Introduces the 'innovation' property of LLMs and proves it is an almost characterization of hallucination while deriving new lower bounds on hallucination rates via missing mass.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
FedEPD decouples topological purification from semantic recalibration using energy-guided pruning and prototype injection to improve minority performance in federated long-tailed graph learning.
citing papers explorer
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Innovation: An Almost Characterization of Hallucination
Introduces the 'innovation' property of LLMs and proves it is an almost characterization of hallucination while deriving new lower bounds on hallucination rates via missing mass.
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Towards Federated Long-Tailed Graph Learning: An Energy-Guided Dual Decoupling Approach
FedEPD decouples topological purification from semantic recalibration using energy-guided pruning and prototype injection to improve minority performance in federated long-tailed graph learning.