Ko-WideSearch: A Korean Breadth-Search Benchmark for Exhaustive Set Enumeration by Web Agents
Ko-WideSearch is a Korean breadth-search benchmark built via an automated synthesize-and-verify pipeline, comprising 228 tables over 190 entities across 16 categories and three difficulty tiers. Evaluations on 20 web agents show consistent failure: agents recover sets but not rows (Item-F1 92.8 vs Row-F1 53.7), accuracy drops with difficulty, and open-ended free-text cells are the main bottleneck.
[2606.27595] Ko-WideSearch: A Korean Breadth-Search Benchmark for Exhaustive Set Enumeration by Web Agents
[Submitted on 25 Jun 2026]
Title:Ko-WideSearch: A Korean Breadth-Search Benchmark for Exhaustive Set Enumeration by Web Agents
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Abstract:Web-agent benchmarks overwhelmingly measure depth -- pinning one obscure answer behind a chain of constraints -- while breadth, exhaustively enumerating a closed set and filling each item's attributes, is barely evaluated, especially outside English. Breadth is also hard to build: certifying that a gold set is complete and every cell correct is far costlier than checking a single answer. I introduce \textsc{Ko-WideSearch}, a Korean breadth-search benchmark built by an automated synthesize-and-verify pipeline. Each task names a set-parent entity -- a TV season, a dynasty, a league, an administrative region, an election -- and asks for its full membership plus a per-item attribute table, graded by Item-, Column-, and Row-F1. It spans 228 tables over 190 entities and sixteen categories across three difficulty tiers, set by two structural knobs I dial independently -- table width and a 2-D composite key -- so cross-product membership climbs from 0\% to 100\% across the tiers. A single normalization-aware comparator is shared between gold construction and grading, so stable date and count columns are not over-dropped on formatting alone. Across twenty web agents, the failure is consistent: agents recover the set but not the rows (e.g.\ Item-F1 92.8 against Row-F1 53.7), accuracy falls steadily as the knobs harden, and neither more search nor more spend closes the gap. Broken down by cell, the hard part is finding the right value, not formatting it: open-ended free-text cells fail most, while cells with a standard answer such as a date or a name usually come out right.
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Computation and Language (cs.CL)
Cite as: arXiv:2606.27595 [cs.CL]
(or arXiv:2606.27595v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2606.27595
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Minbyul Jeong [view email] [v1] Thu, 25 Jun 2026 22:51:59 UTC (818 KB)
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