Papers with regression-based models
Identifying Bias in Machine-generated Text Detection (2026.acl-long)
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| Challenge: | a growing number of generative AI systems are detecting text generated by a model or written by . humans perform poorly at the detection task, but show no significant biases on the studied attributes. |
| Approach: | They examine gender, race/ethnicity, English-language learner status, and economic status . they find several models tend to classify disadvantaged groups as machine-generated . |
| Outcome: | The proposed models show strong performance but can cause negative impacts . the models classify disadvantaged groups as machine-generated, while economically disadvantaged students' essays are less likely to be classified as machine generated . |