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Trojan Detection Software Challenge - nlp-question-answering-sep2021-test

Round 8 Test DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers. This dataset consists of 360 QA AI models using a small set of model architectures. Half (50%) of the models have been poisoned with an embedded trigger which causes misclassification of the input when the trigger is present.

About this Dataset

Updated: 2024-02-22
Metadata Last Updated: 2021-08-09 00:00:00
Date Created: N/A
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Dataset Owner: N/A

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Table representation of structured data
Title Trojan Detection Software Challenge - nlp-question-answering-sep2021-test
Description Round 8 Test DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers. This dataset consists of 360 QA AI models using a small set of model architectures. Half (50%) of the models have been poisoned with an embedded trigger which causes misclassification of the input when the trigger is present.
Modified 2021-08-09 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:[email protected]
Keywords Trojan Detection , Artificial Intelligence , AI , Machine Learning , Adversarial Machine Learning
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