LUMINA derives three design principles for physics-informed foundation models that balance accuracy, constraint satisfaction, and reliability on topology-transferable ACOPF problems.
Large language model powered agents in the web , isbn =
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
WebUncertainty improves web agent performance on benchmarks by adaptively selecting planning modes based on task uncertainty and using confidence-induced action uncertainty in MCTS to quantify aleatoric and epistemic uncertainty for better decisions.
citing papers explorer
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LUMINA: Foundation Models for Topology Transferable ACOPF
LUMINA derives three design principles for physics-informed foundation models that balance accuracy, constraint satisfaction, and reliability on topology-transferable ACOPF problems.
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WebUncertainty: Dual-Level Uncertainty Driven Planning and Reasoning For Autonomous Web Agent
WebUncertainty improves web agent performance on benchmarks by adaptively selecting planning modes based on task uncertainty and using confidence-induced action uncertainty in MCTS to quantify aleatoric and epistemic uncertainty for better decisions.