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Found 7 papers, 2 papers with code
Disentangling Categorization in Multi-agent Emergent Communication
The emergence of language between artificial agents is a recent focus of computational linguistics, as it offers a synthetic substrate for reasoning about human language evolution.
Less is More: Dimension Reduction Finds On-Manifold Adversarial Examples in Hard-Label Attacks
It was recently shown in the gradient-level setting that regular adversarial examples leave the data manifold, while their on-manifold counterparts are in fact generalization errors.
Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples
It was recently shown in the gradient-level setting that regular adversarial examples leave the data manifold, while their on-manifold counterparts are in fact generalization errors.
Hear "No Evil", See "Kenansville": Efficient and Transferable Black-Box Attacks on Speech Recognition and Voice Identification Systems
Automatic speech recognition and voice identification systems are being deployed in a wide array of applications, from providing control mechanisms to devices lacking traditional interfaces, to the automatic transcription of conversations and authentication of users.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Practical Hidden Voice Attacks against Speech and Speaker Recognition Systems
In this paper, we break these dependencies and make hidden command attacks more practical through model-agnostic (blackbox) attacks, which exploit knowledge of the signal processing algorithms commonly used by VPSes to generate the data fed into machine learning systems.
Explainable Black-Box Attacks Against Model-based Authentication
Establishing unique identities for both humans and end systems has been an active research problem in the security community, giving rise to innovative machine learning-based authentication techniques.
BIG-bench Machine Learning
Explainable Artificial Intelligence (XAI)
MTLE: A Multitask Learning Encoder of Visual Feature Representations for Video and Movie Description
Many of the current state of the art methods for video captioning and movie description rely on simple encoding mechanisms through recurrent neural networks to encode temporal visual information extracted from video data.
