AIMC Topic: Language

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A boundary enhanced multi-task neural attention approach for Chinese named entity recognition.

Scientific reports
Named Entity Recognition (NER) stands as a fundamental task in Chinese information processing. However, it encounters unique difficulties due to the lack of explicit word boundaries in the Chinese language. This study proposes framing Chinese NER as ...

ChatGPT does not replicate human moral judgments: the importance of examining metrics beyond correlation to assess agreement.

Scientific reports
The rise of generative artificial intelligence has prompted claims that large language models (LLMs) can substitute for human participants, particularly in moral judgment tasks where correlations between ChatGPT and humans approach r = 1.00. In respo...

Leveraging Large Language Models to Identify Engagement-Driving Features in Vaping-Related TikTok Videos: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Electronic cigarette (e-cigarette) use is prevalent in youth and young adults in the United States. TikTok (ByteDance), a popular social media platform among youth and young adults, has become a key avenue for disseminating e-cigarette-re...

Reconstructing impaired language using generative AI for people with aphasia.

Scientific reports
In an era of Generative Artificial Intelligence (AI), it may be possible to capitalise on AI's generative capabilities to assist people in compensating for their impaired language. Large Language Models (LLMs) have emerged as a recent breakthrough, r...

Quantifying the speed-accuracy trade-off of large language models on oral and maxillofacial surgery multiple-choice questions.

Scientific reports
Large language models (LLMs) such as GPT-4o, Copilot and Gemini are entering dental curricula, yet their suitability for real-time decision support remains unclear because most evaluations report accuracy alone. This prospective in silico diagnostic-...

Comparative performance of large language models in answering periodontology questions from the Turkish Dental Specialty Examination: a cross-sectional study on accuracy and coverage.

BMC oral health
BACKGROUND: In recent years, several studies have explored the use of large language models (LLMs) such as ChatGPT-4, Claude, Gemini Advanced, and DeepSeek-R1 in dental education. Nevertheless, no study has yet reported a comparative evaluation of mu...

Artificial intelligence in anesthesia: comparison of the utility of ChatGPT v/s google gemini large language models in pre-anesthetic education: content, readability and sentiment analysis.

BMC anesthesiology
BACKGROUND: Large Language Models (LLMs) such as ChatGPT and Google Gemini are increasingly explored for their potential in patient education, particularly in the perioperative setting. As text-based tools trained on extensive datasets, they can gene...

Acceptance of healthcare services based on the large language model in China: a national cross-sectional study.

BMC public health
BACKGROUND: Increasing public acceptance of medical large language models will be beneficial for further leveraging their potential in reducing medical costs and improving efficiency. The objective of our research is to figure out the acceptance of h...

English-focused CL-HAMC with contrastive learning and hierarchical attention for multiple-choice reading comprehension.

Scientific reports
Multiple-choice questions constitute a critical format for assessing language application proficiency in standardized English tests, such as BEC and TOEIC. Developing explanatory content for such materials traditionally relies heavily on manual labor...

LLMs outperform outsourced human coders on complex textual analysis.

Scientific reports
This paper evaluates the effectiveness of large language models (LLMs) in extracting complex information from text data. Using a corpus of Spanish news articles, we compare how accurately various LLMs and outsourced human coders reproduce expert anno...