You've Got a BUD in Me: Authenticated Reads from Per-Block Write Logs
该研究通过为每个区块的写入创建认证日志(BUD)来解决区块链中全状态认证读取成本高的问题,从而支持历史成员和排除证明。
该研究通过为每个区块的写入创建认证日志(BUD)来解决区块链中全状态认证读取成本高的问题,从而支持历史成员和排除证明。
研究提出了一种新的账本认证器及安全性实验LAEUF,解决了量子随机预言模型中账本认证的安全性问题,通过设定资源边界和条件来防止伪造。
This study addresses estimation bias in large language model evaluation arising from the confounding of prompt instability and sampling noise. We propose a second-order response law framework that derives an unbiased estimator and employs a crossed prompt-answer order experimental design to effectively disentangle inter-prompt variability from intra-prompt sampling noise. This approach enables precise, debiased assessment of prompt robustness under low repetition budgets, yielding corrected estimates that closely approximate high-repetition benchmarks. By resolving noise interference challenges under limited inference calls, this work establishes a novel theoretical foundation and methodological paradigm for cost-effective and reliable LLM evaluation.
This work addresses the vulnerability of encrypted mempools to economically lagging and security risks arising from self-authorized state manipulation—such as perpetual contract funding rate manipulation—due to their inability to inject corrective transactions into already committed batches, despite offering protection against victim-dependent MEV attacks. The paper proposes a micro-correction mechanism grounded in executable arbitrage, modeling how correctors optimally choose order sizes balancing price impact and inventory costs, while evaluating exploitable opportunities through the lens of protocol disclosure timing. It introduces a novel local security index incorporating attacker blind spots, correction shielding, and capitalization shielding, revealing how private transactions suppress predictive capitalization of funding rates and induce dual amplification effects. By integrating game theory, market mechanism design, and encrypted mempool architecture, the study establishes a dynamic security framework driven by information scheduling and response factors, proving that closed-phase correction rates fall below adaptive correction rates and quantifying both state distortion and its responsive amplification.
This study addresses the incentive challenge in threshold team production, where task failure may result from members delaying submission of their shares. The authors propose a non-negative completion bonus mechanism that relies solely on submitted shares and achieves strong delay immunity without requiring deposits or penalties. By employing a uniform allocation rule and leveraging mechanism design and game-theoretic analysis, the work precisely characterizes the minimal budget required in the worst case under the k-of-n threshold task model. The paper establishes necessary and sufficient conditions to guarantee timely participation by all agents while being robust against collusive delays, and proves that the derived budget bound is tight for all transfer rules based solely on completed shares.
该研究通过为每个区块的写入创建认证日志(BUD)来解决区块链中全状态认证读取成本高的问题,从而支持历史成员和排除证明。
研究提出了一种新的账本认证器及安全性实验LAEUF,解决了量子随机预言模型中账本认证的安全性问题,通过设定资源边界和条件来防止伪造。
This study addresses estimation bias in large language model evaluation arising from the confounding of prompt instability and sampling noise. We propose a second-order response law framework that derives an unbiased estimator and employs a crossed prompt-answer order experimental design to effectively disentangle inter-prompt variability from intra-prompt sampling noise. This approach enables precise, debiased assessment of prompt robustness under low repetition budgets, yielding corrected estimates that closely approximate high-repetition benchmarks. By resolving noise interference challenges under limited inference calls, this work establishes a novel theoretical foundation and methodological paradigm for cost-effective and reliable LLM evaluation.
This work addresses the vulnerability of encrypted mempools to economically lagging and security risks arising from self-authorized state manipulation—such as perpetual contract funding rate manipulation—due to their inability to inject corrective transactions into already committed batches, despite offering protection against victim-dependent MEV attacks. The paper proposes a micro-correction mechanism grounded in executable arbitrage, modeling how correctors optimally choose order sizes balancing price impact and inventory costs, while evaluating exploitable opportunities through the lens of protocol disclosure timing. It introduces a novel local security index incorporating attacker blind spots, correction shielding, and capitalization shielding, revealing how private transactions suppress predictive capitalization of funding rates and induce dual amplification effects. By integrating game theory, market mechanism design, and encrypted mempool architecture, the study establishes a dynamic security framework driven by information scheduling and response factors, proving that closed-phase correction rates fall below adaptive correction rates and quantifying both state distortion and its responsive amplification.
This study addresses the incentive challenge in threshold team production, where task failure may result from members delaying submission of their shares. The authors propose a non-negative completion bonus mechanism that relies solely on submitted shares and achieves strong delay immunity without requiring deposits or penalties. By employing a uniform allocation rule and leveraging mechanism design and game-theoretic analysis, the work precisely characterizes the minimal budget required in the worst case under the k-of-n threshold task model. The paper establishes necessary and sufficient conditions to guarantee timely participation by all agents while being robust against collusive delays, and proves that the derived budget bound is tight for all transfer rules based solely on completed shares.