Debiasing Knowledge Graphs: Why Female Presidents are not like Female Popes
By Krzysztof Janowicz, Bo Yan, Blake Regalia, Rui Zhu, Gengchen Mai. 2018
37 citations recorded by the source corpus.
Subfields: Safety, Robustness & Interpretability
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In Safety, Robustness & Interpretability
Citations in the corpus
- RuleBERT: Teaching Soft Rules to Pre-Trained Language Models (2021, methodology): “…language patterns (Sheng et al., 2019; Zhang et al., 2020; Bender et al., 2021; Liang et al., 2021) that PLMs impose, and (ii) the imperfectness and the biases of our rules as data from Wikipedia has been used to mine the rules and compute their confidences (Janowicz et al., 2018; Demartini, 2019).”
- Knowledge Graphs (2020, unknown): “Measures of representativeness involve comparison of known statistical distributions with those of the knowledge graph, for example, comparing geolocated entities with known population densities [269], linguistic distributions with known distributions of speakers [276], etc.”