Modular construction of succinct arguments for QMA via OSP-based interactive protocol plus collapsing-hash communication compression compiler, without LWE.
2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS) , pages =
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BehaviorLM applies progressive fine-tuning in two stages to let LLMs predict both frequent anchor and rare tail user behaviors more robustly on real-world datasets.
citing papers explorer
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A Modular Approach to Succinct Arguments for QMA
Modular construction of succinct arguments for QMA via OSP-based interactive protocol plus collapsing-hash communication compression compiler, without LWE.
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Tuning Language Models for Robust Prediction of Diverse User Behaviors
BehaviorLM applies progressive fine-tuning in two stages to let LLMs predict both frequent anchor and rare tail user behaviors more robustly on real-world datasets.