AIMC Topic: Language

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Generative AI enhances individual creativity but reduces the collective diversity of novel content.

Science advances
Creativity is core to being human. Generative artificial intelligence (AI)-including powerful large language models (LLMs)-holds promise for humans to be more creative by offering new ideas, or less creative by anchoring on generative AI ideas. We st...

Exploring the potential of artificial intelligence to enhance the writing of english academic papers by non-native english-speaking medical students - the educational application of ChatGPT.

BMC medical education
BACKGROUND: Academic paper writing holds significant importance in the education of medical students, and poses a clear challenge for those whose first language is not English. This study aims to investigate the effectiveness of employing large langu...

Clinical efficacy of pre-trained large language models through the lens of aphasia.

Scientific reports
The rapid development of large language models (LLMs) motivates us to explore how such state-of-the-art natural language processing systems can inform aphasia research. What kind of language indices can we derive from a pre-trained LLM? How do they d...

Language-aware multiple datasets detection pretraining for DETRs.

Neural networks : the official journal of the International Neural Network Society
Pretraining on large-scale datasets can boost the performance of object detectors while the annotated datasets for object detection are hard to scale up due to the high labor cost. What we possess are numerous isolated filed-specific datasets, thus, ...

The Role of Humanization and Robustness of Large Language Models in Conversational Artificial Intelligence for Individuals With Depression: A Critical Analysis.

JMIR mental health
Large language model (LLM)-powered services are gaining popularity in various applications due to their exceptional performance in many tasks, such as sentiment analysis and answering questions. Recently, research has been exploring their potential u...

Continual pre-training mitigates forgetting in language and vision.

Neural networks : the official journal of the International Neural Network Society
Pre-trained models are commonly used in Continual Learning to initialize the model before training on the stream of non-stationary data. However, pre-training is rarely applied during Continual Learning. We investigate the characteristics of the Cont...

Personalized Language Model Selection Through Gamified Elicitation of Contrastive Concept Preferences.

IEEE transactions on visualization and computer graphics
Language models are widely used for different Natural Language Processing tasks while suffering from a lack of personalization. Personalization can be achieved by, e.g., fine-tuning the model on training data that is created by the user (e.g., social...

Assessing the risk of takeover catastrophe from large language models.

Risk analysis : an official publication of the Society for Risk Analysis
This article presents a risk analysis of large language models (LLMs), a type of "generative" artificial intelligence (AI) system that produces text, commonly in response to textual inputs from human users. The article is specifically focused on the ...

Speaking your language: The psychological impact of dialect integration in artificial intelligence systems.

Current opinion in psychology
As the popularity and adoption of Artificial Intelligence (AI) systems continue to rise, this article presents a promising proposition: the use of AI dialects to enhance AI perception. By delving into the potential of personalized AI dialects to augm...

Shared functional specialization in transformer-based language models and the human brain.

Nature communications
When processing language, the brain is thought to deploy specialized computations to construct meaning from complex linguistic structures. Recently, artificial neural networks based on the Transformer architecture have revolutionized the field of nat...