{"ID":2855466,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.12036","arxiv_id":"2510.12036","title":"On the Interplay between Human Label Variation and Model Fairness","abstract":"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.","short_abstract":"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 con...","url_abs":"https://arxiv.org/abs/2510.12036","url_pdf":"https://arxiv.org/pdf/2510.12036v2","authors":"[\"Kemal Kurniawan\",\"Meladel Mistica\",\"Timothy Baldwin\",\"Jey Han Lau\"]","published":"2025-10-14T00:43:48Z","proceeding":"cs.CL","tasks":"[\"cs.CL\"]","methods":"[]","has_code":false}