Cover Image

Triplet Feature Fusion for Equipment Anomaly Prediction : An Open-Source Methodology Using Small Foundation Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Yasuno, Takato
Format:	Preprint
Published:	2026
Subjects:	Machine Learning J.1; J.7; I.2.1
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Distributional Reinforcement Learning for Condition-Based Maintenance of Multi-Pump Equipment
by: Yasuno, Takato
Published: (2026)

Adapting Methods for Domain-Specific Japanese Small LMs: Scale, Architecture, and Quantization
by: Yasuno, Takato
Published: (2026)

Suppressing Domain-Specific Hallucination in Construction LLMs: A Knowledge Graph Foundation for GraphRAG and QLoRA on River and Sediment Control Technical Standards
by: Yasuno, Takato
Published: (2026)

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding
by: Rollman, John C., et al.
Published: (2025)

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters
by: van der Meer, Virgill, et al.
Published: (2026)

Hierarchical Dual-Head Model for Suicide Risk Assessment via MentalRoBERTa
by: Yang, Chang, et al.
Published: (2025)

PulmoVec: A Two-Stage Stacking Meta-Learning Architecture Built on the HeAR Foundation Model for Multi-Task Classification of Pediatric Respiratory Sounds
by: Akbasli, Izzet Turkalp, et al.
Published: (2026)

Fine-Tuning Vision-Language Models for Understanding Current Damage and Scoring Priority with Quality Guard Agent
by: Yasuno, Takato
Published: (2026)

Temporal Relation Extraction in Clinical Texts: A Span-based Graph Transformer Approach
by: Chaturvedi, Rochana, et al.
Published: (2025)

Large Language Models for History, Philosophy, and Sociology of Science: Interpretive Uses, Methodological Challenges, and Critical Perspectives
by: Simons, Arno, et al.
Published: (2025)

Model-free reinforcement learning with noisy actions for automated experimental control in optics
by: Richtmann, Lea, et al.
Published: (2024)

Assessing the Performance-Efficiency Trade-off of Foundation Models in Probabilistic Electricity Price Forecasting
by: Lettner, Jan Niklas, et al.
Published: (2026)

A Survey of Graph Neural Networks for Drug Discovery: Recent Developments and Challenges
by: Berry, Katherine, et al.
Published: (2025)

Parkinson's Disease Detection via Self-Supervised Dual-Channel Cross-Attention on Bilateral Wrist-Worn IMU Signals
by: Zannat, Meheru
Published: (2026)

Topography scanning as a part of process monitoring in power cable insulation process
by: Harjuhahto, Janne, et al.
Published: (2026)

PhenoLinker: Phenotype-Gene Link Prediction and Explanation using Heterogeneous Graph Neural Networks
by: Andreu, Jose L. Mellina, et al.
Published: (2024)

Heterogeneous Variational Inference for Markov Degradation Hazard Models: Discretized Mixture with Interpretable Clusters
by: Yasuno, Takato
Published: (2026)

BLT: Can Large Language Models Handle Basic Legal Text?
by: Blair-Stanek, Andrew, et al.
Published: (2023)

Spatially Resolved Meteorological and Ancillary Data in Central Europe for Rainfall Streamflow Modeling
by: Vischer, Marc Aurel, et al.
Published: (2025)

When Reasoning Fails: Evaluating 'Thinking' LLMs for Stock Prediction
by: Sodha, Rakeshkumar H
Published: (2025)

Unsupervised Discovery of Clinical Disease Signatures Using Probabilistic Independence
by: Lasko, Thomas A., et al.
Published: (2024)

A Domain Knowledge Informed Approach for Anomaly Detection of Electric Vehicle Interior Sounds
by: Kunte, Deepti, et al.
Published: (2025)

Interactive Diabetes Risk Prediction Using Explainable Machine Learning: A Dash-Based Approach with SHAP, LIME, and Comorbidity Insights
by: Allani, Udaya
Published: (2025)

An AI Implementation Science Study to Improve Trustworthy Data in a Large Healthcare System
by: Marteau, Benoit L., et al.
Published: (2025)

Robust Multi-Omics Integration from Incomplete Modalities Significantly Improves Prediction of Alzheimer's Disease
by: Park, Sungjoon, et al.
Published: (2025)

Hierarchical Pooling and Explainability in Graph Neural Networks for Tumor and Tissue-of-Origin Classification Using RNA-seq Data
by: Fontanari, Thomas Vaitses, et al.
Published: (2026)

Understanding Deterioration Random Effects for Causal Discovery in Infrastructure Management
by: Yasuno, Takato
Published: (2026)

The Judge Variable: Challenging Judge-Agnostic Legal Judgment Prediction
by: Zambrano, Guillaume
Published: (2025)

Towards AI-Architecture Liberty: A Comprehensive Survey on Design and Generation of Virtual Architecture by Deep Learning
by: Wang, Anqi, et al.
Published: (2023)

Artificial Intelligence-Assistant Cardiotocography: Unified Model for Signal Reconstruction, Fetal Heart Rate Analysis, and Variability Assessment
by: Wang, Xiaohua, et al.
Published: (2026)

AxOCS: Scaling FPGA-based Approximate Operators using Configuration Supersampling
by: Sahoo, Siva Satyendra, et al.
Published: (2023)

Multi-modal Integration Analysis of Alzheimer's Disease Using Large Language Models and Knowledge Graphs
by: Kiguchi, Kanan, et al.
Published: (2025)

RAPTOR-AI for Disaster OODA Loop: Hierarchical Multimodal RAG with Experience-Driven Agentic Decision-Making
by: Yasuno, Takato
Published: (2026)

Feature graphs for interpretable unsupervised tree ensembles: centrality, interaction, and application in disease subtyping
by: Sirocchi, Christel, et al.
Published: (2024)

Deep Policy Iteration with Integer Programming for Inventory Management
by: Harsha, Pavithra, et al.
Published: (2021)

Antibody Design and Optimization with Multi-scale Equivariant Graph Diffusion Models for Accurate Complex Antigen Binding
by: Chen, Jiameng, et al.
Published: (2025)

GNN-Suite: a Graph Neural Network Benchmarking Framework for Biomedical Informatics
by: Kamp, Sebestyén, et al.
Published: (2025)

SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts
by: Banegas-Luna, Antonio Jesús, et al.
Published: (2022)

Understanding Clinical Decision-Making in Traditional East Asian Medicine through Dimensionality Reduction: An Empirical Investigation
by: Bae, Hyojin, et al.
Published: (2024)

Beyond One-Time Validation: A Framework for Adaptive Validation of Prognostic and Diagnostic AI-based Medical Devices
by: Hellmeier, Florian, et al.
Published: (2024)