He is very intelligent, she is very beautiful? On Mitigating Social Biases in Language Modelling and Generation (2021.findings-acl)
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Aparna Garimella, Akhash Amarnath, Kiran Kumar, Akash Pramod Yalla, Anandhavelu N, Niyati Chhaya, Balaji Vasan Srinivasan
| Challenge: | Existing studies have focused on mitigating social biases in context-free representations, with recent shift to contextual ones. |
| Approach: | They propose an approach to mitigate social biases in a large pre-trained contextual language model . they propose lexical co-occurrence-based bias penalization in the decoder units . |
| Outcome: | The proposed approach reduces biases in fill-in-the-blank sentences and summarizes . it also reduces the biased representations in the frameworks, the authors show . |
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