Warning: this paper contains content that may be offensive or upsetting. Commonsense knowledge bases (CSKB) are increasingly used for various natural language processing tasks. Since CSKBs are mostly human-generated and may reflect societal biases, i
t is important to ensure that such biases are not conflated with the notion of commonsense. Here we focus on two widely used CSKBs, ConceptNet and GenericsKB, and establish the presence of bias in the form of two types of representational harms, overgeneralization of polarized perceptions and representation disparity across different demographic groups in both CSKBs. Next, we find similar representational harms for downstream models that use ConceptNet. Finally, we propose a filtering-based approach for mitigating such harms, and observe that our filtered-based approach can reduce the issues in both resources and models but leads to a performance drop, leaving room for future work to build fairer and stronger commonsense models.
Violence between people as old as life, and the evolution of it and took
some of the traditional crimes new dimensions in their forms and sizes
and styles in the commission, and these patterns that emerged during
the last years of crimes of violence and terrorism that long a lot of
communities, including the Syrian society, which is still over four years
to suffer it.
This study examined the actual status of masturbation and its relationship
to social activity, sexual stimuli, and means to avoid such practice.
A total of 422 medical students in Damascus University, age distribution
were (18-26 year).A questionn
aire had been distributed involved questions
related to the study.
Questions divided in 4 subjects: the first is about the general sexual stimuli,
the second is studying masturbation especially. The third is about risks of
masturbation in general, fourthly is the risks somatic and affective of
masturbation.
