A literature survey finds foundation-model agents in industry are 75% at prototype stages with gains in human interaction and uncertainty handling but deficits in negotiation, plus limitations like hallucinations and latency.
In: 2024 IEEE Interna- tional Conference on Big Data (BigData), pp
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The sum of verifier warnings adds no useful predictive power for code comprehensibility beyond syntactic and developer features.
IA-QCNN applies quantum principles via ring-topology convolution and importance weighting to achieve claimed high-accuracy MGMT methylation prediction from MRI with fewer parameters and noise robustness than classical models.
citing papers explorer
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Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges
A literature survey finds foundation-model agents in industry are 75% at prototype stages with gains in human interaction and uncertainty handling but deficits in negotiation, plus limitations like hallucinations and latency.
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Verifier Warnings Do Not Improve Comprehensibility Prediction
The sum of verifier warnings adds no useful predictive power for code comprehensibility beyond syntactic and developer features.
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A Specialized Importance-Aware Quantum Convolutional Neural Network with Ring-Topology (IA-QCNN) for MGMT Promoter Methylation Prediction in Glioblastoma
IA-QCNN applies quantum principles via ring-topology convolution and importance weighting to achieve claimed high-accuracy MGMT methylation prediction from MRI with fewer parameters and noise robustness than classical models.