Papers by Shweta Singh
Open-DeBias: Toward Mitigating Open-Set Bias in Language Models (2025.findings-emnlp)
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| Challenge: | Existing approaches to addressing harmful biases in LLMs are limited to predefined categories . a novel, data-efficient, and parameter-efficient debiasing method is proposed to mitigate existing social and stereotypical biase . |
| Approach: | They propose an open-set bias detection and mitigation method to address harmful biases in text-based QA. |
| Outcome: | The proposed method improves QA accuracy on Korean BBQ dataset by nearly 48% on ambiguous subsets and 6% on disambiguated ones. |
IPO: Your Language Model is Secretly a Preference Classifier (2025.acl-long)
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| Challenge: | Reinforcement learning from human feedback (RLHF) is the primary method for aligning large language models with human preferences, but it often incurs significant computational and financial costs due to its reliance on training external reward models or human-labeled preferences. |
| Approach: | They propose an alternative approach that leverages generative LLMs as preference classifiers to reduce the dependence on external reward models or human-labeled preferences. |
| Outcome: | The proposed approach reduces the dependence on external reward models or human-labeled preferences by using generative LLMs as preference classifiers. |