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Linguistics

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The linguistic feedback of tourism robots significantly influences visitors' ecotourism behaviors.

Scientific reports
With the extensive application of artificial intelligence technology in the tourism industry, robot-assisted tourism has become a vital strategy for enhancing tourist experiences and promoting sustainable tourism practices. This study aims to explore...

Derivational morphology reveals analogical generalization in large language models.

Proceedings of the National Academy of Sciences of the United States of America
What mechanisms underlie linguistic generalization in large language models (LLMs)? This question has attracted considerable attention, with most studies analyzing the extent to which the language skills of LLMs resemble rules. As of yet, it is not k...

Deep neural networks and humans both benefit from compositional language structure.

Nature communications
Deep neural networks drive the success of natural language processing. A fundamental property of language is its compositional structure, allowing humans to systematically produce forms for new meanings. For humans, languages with more compositional ...

The intuitionistic fuzzy linguistic assessment of forest soil quality with multi-granularity qualitative information.

Environmental monitoring and assessment
The soil quality of forest land is directly related to the growth of forest trees and the local ecological environment. This paper proposes an intuitionistic fuzzy linguistic aggregation method for heterogeneous linguistic assessment information, to ...

Development of compositionality through interactive learning of language and action of robots.

Science robotics
Humans excel at applying learned behavior to unlearned situations. A crucial component of this generalization behavior is our ability to compose/decompose a whole into reusable parts, an attribute known as compositionality. One of the fundamental que...

Incremental accumulation of linguistic context in artificial and biological neural networks.

Nature communications
Large Language Models (LLMs) have shown success in predicting neural signals associated with narrative processing, but their approach to integrating context over large timescales differs fundamentally from that of the human brain. In this study, we s...

Linguistic cues for automatic assessment of Alzheimer's disease across languages.

Journal of Alzheimer's disease : JAD
BackgroundMost common forms of dementia, including Alzheimer's disease, are associated with alterations in spoken language.ObjectiveThis study explores the potential of a speech-based machine learning (ML) approach in estimating cognitive impairment,...

[Technical foundations of large language models].

Radiologie (Heidelberg, Germany)
BACKGROUND: Large language models (LLMs) such as ChatGPT have rapidly revolutionized the way computers can analyze human language and the way we can interact with computers.

Enhancing counterfactual detection in multilingual contexts using a few shot clue phrase approach.

Scientific reports
This research paper introduces an innovative counterfactual detection system, designed to tackle the complexities of identifying hypothetical statements that describe non-occurring events in diverse fields such as NLP, psychology, medicine, politics,...

Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis.

Journal of medical Internet research
BACKGROUND: The opioid epidemic in the United States remains a major public health concern, with opioid-related deaths increasing more than 8-fold since 1999. Chronic pain, affecting 1 in 5 US adults, is a key contributor to opioid use and misuse. Wh...