TL;DR
SACC is the first to treat probabilistic finality as a quantifiable risk budget, and consistently outperforms traditional 2PC and modern fast-path protocols in challenging environments, significantly improving commit rates while strictly bounding tail latency.
Cross-institutional federated learning suffers from centralized trust fragility, poisoning attacks, and the lack of verifiable contribution-based incentives. This paper proposes BFLP, a blockchain-based federated learning protocol integrating zero-knowledge proofs (ZKPs) into a layered, contract-driven architecture. It...
Using Gate.io hourly spot-order-book archives from January 2022 through June 2023, this paper reconstructs a long-horizon five-second panel for comparing the direct Ether/Tether (ETH/USDT) quote with the synthetic Ether/Bitcoin (ETH/BTC) \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackag...
The literature on multi-agent systems lacks a unified framework connecting problem structure to the choice of equilibrium concept and solution method. This survey synthesizes work on Nash equilibrium and its variants, namely standard NE, Mixed/Approximate NE, Generalized Nash Equilibrium (GNE), and Stackelberg equilibr...
Multi-agent LLM systems coordinate through natural-language messages that consume 40--60\% of their token budget. Replacing these with structured graphs reduces cost but fails on tasks requiring adaptive reasoning. We propose \textbf{Routed Graph Handoff}, where a lightweight LLM router (155 tokens, 0.15\% overhead) se...
Formal feature explanations strictly maintain perfect conformity but are intractable to compute, while heuristic methods are much faster but can lead to problematic explanations due to lack of conformity guarantees. We propose relative keys that have the best of both worlds. Relative keys associate feature explanations...
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