| Challenge: | Existing systems that embed and amplify gender bias can still exhibit and exacerbate this problem. |
| Approach: | They propose a multi-step system that combines the positive aspects of rule-based and neural rewriting models to provide personalized outputs based on the users’ grammatical gender preferences. |
| Outcome: | The proposed system achieves 88.42 M2 F0.5 on a blind test set and improves over previous work on the first-person-only version of this task by 3.05 absolute increase in M2F0.5. |
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NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender Neutral Alternatives (2021.emnlp-main)
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| Challenge: | In the past years, LLMs have been used in everyday tasks, especially the formulation and revision of text. |
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