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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SPIN co-designs sparse attention with hierarchical memory to achieve 1.66-5.66x higher throughput, 7-9x lower TTFT, and up to 58% lower TPOT than vLLM and original sparse implementations.
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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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Unifying Sparse Attention with Hierarchical Memory for Scalable Long-Context LLM Serving
SPIN co-designs sparse attention with hierarchical memory to achieve 1.66-5.66x higher throughput, 7-9x lower TTFT, and up to 58% lower TPOT than vLLM and original sparse implementations.
- RetroInfer: A Vector Storage Engine for Scalable Long-Context LLM Inference