Zobrazeno 1 - 10
of 963
pro vyhledávání: '"Hale, John"'
Humans understand sentences word-by-word, in the order that they hear them. This incrementality entails resolving temporary ambiguities about syntactic relationships. We investigate how humans process these syntactic ambiguities by correlating predic
Externí odkaz:
http://arxiv.org/abs/2401.18046
Autor:
Liu, Zhengliang, Li, Yiwei, Cao, Qian, Chen, Junwen, Yang, Tianze, Wu, Zihao, Hale, John, Gibbs, John, Rasheed, Khaled, Liu, Ninghao, Mai, Gengchen, Liu, Tianming
Recent advances in artificial general intelligence (AGI), particularly large language models and creative image generation systems have demonstrated impressive capabilities on diverse tasks spanning the arts and humanities. However, the swift evoluti
Externí odkaz:
http://arxiv.org/abs/2310.19626
To model behavioral and neural correlates of language comprehension in naturalistic environments researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, p
Externí odkaz:
http://arxiv.org/abs/2210.16147
Pro-drop is commonly seen in many languages, but its discourse motivations have not been well characterized. Inspired by the topic chain theory in Chinese, this study shows how character-verb usage continuity distinguishes dropped pronouns from overt
Externí odkaz:
http://arxiv.org/abs/2209.07961
Publikováno v:
ICML 2022 - 39th International Conference on Machine Learning, Jul 2022, Baltimore, United States. pp.18
Neural Language Models (NLMs) have made tremendous advances during the last years, achieving impressive performance on various linguistic tasks. Capitalizing on this, studies in neuroscience have started to use NLMs to study neural activity in the hu
Externí odkaz:
http://arxiv.org/abs/2207.03380