Esin Durmus

esin

Contact: esindurmus AT cs DOT stanford DOT edu

Hi! I am Esin Durmus. I am a Postdoctoral Scholar at Stanford NLP group working with Tatsu Hashimoto, Dan Jurafsky and Chris Manning. I received my PhD from Cornell University where I was advised by Claire Cardie. I am interested in text generation, evaluating generation systems and social applications of Natural Language Processing such as detection of racism and colorblindness on social media platforms.

News

Publications

  1. On the Opportunities and Risks of Foundation Models
    [paper] [bib]

  2. Towards Understanding Persuasion in Computational Argumentation
    PhD Dissertation
    [paper] [bib]

  3. Leveraging Topic Relatedness for Argument Persuasion
    Xinran Zhao, Esin Durmus, Hongming Zhang, Claire Cardie
    In Findings of ACL, 2021.
    [paper] [bib]

  4. The Gem Benchmark: Natural Language Generation, its Evaluation and Metrics
    [Team] [paper] [bib] [website]

  5. WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization
    Faisal Ladhak, Esin Durmus , Claire Cardie and Kathleen McKeown.
    In Findings of EMNLP, 2020.
    [paper] [data] [bib]

  6. Exploring the Role of Argument Structure in Online Debate Persuasion
    Jialu Li, Esin Durmus and Claire Cardie.
    In Proceedings of EMNLP, 2020.
    [paper] [bib]

  7. FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization
    Esin Durmus, He He and Mona Diab.
    In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2020.
    [paper] [code] [bib]

  8. The Role of Pragmatic and Discourse Context in Determining Argument Impact
    Esin Durmus, Faisal Ladhak and Claire Cardie.
    In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019.
    [paper] [bib]

  9. Determining Relative Argument Specificity and Stance for Complex Argumentative Structures
    Esin Durmus, Faisal Ladhak and Claire Cardie.
    In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), 2019.
    [paper] [bib]

  10. A Corpus for Modeling User and Language Effects in Argumentation on Online Debating
    Esin Durmus and Claire Cardie.
    In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), 2019.
    [paper] [bib] [dataset]

  11. Persuasion of the Undecided: Language vs. the Listener
    Liane Longpre, Esin Durmus and Claire Cardie.
    In Proceedings of the 6th Workshop in Argumentation Mining 2019.
    [paper] [bib] [dataset]

  12. Modeling the Factors of User Success in Online Debate
    Esin Durmus and Claire Cardie.
    In Proceedings of the World Wide Web Conference (WWW), 2019.
    [paper] [bib] [dataset]
    Cornell Chronicle Story

  13. Exploring the Role of Prior Beliefs for Argument Persuasion
    Esin Durmus and Claire Cardie.
    In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), 2018.
    [paper] [bib] [dataset]

  14. Understanding the Effect of Gender and Stance on Opinion Expression in Debates on "Abortion”.
    Esin Durmus and Claire Cardie.
    In Proceedings of PEOPLES2018 workshop (co-organized with NAACL) on computational modeling of peoples opinions, personality, and emotions in social media.
    [paper] [bib]

  15. Cornell Belief and Sentiment System at TAC 2016
    Vlad Niculae, Kai Sun, Xilun Chen, Yao Cheng, Xinya Du, Esin Durmus, Arzoo Katiyar and Claire Cardie.
    Text Analysis Conference (TAC), 2016.
    [paper] [bib]

Published Datasets

Teaching

Industry Experience