Papers by Meghana Moorthy Bhat
Say ‘YES’ to Positivity: Detecting Toxic Language in Workplace Communications (2021.findings-emnlp)
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| Challenge: | Toxic workplace communication is subtle, hidden or shows human biases . lack of corpus, sparsity of toxicity in enterprise emails hinder study . |
| Approach: | They propose a taxonomy to study toxic language at the workplace and a dataset to study it. |
| Outcome: | The proposed taxonomy provides a general and computationally viable taxonomies for studying toxic language at the workplace and analyzes why offensive language and hate-speech datasets are not suitable to detect workplace toxicity. |
Self-training with Few-shot Rationalization (2021.emnlp-main)
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| Challenge: | Recent work focused on training largescale and complex neural network models, but they are opaque in terms of their decision-making process. |
| Approach: | They propose a multi-task teacher-student framework for self-training pre-trained language models with limited task-specific labels and annotated rationales. |
| Outcome: | The proposed model improves performance in low-resource settings by making it aware of its rationalized predictions. |