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Cited by 2Recommender Systems and TechniquesEthics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation

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Wang, Nan, Wang, Qifan, Wang, Yi-Chia, Sanjabi, Maziar, Liu, Jingzhou, Firooz, Hamed, Wang, Hongning, Nie, Shaoliang·2023·Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
DOI 10.18653/v1/2023.emnlp-main.819
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Abstract

Nan Wang, Qifan Wang, Yi-Chia Wang, Maziar Sanjabi, Jingzhou Liu, Hamed Firooz, Hongning Wang, Shaoliang Nie. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. 2023.

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  • Personalization may provide identifying information about the user leading to biases in the generated text.

    “Moreover, personalization may provide identifying information about the user leading to biases in the generated text (Wang et al., 2023; He et al., 2024; Weissburg et al., 2024).”

    From On the Way to LLM Personalization: Learning to Remember User Conversations (2024) · cites this paper as Wang et al., 2023

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Authors
Wang, N., Wang, Q., Wang, Y.-C., Sanjabi, M., Liu, J., Firooz, H., Wang, H., & Nie, S.
Affiliations
  • University of Virginia (US)
  • Meta (United States) (US)
Corresponding author
Wang, Nan
ORCID
Venue
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Publisher
Association for Computational Linguistics
Published
2023
Pages
13258-13275
DOI
10.18653/v1/2023.emnlp-main.819
OpenAlex
W4389523737
Cited by
2
References
66
Citations by year
2024: 2
FWCI
0.51
Type
conference paper
Language
en
Open access
Licence
cc-by
Locations
Conference on Empirical Methods in Natural Language Processing (EMNLP) (publishedVersion, cc-by)
Funders
National Science Foundation (2007492, 1838615)
Topics
  • Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
Keywords
counterfactual fairness, personalized text generation, explainable recommendation, recommendation fairness, text generation

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