AIMC Topic: Knowledge

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Deep learning based knowledge tracing in intelligent tutoring systems.

Scientific reports Jul 1, 2025
The emergence of online education, e.g., intelligent tutoring system (ITS), complements or partially replaces conventional offline education, especially during the COVID-19 pandemic. Knowledge tracing (KT) plays a pivotal role in the intelligent tuto...
Neural Networks, Computer COVID-19 Humans Knowledge Education, Distance SARS-CoV-2 Deep Learning
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Tailored knowledge distillation with automated loss function learning.

PloS one Jun 11, 2025
Knowledge Distillation (KD) is one of the most effective and widely used methods for model compression of large models. It has achieved significant success with the meticulous development of distillation losses. However, most state-of-the-art KD loss...
Distillation Machine Learning Algorithms Learning Knowledge Humans Neural Networks, Computer
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Classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing.

PloS one Apr 7, 2025
In order to accurately assess the students' learning process and the cognitive state of knowledge points in smart classroom. A classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing model (CL-PTKT...
Knowledge Learning Students Schools Attention Neural Networks, Computer Humans Algorithms
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Bridging the human-AI knowledge gap through concept discovery and transfer in AlphaZero.

Proceedings of the National Academy of Sciences of the United States of America Mar 26, 2025
AI systems have attained superhuman performance across various domains. If the hidden knowledge encoded in these highly capable systems can be leveraged, human knowledge and performance can be advanced. Yet, this internal knowledge is difficult to ex...
Knowledge Humans Artificial Intelligence
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The need for epistemic humility in AI-assisted pain assessment.

Medicine, health care, and philosophy Mar 15, 2025
It has been difficult historically for physicians, patients, and philosophers alike to quantify pain given that pain is commonly understood as an individual and subjective experience. The process of measuring and diagnosing pain is often a fraught an...
Trust Pain Measurement Humans Artificial Intelligence Pain Management Knowledge
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AI anxiety and knowledge payment: the roles of perceived value and self-efficacy.

BMC psychology Mar 6, 2025
BACKGROUND: The integration of Artificial Intelligence (AI) into daily life raises significant challenges and uncertainties, notably concerning job security and skill relevance. This has led to the emergence of 'AI anxiety'-a stress response to poten...
Self Efficacy Knowledge Middle Aged Anxiety Female Young Adult Adult Male Humans Artificial Intelligence
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Hermeneutics as impediment to AI in medicine.

Theoretical medicine and bioethics Feb 26, 2025
Predictions that artificial intelligence (AI) will become capable of replacing human beings in domains such as medicine rest implicitly on a theory of mind according to which knowledge can be captured propositionally without loss of meaning. Generati...
Humans Artificial Intelligence Knowledge Hermeneutics Philosophy, Medical
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Dual view graph transformer networks for multi-hop knowledge graph reasoning.

Neural networks : the official journal of the International Neural Network Society Feb 14, 2025
To address the incompleteness of knowledge graphs, multi-hop reasoning aims to find the unknown information from existing data and enhance the comprehensive understanding. The presence of reasoning paths endows multi-hop reasoning with interpretabili...
Algorithms Knowledge Humans Neural Networks, Computer
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Knowledge-Guided Semantically Consistent Contrastive Learning for sequential recommendation.

Neural networks : the official journal of the International Neural Network Society Jan 23, 2025
Contrastive learning has gained dominance in sequential recommendation due to its ability to derive self-supervised signals for addressing data sparsity problems. However, caused by random augmentations (e.g., crop, mask, and reorder), existing metho...
Neural Networks, Computer Machine Learning Humans Semantics Knowledge
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A rule- and query-guided reinforcement learning for extrapolation reasoning in temporal knowledge graphs.

Neural networks : the official journal of the International Neural Network Society Jan 21, 2025
Extrapolation reasoning in temporal knowledge graphs (TKGs) aims at predicting future facts based on historical data, and finds extensive application in diverse real-world scenarios. Existing TKG reasoning methods primarily focus on capturing the fac...
Reinforcement, Psychology Semantics Humans Knowledge Machine Learning Neural Networks, Computer
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