Papers by Akhash Amarnath
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 . |
Demographic-Aware Language Model Fine-tuning as a Bias Mitigation Technique (2022.aacl-short)
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| Challenge: | In this paper, we analyze the variations in gender and racial biases in BERT-like language models when exposed to different demographic groups. |
| Approach: | They analyze gender and racial biases in BERT-like language models when exposed to different demographic groups. |
| Outcome: | The proposed model can mitigate biases in text authored by disadvantaged demographic groups compared to advantaged groups . the proposed model is agnostic to the language of the speakers behind the language . |