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Email

y.otmakhova@unimelb.edu.au

Credentials


Position
Research Fellow, NLP/Media Bias
School of Computing and Information Systems
Education
PhD
University of Melbourne
Masters
Seoul National University
Bachelors Degree (Honours)
Tomsk State University
ORCID

0000-0002-6738-3451

Dr Yulia Otmakhova

Research Fellow, NLP/Media Bias
School of Computing and Information Systems

20 Scholarly works
1 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Retain or Reframe? A Computational Framework for the Analysis of Framing in News Articles and Reader Comments
    DOI: 10.1162/TACL.a.698
  • 2025

    Conference Proceedings

    Narrative Media Framing in Political Discourse
    DOI: 10.18653/v1/2025.findings-acl.477
  • 2025

    Report

    Submission to the Select Committee on Information Integrity on Climate Change and Energy, Parliament of Australia
  • 2025

    Research grants (other domestic)

    Detecting Misinforming Narrative Plots in Climate Change News
  • 2024

    Conference Proceedings

    Revisiting subword tokenization: A case study on affixal negation in large language models
    DOI: 10.18653/v1/2024.naacl-long.284
  • 2024

    Conference Proceedings

    Media Framing: A Typology and Survey of Computational Approaches Across Disciplines
    DOI: 10.18653/v1/2024.acl-long.822
  • 2024

    Conference Proceedings

    Generative Debunking of Climate Misinformation
    DOI: 10.18653/v1/2024.climatenlp-1.4
Yulia Otmakhova

RECENT SCHOLARLY WORKS

  • 2023

    Thesis / Dissertation

    Multi-document Summarisation Supporting Clinical Evidence Review
  • 2023

    Journal article

    Automating Quality Assessment of Medical Evidence in Systematic Reviews: Model Development and Validation Study
    DOI: 10.2196/35568
  • 2023

    Conference Proceedings

    Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations
    DOI: 10.18653/v1/2023.acl-long.549
  • 2022

    Conference Proceedings

    Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal Negation
    DOI: 10.18653/v1/2022.aacl-main.65

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