith Ananthram)
  • António Câmara (Sept. 2021 - June 2022) (co-advised with Elsbeth Turcan) --> PhD @ Harvard
  • Sahil Jayaram (Sept. 2020 - May 2021) --> Apple
  • William Chiu (Jan. 2021 - May 2021)
  • Amith Ananthram (Jan. 2020 - Dec. 2020) --> PhD @ Columbia
  • Malavika Srikanth (Jan. 2020 - Dec. 2020) --> Amazon
  • Yuncong Yang (Jan. 2020 - May 2020)

Misc

In my spare time I like to travel, play music, and ballroom dance.
I have a cat named Mila.