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publications
Benchmarking and Improving LLM Robustness for Personalized Generation
Published in Findings of the Empirical Methods in Natural Language Processing (EMNLP), 2025
This paper highlights the issues associated with the current evaluation approaches in personalization that focus solely on preference alignment and adovate for a multidemnsional evaluation approach instead
Recommended citation: Chimaobi Okite, Naihao Deng, Kiran Bodipati, Huaidian Hou, Joyce Chai, Rada Mihalcea. (2025). "Benchmarking and Improving LLM Robustness for Personalized Generation" In Findings of the Empirical Methods in Natural Language Processing .
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talks
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teaching
Graduate Student Instructor
CSE 595: Natural Language Processing, Fall, 2025