LLM-based neural distinguishers on SPECK-32/64 show no improvement over ResNet but gain from XOR-inclusive prompts.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
A multi-agent system combining contextual bandits, LLM agents, and semantic checkpoints improves convergence and robustness in adaptive method selection for sensitivity analysis and uncertainty quantification.
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Do LLMsMakeNeural Distinguishers Wise?
LLM-based neural distinguishers on SPECK-32/64 show no improvement over ResNet but gain from XOR-inclusive prompts.
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Learning to Choose: An Empowerment-Guided Multi-Agent System with semantic communication for Adaptive Method Selection
A multi-agent system combining contextual bandits, LLM agents, and semantic checkpoints improves convergence and robustness in adaptive method selection for sensitivity analysis and uncertainty quantification.