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Don't Judge Me by My Face : An Indirect Adversarial Approach to Remove Sensitive Information From Multimodal Neural Representation in Asynchronous Job Video Interviews
In this article, we propose a new adversarial approach to remove sensitive information from the latent representation of neural networks without the need to collect any sensitive variable.
Slices of Attention in Asynchronous Video Job Interviews
In this paper, we focus on studying influential non verbal social signals in asynchronous job video interviews that are discovered by deep learning methods.
HireNet: a Hierarchical Attention Model for the Automatic Analysis of Asynchronous Video Job Interviews
As part of a project to help recruiters, we collected a corpus of more than 7000 candidates having asynchronous video job interviews for real positions and recording videos of themselves answering a set of questions.
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