Papers by Phil Ostheimer

2 papers
Tethering Broken Themes: Aligning Neural Topic Models with Labels and Authors (2025.findings-naacl)

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Challenge: Recent studies suggest that topic models do not align well with human intentions.
Approach: They propose a method to align neural topic models with both labels and authorship information.
Outcome: The proposed method improves existing models in terms of topic quality and alignment.
A Call for Standardization and Validation of Text Style Transfer Evaluation (2023.findings-acl)

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Challenge: Text style transfer (TST) evaluation is inconsistent in practice.
Approach: They conduct a meta-analysis on human and automated TST evaluation and experimentation . they find a standardization gap and a validation gap in the field .
Outcome: The authors find that evaluation procedures are inconsistent and that they need to improve on them.

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