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1,432 papers
This study investigates how employees in a energy company understand AI adoption and identifies areas where AI and LLMs-based agentic workflows could assist daily activities, including reporting work, forecasting, data handling, maintenance-related tasks, and anomaly detection.
This is one of the first reviews to integrate peer-reviewed and grey literature on vibe coding under a single documented protocol and is strongest for prototyping and user-interface work and weakest for production, data-intensive, and safety-critical use, and tool visibility does not imply effectiveness.
The results indicate that the proposed approach reduces the effort required for manual dataset construction while preserving data quality through mandatory human validation, and highlights the effectiveness of hybrid automation workflows in accelerating fine-tuning dataset preparation without compromising reliability.
A variability-preserving imputation method is introduced that augments linear interpolation with locally adaptive stochastic noise, retaining physiological dynamics essential for accurate forecasting in short-term Heart Rate Variability forecasting.
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An experience report from a small full-stack team that applied contextual prompting and explicit architectural constraints to build a multi-project agent learning platform designed for sustained, production-oriented use and an academic retrieval-augmented generation system is presented.
Overall, the results suggest that epic-organized generation can improve perceived Gherkin quality while maintaining comparable semantic coverage, although broader replication is needed before generalizing this finding.
This study investigates how employees in a energy company understand AI adoption and identifies areas where AI and LLMs-based agentic workflows could assist daily activities, including reporting work, forecasting, data handling, maintenance-related tasks, and anomaly detection.
Five domain-specific RAG applications developed for real-world scenarios across governance, cybersecurity, agriculture, industrial research, and medical diagnostics are presented, highlighting technical, operational, and ethical challenges affecting the reliability and usability of RAG systems in practice.
A generalized Multimodal Subspace Support Vector Data Description model with graph-embedded regularization is proposed, illustrating how relational and structural information can be systematically embedded into one-class models, enabling robust learning under complex, high-dimensional, and multimodal conditions.
LLM-based multi-agent systems can support strategic AI planning by enabling iterative refinement with human experts by supporting structured and collaborative Requirements Engineering processes for AI adoption planning.
Development of safe-harbor integration and B2M/CIITA-based hypoimmunogenic designs as strategies to reduce engineering-related batch variability and HLA-dependent donor variability support a transition from empirical optimized MSC preparations toward molecularly defined cellular medicines with predefined genotype, expr...
Recent studies demonstrate promising therapeutic targets for mitochondrial dysfunction and highlight the need for research in mitochondrial function to change the therapeutic landscape in the management of mitochondrial dysfunction-associated diseases.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
A Blog post by Ai2 on Hugging Face
A Blog post by ServiceNow-AI on Hugging Face
“InstructMesh” can generate designs for everyday objects that are easy to edit and fabricate for both experts and newcomers to 3D modeling.
Proof of concept for watermarking AI-generated proteins while preserving biological function.
Algorithms & Theory
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