Papers by Tulika Bose
Transferring Knowledge via Neighborhood-Aware Optimal Transport for Low-Resource Hate Speech Detection (2022.aacl-main)
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| Challenge: | Existing approaches to detect hate speech are expensive and time-consuming . a new approach allows for flexible learning of neighborhood information . |
| Approach: | They propose a method that allows flexible modeling of neighbors retrieved from a resource-rich corpus to learn the amount of transfer. |
| Outcome: | The proposed training strategy improves on low-resource hate speech corpora over baselines. |
Domain Classification-based Source-specific Term Penalization for Domain Adaptation in Hate-speech Detection (2022.coling-1)
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| Challenge: | Existing approaches for hate-speech detection exhibit poor performance in out-of-domain settings due to overemphasizing source-specific information that negatively impacts its domain invariance. |
| Approach: | They propose a domain adaptation approach that automatically extracts and penalizes source-specific terms using a classifier. |
| Outcome: | The proposed approach improves cross-domain evaluation on indomain held-out instances while preserving high performance on out-of-domain settings. |
Dynamically Refined Regularization for Improving Cross-corpora Hate Speech Detection (2022.findings-acl)
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| Challenge: | Hate speech classifiers exhibit performance degradation when evaluated on datasets different from the source. |
| Approach: | They propose to automatically identify and reduce spurious correlations using attribution methods with dynamic refinement of the list of terms that need to be regularized during training. |
| Outcome: | The proposed method improves performance across corpora and on different datasets. |