Transformer models detect applicant gender in de-gendered academic recommendation letters via implicit linguistic patterns such as associations with words like 'emotional' and 'humanitarian', and removing these cues reduces but does not eliminate prediction accuracy above chance.
ReadmeReady: Free and Customizable Code Documentation with LLMs-A Fine-Tuning Approach.Journal of Open Source Software, 10(108):7489, 2025
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Reinforcement learning policies for time-constrained slate recommendations improve engagement over contextual bandits in e-commerce settings.
citing papers explorer
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Identifying and Mitigating Gender Cues in Academic Recommendation Letters: An Interpretability Case Study
Transformer models detect applicant gender in de-gendered academic recommendation letters via implicit linguistic patterns such as associations with words like 'emotional' and 'humanitarian', and removing these cues reduces but does not eliminate prediction accuracy above chance.
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Time-Constrained Recommendations: Reinforcement Learning Strategies for E-Commerce
Reinforcement learning policies for time-constrained slate recommendations improve engagement over contextual bandits in e-commerce settings.