Gender Bias in Coreference Resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard, Benjamin Van Durme
TL;DR
This paper investigates gender bias in coreference resolution systems using a new set of minimal pair sentences called Winogender schemas, revealing systematic biases and their correlation with gender statistics.
Contribution
Introduces Winogender schemas for evaluating gender bias and demonstrates systematic bias in three coreference systems, linking it to real-world gender data.
Findings
Systematic gender bias confirmed in three coreference systems
Winogender schemas effectively reveal bias differences
Bias correlates with real-world gender statistics
Abstract
We present an empirical study of gender bias in coreference resolution systems. We first introduce a novel, Winograd schema-style set of minimal pair sentences that differ only by pronoun gender. With these "Winogender schemas," we evaluate and confirm systematic gender bias in three publicly-available coreference resolution systems, and correlate this bias with real-world and textual gender statistics.
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Code & Models
- 🤗google/gemma-7bmodel· 30k dl· ♡ 329330k dl♡ 3293
- 🤗google/gemma-2-2b-itmodel· 368k dl· ♡ 1314368k dl♡ 1314
- 🤗google/gemma-2-2bmodel· 489k dl· ♡ 636489k dl♡ 636
- 🤗google/gemma-2bmodel· 174k dl· ♡ 1152174k dl♡ 1152
- 🤗google/gemma-2-27b-itmodel· 309k dl· ♡ 561309k dl♡ 561
- 🤗google/gemma-2-9b-itmodel· 254k dl· ♡ 781254k dl♡ 781
- 🤗ataeff/recurrentgemma-2b-itmodel· ♡ 1♡ 1
- 🤗google/gemma-2b-itmodel· 57k dl· ♡ 86257k dl♡ 862
- 🤗google/gemma-7b-itmodel· 67k dl· ♡ 124167k dl♡ 1241
- 🤗alpindale/gemma-7bmodel· 66 dl· ♡ 766 dl♡ 7
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