APIDiffer automatically detects 72 API inconsistencies across 11 Ethereum clients using specification-guided test generation and LLM-based false-positive filtering, with 90% of bugs confirmed by developers.
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PrivaDE is a privacy-preserving protocol for jointly computing data utility scores in ML using secure computation, with optimizations for efficiency and blockchain integration via smart contracts.
ALPINE deploys an offline-trained TD3 policy on terminal devices to map multi-dimensional risk states to adaptive privacy budgets for local differential privacy in mobile edge crowdsensing, with edge feedback closing the loop.
NetSquid simulations characterize how memory quality, noise, distances, switches, purification and error correction affect end-to-end fidelity in entanglement-based quantum networks and yield design guidelines.
citing papers explorer
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When Specifications Meet Reality: Uncovering API Inconsistencies in Ethereum Infrastructure
APIDiffer automatically detects 72 API inconsistencies across 11 Ethereum clients using specification-guided test generation and LLM-based false-positive filtering, with 90% of bugs confirmed by developers.
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PrivaDE: Privacy-preserving Data Evaluation for Blockchain-based Data Marketplaces
PrivaDE is a privacy-preserving protocol for jointly computing data utility scores in ML using secure computation, with optimizations for efficiency and blockchain integration via smart contracts.
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ALPINE: Closed-Loop Adaptive Privacy Budget Allocation for Mobile Edge Crowdsensing
ALPINE deploys an offline-trained TD3 policy on terminal devices to map multi-dimensional risk states to adaptive privacy budgets for local differential privacy in mobile edge crowdsensing, with edge feedback closing the loop.
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Simulation of entanglement based quantum networks for performance characterization
NetSquid simulations characterize how memory quality, noise, distances, switches, purification and error correction affect end-to-end fidelity in entanglement-based quantum networks and yield design guidelines.