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New arXiv Paper Defines Erasure Harms in NLP Systems

A new paper published on arXiv proposes a structured definition for "erasure harms" in Natural Language Processing (NLP) systems. The authors aim to provide a clearer conceptual foundation for identifying and measuring this specific type of harm, which has been a growing concern with the deployment of NLP technologies. The proposed definition is intended to be adaptable across various settings, addressing the limitations of existing broad or highly specific conceptualizations. AI

RANK_REASON The cluster contains an academic paper published on arXiv detailing research into NLP harms. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Yu Lu Liu, Arnav Goel, Jackie Chi Kit Cheung, Alexandra Olteanu, Ziang Xiao, Su Lin Blodgett ·

    On Defining Erasure Harms for NLP

    arXiv:2606.15815v1 Announce Type: new Abstract: The deployment of NLP systems has raised concerns about harms they might produce, including representational harms. Recent literature has begun to conceptualize and measure one such harm, the harm of erasure. Nevertheless, the field…