Pannaga Shivaswamy

What is in a name? Mitigating Name Bias in Text Embedding Similarity via Anonymization

Text-embedding models often exhibit biases arising from the data on which they are trained. In this paper, we examine a hitherto unexplored bias in text-embeddings: bias arising from the presence of names such as persons, locations, organizations etc. in the text. Our study shows how the presence of…