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PersonalityScanner: Exploring the Validity of Personality Assessment Based on Multimodal Signals in Virtual Reality

Autor: Zhang, Xintong, Lu, Di, Hu, Huiqi, Jiang, Nan, Yu, Xianhao, Xu, Jinan, Peng, Yujia, Li, Qing, Han, Wenjuan

Human cognition significantly influences expressed behavior and is intrinsically tied to authentic personality traits. Personality assessment plays a pivotal role in various fields, including psychology, education, social media, etc. However, traditi

Externí odkaz: http://arxiv.org/abs/2407.19728

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Evaluating and Modeling Social Intelligence: A Comparative Study of Human and AI Capabilities

Autor: Wang, Junqi, Zhang, Chunhui, Li, Jiapeng, Ma, Yuxi, Niu, Lixing, Han, Jiaheng, Peng, Yujia, Zhu, Yixin, Fan, Lifeng

Facing the current debate on whether Large Language Models (LLMs) attain near-human intelligence levels (Mitchell & Krakauer, 2023; Bubeck et al., 2023; Kosinski, 2023; Shiffrin & Mitchell, 2023; Ullman, 2023), the current study introduces a benchmar

Externí odkaz: http://arxiv.org/abs/2405.11841

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MEWL: Few-shot multimodal word learning with referential uncertainty

Autor: Jiang, Guangyuan, Xu, Manjie, Xin, Shiji, Liang, Wei, Peng, Yujia, Zhang, Chi, Zhu, Yixin

Without explicit feedback, humans can rapidly learn the meaning of words. Children can acquire a new word after just a few passive exposures, a process known as fast mapping. This word learning capability is believed to be the most fundamental buildi

Externí odkaz: http://arxiv.org/abs/2306.00503

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