AIMC Topic: Problem Solving

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Potential cognitive risks of generative transformer-based AI chatbots on higher order executive functions.

Neuropsychology
BACKGROUND: Chat generative retrained transformer (ChatGPT) represents a groundbreaking advancement in Artificial Intelligence (AI-chatbot) technology, utilizing transformer algorithms to enhance natural language processing and facilitating their use...

Solving olympiad geometry without human demonstrations.

Nature
Proving mathematical theorems at the olympiad level represents a notable milestone in human-level automated reasoning, owing to their reputed difficulty among the world's best talents in pre-university mathematics. Current machine-learning approaches...

Automated Paper Screening for Clinical Reviews Using Large Language Models: Data Analysis Study.

Journal of medical Internet research
BACKGROUND: The systematic review of clinical research papers is a labor-intensive and time-consuming process that often involves the screening of thousands of titles and abstracts. The accuracy and efficiency of this process are critical for the qua...

Assessment of the capacity of ChatGPT as a self-learning tool in medical pharmacology: a study using MCQs.

BMC medical education
BACKGROUND: ChatGPT is a large language model developed by OpenAI that exhibits a remarkable ability to simulate human speech. This investigation attempts to evaluate the potential of ChatGPT as a standalone self-learning tool, with specific attentio...

Knowledge graph and CBR-based approach for automated analysis of bridge operational accidents: Case representation and retrieval.

PloS one
Bridge operational accident analysis is a critical process in bridge operational risk management. It provides valuable knowledge support for responding to newly occurring accidents. However, there are three issues: (1) research specifically focused o...

TGDAUNet: Transformer and GCNN based dual-branch attention UNet for medical image segmentation.

Computers in biology and medicine
Accurate and automatic segmentation of medical images is a key step in clinical diagnosis and analysis. Currently, the successful application of Transformers' model in the field of computer vision, researchers have begun to gradually explore the appl...

Two-timescale projection neural networks in collaborative neurodynamic approaches to global optimization and distributed optimization.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a two-timescale projection neural network (PNN) for solving optimization problems with nonconvex functions. We prove the convergence of the PNN with sufficiently different timescales to a local optimal solution. We develop a...

Enhancing neurodynamic approach with physics-informed neural networks for solving non-smooth convex optimization problems.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a deep learning approach for solving non-smooth convex optimization problems (NCOPs), which have broad applications in computer science, engineering, and physics. Our approach combines neurodynamic optimization with physics-inform...

Scene context is predictive of unconstrained object similarity judgments.

Cognition
What makes objects alike in the human mind? Computational approaches for characterizing object similarity have largely focused on the visual forms of objects or their linguistic associations. However, intuitive notions of object similarity may depend...

A survey on neural-symbolic learning systems.

Neural networks : the official journal of the International Neural Network Society
In recent years, neural systems have demonstrated highly effective learning ability and superior perception intelligence. However, they have been found to lack effective reasoning and cognitive ability. On the other hand, symbolic systems exhibit exc...