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Found 5 papers, 1 papers with code
Adversarial Attacks on Speech Recognition Systems for Mission-Critical Applications: A Survey
Indeed, Adversarial Artificial Intelligence (AI) which refers to a set of techniques that attempt to fool machine learning models with deceptive data, is a growing threat in the AI and machine learning research community, in particular for machine-critical applications.
Unintended Bias in Language Model-driven Conversational Recommendation
Conversational Recommendation Systems (CRSs) have recently started to leverage pretrained language models (LM) such as BERT for their ability to semantically interpret a wide range of preference statement variations.
Linked Data Triples Enhance Document Relevance Classification
These use an external corpus as a knowledge base that conditions the model to help predict what a document is about.
Feature Extraction Functions for Neural Logic Rule Learning
Combining symbolic human knowledge with neural networks provides a rule-based ante-hoc explanation of the output.
A Distributed Collaborative Filtering Algorithm Using Multiple Data Sources
Collaborative Filtering (CF) is one of the most commonly used recommendation methods.
