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AI Open
Scopus
ISSN 2666-6510 · KeAi Communications Co. Ltd. · 108 artikel di indeks
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Artikel Jurnal
Integrating cross-view multi-scale perception and RAG-enabled expert fusion for medical prediction
Electronic Health Records (EHRs) continuously monitor patients’ health status in Intensive Care Units (ICUs), capturing irregular numerical time-series data and unstructured clinical text. While existing studies primarily focus on handling modality irregularities, they often overlook the complex…
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Artikel Jurnal
Knowledge intensive agents
Large Language Models (LLMs) have exhibited impressive capabilities in reasoning and language understanding. However, their reliance on memorized knowledge and tendency to generate hallucinated content limit their reliability in real-world applications. Retrieval-Augmented Generation (RAG)…
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Artikel Jurnal
Bio-inspired adaptive neurons for dynamic weighting in Artificial Neural Networks
Traditional neural networks employ fixed weights during inference, limiting their ability to adapt to changing input conditions, unlike biological neurons that adjust signal strength dynamically based on stimuli. This discrepancy between artificial and biological neurons constrains neural network…
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Artikel Jurnal
WorldArena: A unified benchmark for evaluating perception and functional utility of embodied world models
While world models have emerged as a cornerstone of embodied intelligence by enabling agents to reason about environmental dynamics through action-conditioned prediction, their evaluation remains fragmented. Current evaluation of embodied world models has largely focused on perceptual fidelity…
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Artikel Jurnal
LLMKG＋: Systematically improving knowledge quality and coverage in KGs using LLMs – A case study in medical domain
Knowledge graphs (KGs) encode structured information about real-world entities and their relations, supporting core NLP tasks such as question answering and retrieval. Existing LLM-based methods for knowledge extraction and fusion often struggle to balance quality and coverage when adapting to…
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Artikel Jurnal
Symbolic learning enables self-evolving agents
The AI community has been exploring a pathway to artificial general intelligence (AGI) by developing “language agents”, which are complex large language models (LLMs) workflows involving both prompting techniques and tool usage methods. While language agents have demonstrated impressive…
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Artikel Jurnal
Advancing AI for science: From the revolution of tools to the tools for revolution
Scientific research is not a linear pipeline but a dynamic system built upon the ever-shifting interactions among three elements — research objects, tools, and researchers. And sustained progress depends on how quickly insights circulate within this network, not on optimizing a single node in…
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Artikel Jurnal
AI-generated content in landscape architecture: A survey
Landscape design is a complex process that requires designers to engage in intricate planning, analysis, and decision-making. This process involves the integration and reconstruction of science, art, and technology. Traditional landscape design methods are shaped by various factors, including the…
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Artikel Jurnal
ADAP: Adaptive & Dynamic Arc Padding for predicting seam profiles in Multi-Layer-Multi-Pass robotic welding
Welding thick metal plates using Multi-Layer-Multi-Pass (MLMP) techniques demands precise control over the weld seam profile as it evolves during the cooling process. In MLMP welding, typically executed with Gas Metal Arc Welding (GMAW) and shielding gas protection, the continuous deposition of…
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Artikel Jurnal
From tools to partners: How large language models are transforming urban planning
Recent advances in large language models have transformed urban planning from passive tool-assisted workflows to active human–AI collaborative partnerships, enabling natural language-driven design generation, multi-agent stakeholder simulation, and intelligent decision support. This survey…
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Artikel Jurnal
Computer audition for healthcare: A survey on speech analysis
Intelligent speech analysis (ISA) constitutes a significant component within the realm of computer audition (CA) technology. Speech, as a fundamental tool for human communication, not only conveys rich semantic information but also holds significant potential for various healthcare applications…
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Artikel Jurnal
Multi-scale texture loss for CT denoising with GANs
Generative Adversarial Networks (GANs) have proved as a powerful framework for denoising applications in medical imaging. However, GAN-based denoising algorithms still suffer from limitations in capturing complex relationships within the images. In this regard, the loss function plays a crucial…
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Artikel Jurnal
Robust emotion recognition using hybrid Bayesian LSTM based on Laban movement analysis
Emotion recognition has become increasingly significant in artificial intelligence; however, the impact of body movements on emotion interpretation remains under-explored. This paper presents a novel Hybrid Bayesian Pre-trained Long Short-Term Memory (HBP-LSTM) framework that combines low-level…
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Artikel Jurnal
Scalable graph attention-based instance selection via mini-batch sampling and hierarchical hashing
Instance selection (IS) addresses the critical challenge of reducing dataset size while keeping informative characteristics, becoming increasingly important as datasets grow to millions of instances. Current IS methods often struggle with capturing complex relationships in high-dimensional spaces…
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Artikel Jurnal
Proactive Recommendation in Social Networks: Steering user interest with causal inference
Recommending items that solely cater to users’ historical interests narrows users’ horizons. Recent works have considered steering target users beyond their historical interests by directly adjusting items exposed to them. However, the recommended items for direct steering might not align perfectly…
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Artikel Jurnal
Client: Cross-variable linear integrated enhanced transformer for multivariate long-term time series forecasting
Long-term time series forecasting (LTSF) is crucial in modern society, playing a pivotal role in facilitating long-term planning and developing early warning systems. While many Transformer-based models have recently been introduced for LTSF, a doubt has been raised regarding the effectiveness of…
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Artikel Jurnal
SafeCast: Risk-responsive motion forecasting for autonomous vehicles
Accurate motion forecasting is essential for the safety and reliability of autonomous driving (AD) systems. While existing methods have made significant progress, they often overlook explicit safety constraints and struggle to capture the complex interactions among traffic agents, environmental…
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Artikel Jurnal
FedGPA: Federated Learning with Global Personalized Aggregation
A significant challenge in Federated Learning (FL) is addressing the heterogeneity of local data distribution across clients. Personalized Federated Learning (PFL), an emerging method aimed at overcoming data heterogeneity, can either integrate personalized components into the global model or train…
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Artikel Jurnal
DFM: Dialogue foundation model for universal large-scale dialogue-oriented task learning
Building a universal conversational agent has been a long-standing goal of the dialogue research community. Most previous works only focus on a small set of dialogue tasks. In this work, we aim to build a unified dialogue foundation model (DFM) which can be used to solve massive diverse dialogue…