ARTIFICIAL INTELLIGENCE REVIEW
ARTIFICIAL INTELLIGENCE REVIEW(英文缩写 ARTIF INTELL REV),ISSN 0269-2821,eISSN 1573-7462 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
指标来源：jcr_cas_ifqb
期刊简介
暂无简介。
历年影响因子趋势
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ARTIFICIAL INTELLIGENCE REVIEW 最新收录文献
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Super greedy trees.
We introduce Super Greedy Trees (SGTs), a decision-tree framework that extends CART by constructing tree splits from lasso-penalized parametric models. At each tree node, a model fitted to the local d…
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Topological data analysis and topological deep learning beyond persistent homology: a review.
Topological data analysis (TDA) is a rapidly evolving field in applied mathematics and data science that leverages tools from topology to uncover robust, shape-driven, and explainable insights in comp…
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An auditable pipeline for fuzzy full-text screening in systematic reviews: integrating contrastive semantic highlighting and LLM judgment.
Full-text screening is the major bottleneck of systematic reviews (SRs), particularly in domains such as population health modelling of noncommunicable diseases (NCDs), where decisive eligibility info…
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Quantum adversarial machine learning: from classical adaptations to quantum-native methods.
Machine learning has revolutionized numerous industrial domains. Despite recent advances, machine learning models remain vulnerable to adversarial threats. Adversarial machine learning is a field that…
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Artificial neural networks fighting real neural decline: a systematic review of AI in Alzheimer's research.
Alzheimer's disease (AD) is a major global health challenge, with Artificial Intelligence (AI) increasingly recognized as a transformative tool for early detection, disease progression modeling, and t…
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Advances in artificial intelligence: a review for the creative industries.
Artificial intelligence (AI) has undergone transformative advances since 2022, particularly through generative AI, large language models (LLMs), and diffusion models, fundamentally reshaping the creat…
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Exploring unanswerability in machine reading comprehension: approaches, benchmarks, and open challenges.
The challenge of unanswerable questions in Machine Reading Comprehension (MRC) has drawn considerable attention, as current MRC systems are typically designed under the assumption that every question …
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Knowledge distillation and dataset distillation of large language models: emerging trends, challenges, and future directions.
The exponential growth of Large Language Models (LLMs) continues to highlight the need for efficient strategies to meet ever-expanding computational and data demands. This survey provides a comprehens…
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Validation is the central challenge for generative social simulation: a critical review of LLMs in agent-based modeling.
Recent advances in Large Language Models (LLMs) have revitalized interest in Agent-Based Models (ABMs) by enabling "generative" simulations, with agents that can plan, reason, and interact through nat…
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Artificial intelligence in four-dimensional imaging for motion management in radiation therapy.
Four-dimensional imaging (4D-imaging) plays a critical role in achieving precise motion management in radiation therapy. However, challenges remain in 4D-imaging such as a long imaging time, suboptima…