Results 121 to 130 of about 9,156,471 (236)

Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios, Léon Chiriatti, Simon Poppinga, Thomas Speck, Vincent Le Houérou   +4 more
wiley   +1 more source

Rule-Guided Graph Neural Networks for Explainable Knowledge Graph Reasoning

The connections between symbolic rules and neural networks have been explored in various directions, including rule mining through neural networks and rule-based explanation for neural networks.
Wang, Zhe, Zhuang, Zhiqiang, Wang, Z, Ma, S, Ma, Suxue, Wang, Kewen, Wang, K, Zhuang, Z   +7 more
core   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jan‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

Multi-hop question answering by integrating large language models and knowledge graphs

Dianxin kexue
With the widespread application of large language models (LLM) in natural language processing tasks, improving their performance in domain-specific question answering has become a key research focus.
JIANG Xian, WANG Hanyi, YANG Shiting, CHEN Xingyu, ZHOU Mengyao, DONG Ligang   +5 more
doaj  

Dynamic Cognition Graph for Adaptive Learning: Integrating Reasoning Evidence and Reinforcement Learning

Applied Sciences
Accurate modeling of learners’ evolving cognitive states is essential for intelligent educational systems, yet many existing knowledge tracing and graph-based approaches rely on static structures or purely sequential representations that inadequately ...
Ying Li, Yiming Gai, Xingyu Wang, Leilei Sun, Xuefei Huang   +4 more
doaj   +1 more source

Temporal Knowledge Graph Reasoning Based on Entity Relationship Similarity Perception

Temporal knowledge graphs (TKGs) are used for dynamically modeling facts in the temporal dimension, and are widely used in various fields. However, existing reasoning models often fail to consider the similarity features between entity relationships and ...
Xunyang Ji, Mengxing Huang, Cong Zhou, Siling Feng, Qian Liu   +4 more
core   +1 more source

Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers

Advanced Intelligent Systems, EarlyView.
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley   +1 more source

A survey on the application and research progress of large language models in financial forecasting

AIP Advances
Large language models (LLMs) are reshaping the technical paradigms of financial forecasting through their robust representation learning and reasoning capabilities.
Ruonan Wu, Hong Liu
doaj   +1 more source

Plugging Small Models in Large Language Models for POI Recommendation in Smart Tourism

Algorithms
Point-of-interest (POI) recommendation is a crucial task in location-based social networks, especially for enhancing personalized travel experiences in smart tourism.
Hong Zheng, Zhenhui Xu, Qihong Pan, Zhenzhen Zhao, Xiangjie Kong   +4 more
doaj   +1 more source

The Collective Power of Bacteria as a Blueprint for Emergent Intelligence

Advanced Intelligent Systems, EarlyView.
Small cells, powerful collectives. Bacteria demonstrate how sophisticated behaviors can emerge from many simple individuals working together. We explore the remarkable world of bacterial communities and the mechanisms that underpin their complex emergent behaviors, enabling impressive adaptability, robustness, and responsiveness to changing ...
Johanna A. Blee, Thomas E. Gorochowski, Sabine Hauert   +2 more
wiley   +1 more source