NIST · ИТ · 94bfbd7782bb04a22900
2024 NIST Generative AI (GenAI): Evaluation Plan for Text-to-Text (T2T) Discriminators
Generator (G) teams will be tested on their system's ability to generate content that is indistinguishable from human-generated content. For the pilot study, the evaluation will help determine strengths and weaknesses in their approaches including insights
NIST · ИТОфициальный источник · 2024-04-01
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"title_en": "2024 NIST Generative AI (GenAI): Evaluation Plan for Text-to-Text (T2T) Discriminators",
"designation": "",
"series": "",
"status": "",
"date": "2024-04-01",
"date_original": "April 1, 2024",
"url": "https://www.nist.gov/publications/2024-nist-generative-ai-genai-evaluation-plan-text-text-t2t-discriminators",
"source": "NIST Publications",
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"authors_en": "Yooyoung Lee , George Awad , Asad Butt , Lukas Diduch , Kay Peterson , Seungmin Seo , Ian Soboroff , Hariharan Iyer",
"abstract_excerpt_en": "Generator (G) teams will be tested on their system's ability to generate content that is indistinguishable from human-generated content. For the pilot study, the evaluation will help determine strengths and weaknesses in their approaches including insights",
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{
"title_en": "2024 NIST Generative AI (GenAI): Evaluation Plan for Text-to-Text (T2T) Discriminators",
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"date": "2024-04-01",
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"authors_en": "Yooyoung Lee , George Awad , Asad Butt , Lukas Diduch , Kay Peterson , Seungmin Seo , Ian Soboroff , Hariharan Iyer",
"abstract_excerpt_en": "Generator (G) teams will be tested on their system's ability to generate content that is indistinguishable from human-generated content. For the pilot study, the evaluation will help determine strengths and weaknesses in their approaches including insights"
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