On the Interplay between Human Label Variation and Model Fairness
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917243166654464 |
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| author | Kurniawan, Kemal Mistica, Meladel Baldwin, Timothy Lau, Jey Han |
| author_facet | Kurniawan, Kemal Mistica, Meladel Baldwin, Timothy Lau, Jey Han |
| contents | The impact of human label variation (HLV) on model fairness is an unexplored topic. This paper examines the interplay by comparing training on majority-vote labels with a range of HLV methods. Our experiments show that without explicit debiasing, HLV training methods have a positive impact on fairness under certain configurations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_12036 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On the Interplay between Human Label Variation and Model Fairness Kurniawan, Kemal Mistica, Meladel Baldwin, Timothy Lau, Jey Han Computation and Language The impact of human label variation (HLV) on model fairness is an unexplored topic. This paper examines the interplay by comparing training on majority-vote labels with a range of HLV methods. Our experiments show that without explicit debiasing, HLV training methods have a positive impact on fairness under certain configurations. |
| title | On the Interplay between Human Label Variation and Model Fairness |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2510.12036 |