no code implementations • ACL (CODI, CRAC) 2021 • Sopan Khosla, Juntao Yu, Ramesh Manuvinakurike, Vincent Ng, Massimo Poesio, Michael Strube, Carolyn Rosé
In this paper, we provide an overview of the CODI-CRAC 2021 Shared-Task: Anaphora Resolution in Dialogue.
1 code implementation • NAACL (NUSE) 2021 • Michael Yoder, Sopan Khosla, Qinlan Shen, Aakanksha Naik, Huiming Jin, Hariharan Muralidharan, Carolyn Rosé
The pipeline includes modules for character identification and coreference, as well as the attribution of quotes and narration to those characters.
no code implementations • NAACL (BEA) 2022 • James Fiacco, Shiyan Jiang, David Adamson, Carolyn Rosé
In this paper we propose a state-of-the-art method for automated analysis of structure and flow of writing, referred to as Rhetorical Structure Theory (RST) parsing.
no code implementations • TU (COLING) 2022 • Sumit Agarwal, Rosanna Vitiello, Carolyn Rosé
Videos of group interactions contain a wealth of information beyond the information directly communicated in a transcript of the discussion.
no code implementations • COLING (CODI, CRAC) 2022 • Juntao Yu, Sopan Khosla, Ramesh Manuvinakurike, Lori Levin, Vincent Ng, Massimo Poesio, Michael Strube, Carolyn Rosé
The CODI-CRAC 2022 Shared Task on Anaphora Resolution in Dialogues is the second edition of an initiative focused on detecting different types of anaphoric relations in conversations of different kinds.
no code implementations • 16 Jul 2024 • Diya Li, Carolyn Rosé, Ao Yuan, Chunxiao Zhou
In the field of natural language processing, correction of performance assessment for chance agreement plays a crucial role in evaluating the reliability of annotations.
no code implementations • NAACL 2021 • Denis Newman-Griffis, Jill Fain Lehman, Carolyn Rosé, Harry Hochheiser
Natural language processing (NLP) research combines the study of universal principles, through basic science, with applied science targeting specific use cases and settings.
1 code implementation • ACL 2020 • Aakanksha Naik, Carolyn Rosé
We tackle the task of building supervised event trigger identification models which can generalize better across domains.