Papers by Pardis Sadat Zahraei
Prior Beliefs Prejudice LLM-as-Judge: Evidence from Persuasion Evaluation (2026.findings-acl)
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| Challenge: | Large Language Models are increasingly used as judges to evaluate text quality, content and assess arguments. |
| Approach: | They propose to exploit belief-conditioned rating inflation by using persuasion-based probing to examine persuasive arguments. |
| Outcome: | The proposed model fails to evaluate persuasive arguments based on belief alignment . the model fails in three of the three tasks, with belief-conditioned rating inflation accounting for 88% of cases. |
Translate With Care: Addressing Gender Bias, Neutrality, and Reasoning in Large Language Model Translations (2025.findings-acl)
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| Challenge: | addressing gender bias and maintaining logical coherence in machine translation remains challenging, especially when translating between natural gender languages, like English, and genderless languages, such as Persian, Indonesian, and Finnish. |
| Approach: | They propose a dataset to assess translation systems' performance in six low- to mid-resource languages and a translation dataset to examine gender bias and logical coherence. |
| Outcome: | The Translate-with-Care dataset, comprising 3,950 challenging scenarios across six low- to mid-resource languages, reveals a universal struggle in translating genderless content, resulting in gender stereotyping and reasoning errors. |