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20232026
most citedGeo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages

187 citations · 334 across the 15 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CV2023★ 7 cited

On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications

Chenjiao Tan, Qian Cao, Yiwei Li +15

The advent of large language models (LLMs) has heightened interest in their potential for multimodal applications that integrate language and vision. This paper explores the capabi…

cs.AI2023★ 26 cited

Multimodality of AI for Education: Towards Artificial General Intelligence

Gyeong-Geon Lee, Lehong Shi, Ehsan Latif +10

This paper presents a comprehensive examination of how multimodal artificial intelligence (AI) approaches are paving the way towards the realization of Artificial General Intellige…

cs.AI2023★ 16 cited

Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities

Zhengliang Liu, Yiwei Li, Qian Cao +9

Recent advances in artificial general intelligence (AGI), particularly large language models and creative image generation systems have demonstrated impressive capabilities on dive…

cs.CY2023★ 187 cited

Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages

Yingjie Hu, Gengchen Mai, Chris Cundy +6

Social media messages posted by people during natural disasters often contain important location descriptions, such as the locations of victims. Recent research has shown that many…

cs.AI2023★ 32 cited

Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges

Fei Dou, Jin Ye, Geng Yuan +22

Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrig…