519894da9e885bb1d82e · From Traditional Topic Models to LLM Topic Models: Can Large Language Models Replace Traditional Topic Models?
From Traditional Topic Models to LLM Topic Models: Can Large Language Models Replace Traditional Topic Models?
A common use of NLP is to facilitate the understanding of large document collections, with models based on Large Language Models (LLMs) replacing probabilistic topic models. Yet the effectiveness of LLM-based approaches in real-world applications remains
{
"title_en": "From Traditional Topic Models to LLM Topic Models: Can Large Language Models Replace Traditional Topic Models?",
"designation": "",
"series": "",
"status": "",
"date": "2025-08-01",
"date_original": "August 1, 2025",
"url": "https://www.nist.gov/publications/traditional-topic-models-llm-topic-models-can-large-language-models-replace-traditional",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Zongxia Li , Lorena Calvo Bartolome, Alexander Hoyle, Daniel Stephens , Paiheng Xu, Alden Dima , Jordan Boyd-Graber, Juan Fung",
"abstract_excerpt_en": "A common use of NLP is to facilitate the understanding of large document collections, with models based on Large Language Models (LLMs) replacing probabilistic topic models. Yet the effectiveness of LLM-based approaches in real-world applications remains",
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"sources": [
"NIST Publications"
],
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{
"title_en": "From Traditional Topic Models to LLM Topic Models: Can Large Language Models Replace Traditional Topic Models?",
"designation": "",
"series": "",
"status": "",
"date": "2025-08-01",
"date_original": "August 1, 2025",
"url": "https://www.nist.gov/publications/traditional-topic-models-llm-topic-models-can-large-language-models-replace-traditional",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Zongxia Li , Lorena Calvo Bartolome, Alexander Hoyle, Daniel Stephens , Paiheng Xu, Alden Dima , Jordan Boyd-Graber, Juan Fung",
"abstract_excerpt_en": "A common use of NLP is to facilitate the understanding of large document collections, with models based on Large Language Models (LLMs) replacing probabilistic topic models. Yet the effectiveness of LLM-based approaches in real-world applications remains"
}
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