VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations
@article{Rathore2021VERBVA, title={VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations}, author={Archit Rathore and Sunipa Dev and J. M. Phillips and Vivek Srikumar and Yan-luan Zheng and Chin-Chia Michael Yeh and Junpeng Wang and Wei Zhang and Bei Wang}, journal={ArXiv}, year={2021}, volume={abs/2104.02797} }
Word vector embeddings have been shown to contain and amplify biases in data they are extracted from. Consequently, many techniques have been proposed to identify, mitigate, and attenuate these biases in word representations. In this paper, we utilize interactive visualization to increase the interpretability and accessibility of a collection of state-of-the-art debiasing techniques. To aid this, we present Visualization of Embedding Representations for deBiasing system (“VERB”), an open-source…
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