Research Result. Theoretical and Applied Linguistics
Volume 10, Issue №4, 2024
PDF
EDITORIAL
Writing in the era of large language models: a bibliometric analysis of research field
The widespread adoption of large language models (LLMs) and chatbots over the past two years has significantly altered writing practices. This editorial paper aims to conduct a bibliometric analysis ...
Human Language Behaviour in Machine-Generated Environments
Technosemantics of gesture: on the possibilities of using Perm sign notation in software-generated environments
This paper is dedicated to the development of a concept and software solution for generating human movements based on a semantically-oriented language notation created by the authors. The language ...
Investigating between-word pause duration in Russian typed texts using mixture modeling based on keystroke data
Keystroke logging is an objective and scalable methodology that has become the gold standard in writing research for modeling writing processes. A particularly significant aspect of this analysis is ...
Large Language Models and Prompt Engineering in Linguistics
Using neural network technologies in determining the emotional state of a person in oral communication
Human oral speech often has an emotional connotation; this is due to the fact that emotions and our mood influence the physiology of the vocal tract and, as a ...
Prompt injection – the problem of linguistic vulnerabilities of large language models at the present stage
The article examines the phenomenon of “prompt injection” in the context of contemporary large language models (LLMs), elucidating a significant challenge for AI developers and researchers. The study comprises ...
Artificial vs human intelligence: a case study of translating jokes based on wordplay
Artificial intelligence (AI) technologies used in professional translation question the effectiveness of human-AI interaction. Deep learning can mimic human cognitive processes, accordingly suggesting that AI could reproduce the logic ...
Combining the tasks of entity linking and relation extraction using a unified neural network model
In this paper we describe methods for training neural network models for extracting pharmacologically significant entities from natural language texts with their further transformation into a formalized form of ...
Using CNN and LSTM neural networks for Arkhangelsk dialect word identification and classification
The study of dialects provides an opportunity to gain an understanding of the culture and history of a people, which are reflected in language. Dialectal vocabulary differs from standard ...
