Papers by Zoran Fijavž

1 papers
Thesis Proposal: Measuring Prejudice at Scale (2026.eacl-srw)

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Challenge: Existing methods for NLP fail to confirm construct validity, limiting the validity of the model.
Approach: They propose to shift from categorical classification to comparative scaling of grounded constructs by using prompt optimization and distillation approaches.
Outcome: The proposed pipeline is scalable for moving from categorical classification to theoretically grounded comparative measurement.

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