EPISODE · Feb 17, 2022 · 44 MIN
Imperceptible NLP Attacks
from The Data Exchange with Ben Lorica · host Ben Lorica
Nicholas Boucher is a PhD at Cambridge University where his focus is on security including on topics like homomorphic encryption, voting systems, and adversarial machine learning. He is the lead author of a fascinating new paper – “Bad Characters: Imperceptible NLP Attacks” – which provides a taxonomy of attacks against text-based NLP models, that are based on Unicode and other encoding systems. Download a FREE copy of our recent NLP Industry Survey Results: https://gradientflow.com/2021nlpsurvey/Subscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.
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Nicholas Boucher is a PhD at Cambridge University where his focus is on security including on topics like homomorphic encryption, voting systems, and adversarial machine learning. He is the lead author of a fascinating new paper – “Bad Characters: Imperceptible NLP Attacks” – which provides a taxonomy of attacks against text-based NLP models, that are based on Unicode and other encoding systems. Download a FREE copy of our recent NLP Industry Survey Results: https://gradientflow...
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Imperceptible NLP Attacks
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