Comparing the performance of ChatGPT and state-of-the-art climate NLP models on climate-related text classification tasks
Comparing the performance of ChatGPT and state-of-the-art climate NLP models on climate-related text classification tasks
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比较 ChatGPT 和最先进的气候 NLP 模型在气候相关文本分类任务上的性能
DOI：
10.1051/e3sconf/202343602004
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发表时间：
2023
影响因子：
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通讯作者：
Vodenska, Irena
中科院分区：
文献类型：
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作者：
Trajanov, Dimitar;Lazarev, Gorgi;Chitkushev, Ljubomir;Vodenska, Irena
最近，通用语言模型激增，ChatGPT是迄今为止最先进的模型。这些模型主要用于生成文本，以响应用户对各种主题的提示。需要验证ChatGPT生成的文本在特定主题上的准确性和相关性，因为它是为一般对话而设计的，而不是用于特定于上下文的目的。这项研究探讨了ChatGPT作为一个通用模型，如何在现实世界的挑战（如气候变化）的背景下与ClimateBert（一种最先进的语言模型）进行比较，ClimateBert是一种专门针对来自各种来源的气候相关数据进行训练的语言模型，包括文本，新闻和论文。ClimateBert在五个不同的NLP分类任务上进行了微调，使其成为与ChatGPT在各种NLP任务上进行比较的有价值的基准。主要结果表明，对于气候特定的NLP任务，ClimateBert优于ChatGPT。
Recently, there has been a surge in general-purpose language models, with ChatGPT being the most advanced model to date. These models are primarily used for generating text in response to user prompts on various topics. It needs to be validated how accurate and relevant the generated text from ChatGPT is on the specific topics, as it is designed for general conversation and not for context-specific purposes. This study explores how ChatGPT, as a general-purpose model, performs in the context of a real-world challenge such as climate change compared to ClimateBert, a state-of-the-art language model specifically trained on climate-related data from various sources, including texts, news, and papers. ClimateBert is fine-tuned on five different NLP classification tasks, making it a valuable benchmark for comparison with the ChatGPT on various NLP tasks. The main results show that for climate-specific NLP tasks, ClimateBert outperforms ChatGPT.
“未来一无所有”是什么意思？
DOI：
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发表时间：
2003
期刊：
Annual Review of the Philosophical Association of Western Japan No.11
影响因子：
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作者：
高橋隆雄(編著);入不二 基義;谷 隆一郎;Irifuji Motoyoshi;高橋隆雄(編著);Irifuji Motoyoshi
通讯作者：
Irifuji Motoyoshi