Four attribution methods applied to over one million Polygon blocks show that most atomic arbitrage MEV opportunities trace to single source transactions from a small set of protocols.
Reducing energy bloat in large model training
3 Pith papers cite this work. Polarity classification is still indexing.
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Affinity Tailor improves per-CPU throughput by 12% on chiplet systems and 3% on non-chiplet systems over Linux CFS by using dynamic compact affinity hints derived from online demand estimates.
GreenDyGNN applies Double-DQN to adapt cache management in distributed GNN training, cutting energy by up to 43% under congestion versus static policies.
citing papers explorer
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The Origins of MEV: Systematic Attribution of Arbitrage Opportunity Creation at Scale
Four attribution methods applied to over one million Polygon blocks show that most atomic arbitrage MEV opportunities trace to single source transactions from a small set of protocols.
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Affinity Tailor: Dynamic Locality-Aware Scheduling at Scale
Affinity Tailor improves per-CPU throughput by 12% on chiplet systems and 3% on non-chiplet systems over Linux CFS by using dynamic compact affinity hints derived from online demand estimates.
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GreenDyGNN: Runtime-Adaptive Energy-Efficient Communication for Distributed GNN Training
GreenDyGNN applies Double-DQN to adapt cache management in distributed GNN training, cutting energy by up to 43% under congestion versus static policies.