Papers by Rohit Sridhar

2 papers
Explaining Toxic Text via Knowledge Enhanced Text Generation (2022.naacl-main)

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Challenge: Existing work on toxic speech classification relies on generic and repetitive explanations . elucidating toxic speech can help with downstream tasks such as debiasing .
Approach: They propose a knowledge-informed encoder-decoder framework to generate toxic text explanations . they use multiple knowledge sources to generate detailed explanations of toxic text .
Outcome: The proposed model outperforms state-of-the-art models significantly in generating toxic explanations . the proposed model can generate detailed explanations of toxic speech compared to baselines compared with baseline models .
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models (2022.findings-naacl)

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Challenge: Existing work identifies task-specific shortcuts via human priors or error analyses, which requires extensive expertise and efforts.
Approach: They propose to automatically identify spurious correlations in NLP models at scale by using existing interpretability methods to extract tokens that significantly affect model’s decision process.
Outcome: The proposed method can identify spurious correlations in NLP models at scale and mitigate these leads to more robust models in multiple applications.

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