跳到正文
研踪PaperTrail

YOUR RESEARCH, IN SIGHT

让下一篇重要论文,不再错过。

覆盖计算机全学科,以 AI 为快捷入口。关注方向、作者和关键词,把发现变成持续的研究积累。

部分采集异常
正在读取账号与研究记录…

全站更新概况

+0新增论文
+0其中 AI 相关
+1已有论文修订
+100新增 AI 导读

arXiv 最近完成扫描:2026-11-09 05:07 · 全站最近入库:2026-11-08 06:02各信源进度 →

统计口径与数据新鲜度

统计 2026-11-08 05:22 — 2026-11-09 05:22(北京时间) · 点击数字查看对应简报;AI 相关包含在新增论文内。

最近完成检查:2026-11-09 05:07最近发现新增版本:2026-11-08 06:02库内论文最新更新时间:2026-11-06 02:59

每分钟刷新已保存的数据。空检查不代表采集异常;新收录可能包含历史论文。AI 导读按新增版本计数。

17,100 已收录论文14,661 AI 相关4,057 有修订112 HF 社区发现

浏览论文库

时间范围跟随排序:版本更新、本站收录或首次发表。最新收录可能包含历史论文。部分信源异常,查看状态 →

找到 2 篇论文 · 按版本更新时间排序上轮扫描起点 2026-11-09 05:05(北京时间)
新论文 · v1arXiv:2611.06462

Weaver: Unlocking Blockchain Transaction Parallelism through State-Decoupled Symbolic Execution

Ru Cheng, Maofan Yin, Liangrong Chen, Lizan Zhou, Chenyuan Wu

原文摘要

Transaction execution remains a major performance bottleneck in blockchains. Existing parallel execution engines are still blocked by slow state accesses on each transaction's critical path, creating a hidden loss of parallelism. This paper presents Weaver, a state-decoupled transaction processing paradigm that enables execution flow to proceed in the absence of concrete state values. Weaver represents states as lightweight symbolic references and records subsequent computation as symbolic expressions while concrete values are fetched on the fly. To handle state-dependent control flow, Weaver predicts the most likely branch direction through hierarchical symbolic pattern matching. Weaver further introduces expression-granular scheduling that evaluates each symbolic expression as soon as its state dependencies are resolved, rather than waiting for the transaction's entire read set, fully exploiting fine-grained intra-transaction parallelism. Evaluation on real Ethereum blocks and synthetic workloads spanning four representative dApps shows that Weaver delivers 41%-63% higher throughput than state-of-the-art parallel execution engines and up to 7.5 times the throughput of serial execution.

cs.DC

新论文 · v1arXiv:2611.05173

Correctness Firewalls for Synthesized Database Components

Mohammad Javad Amiri, Carsten Binnig, Andreas Kipf, Tim Kraska, Ryan Marcus, Johannes Wehrstein, Chenyuan Wu, Geoffrey X. Yu 等 9 位作者

原文摘要

For the first time in history, high-performance code is cheap. Today's coding agents can generate bespoke, instance-optimized data systems with excellent performance, and such agents will continue to improve as LLMs advance. But a purely agentic approach, even when validated with strong testing techniques, does not automatically inherit the correctness guarantees our community has spent decades building. We propose a middle ground between hand-crafted and agent-crafted systems: correctness firewalls, lightweight design patterns under which a synthesized component can affect a system's performance but never its results. Behind a correctness firewall, agents are free to synthesize fast components while the overall system remains correct. We present three case studies, each demonstrating a different type of firewall: cardinality estimation (advisory), searching sorted data (guarded), and data compression (certified). In early experiments, synthesized components search sorted data up to 3x faster than human-designed learned indexes and can compress text 1.5x smaller than Zstd. Drawing on these case studies, we outline a research agenda for how data management systems can exploit coding agents without giving up their hard-won correctness guarantees, from protecting synthesized code to measuring the cost of correctness.

cs.DB