Fine-tuned simulators grounded in real human data produce LLM assistants that win more often against real users than those trained against role-playing simulators.
Density-based clustering based on hierarchical density estimates
2 Pith papers cite this work. Polarity classification is still indexing.
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An unsupervised system-aware framework combines online detection with an LLM-augmented contextual digital twin to deliver real-time, interpretable anomaly diagnosis in industrial control systems.
citing papers explorer
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Quantifying the Utility of User Simulators for Building Collaborative LLM Assistants
Fine-tuned simulators grounded in real human data produce LLM assistants that win more often against real users than those trained against role-playing simulators.
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System-aware contextual digital twin for ICS anomaly diagnosis
An unsupervised system-aware framework combines online detection with an LLM-augmented contextual digital twin to deliver real-time, interpretable anomaly diagnosis in industrial control systems.