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

+586新增论文
+453其中 AI 相关
+91已有论文修订
+100新增 AI 导读

arXiv 最近完成扫描:2026-11-13 11:13 · 全站最近入库:2026-11-13 11:12各信源进度 →

统计口径与数据新鲜度

统计 2026-11-12 11:34 — 2026-11-13 11:34(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:2026-11-13 11:13最近发现新增版本:2026-11-13 11:12库内论文最新更新时间:2026-11-11 22:55

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。

22,261 已收录论文18,776 AI 相关6,286 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 1 篇论文 · 按版本更新时间排序上轮扫描起点 2026-11-13 11:11(北京时间)
版本更新 · v2arXiv:2609.37431

Query Complexity of Testing Structured Parenthesis Languages

Tim Jackman, Diptaksho Palit, Sofya Raskhodnikova

原文摘要

We study the query complexity of testing membership in structured string languages, focusing on Dyck languages and natural generalizations. A tester receives query access to a word and must distinguish valid inputs from words that are far in Hamming distance, while inspecting only a sublinear number of positions. Our results sharpen the boundary between constant-query testability and polynomial query complexity. First, we prove an $Ω(n^{2/5})$ lower bound for testing Dyck languages $D_m$ with any fixed number $m\ge2$ of parenthesis types, improving the previous $Ω(n^{1/5})$ lower bound of Fischer, Magniez, and Starikovskaya (SODA `18) and nearly matching their upper bound of $O(n^{2/5+o(1)})$. Furthermore, we show that all nonadaptive algorithms for these problems require $Ω(n^{1/2})$ queries. Our lower bounds use a Pólya-urn process to construct the hard distribution; Second, we identify a broad class of weighted-parenthesis languages, which we call {\em excursion languages,} that remain constant-query testable. These languages encode bounded-step walks that stay nonnegative and return to zero. For every fixed excursion language, we give a nonadaptive tester with query complexity $O(1/\varepsilon^2)$, and we prove this dependence on $\varepsilon$ is optimal, even for adaptive algorithms. As a special case, we obtain the tight $Θ(1/\varepsilon^2)$ query complexity of testing $D_1$, improving the previous $O(\log(1/\varepsilon)/\varepsilon^2)$ upper bound and giving the first matching two-sided-error lower bound. Third, we construct a simple hard language, Hidden String, that is generated by a deterministic linear grammar but nevertheless requires $Ω(n^{2/5})$ adaptive queries and $Ω(n^{1/2})$ nonadaptive queries to test. This shows that polynomial query complexity appears even for highly restricted string languages.

cs.DS · cs.CC