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New benchmark tests LLMs on multilingual crosswords and answer constraints

By PulseAugur Editorial · [1 sources] ·

Researchers have developed CulturalCrosswords, a new multilingual benchmark designed to evaluate how large language models handle answer constraints and grid completion. This benchmark uses crowdsourced crosswords from 42 languages, focusing on cultural riddles where multiple answers might be valid. The study found that providing answer lengths significantly improves model agreement with references, and requiring a completed grid reveals substantial differences in model capabilities. AI

IMPACT This benchmark could lead to more robust LLM evaluations, particularly for tasks requiring nuanced understanding of cultural context and constraint satisfaction.

RANK_REASON The item is a research paper detailing a new benchmark for evaluating LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New benchmark tests LLMs on multilingual crosswords and answer constraints

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The item is a research paper detailing a new benchmark for evaluating LLMs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Isaac Saxton-Knight, Gabriel Saxton-Knight, Diego Oliveira, Tidor-Vlad Pricope, Aston Garratt, Jocelyn D'Arcy ·

    CulturalCrosswords: A Multilingual Benchmark of Answer Constraints and Grid Completion

    arXiv:2611.10044v2 Announce Type: replace-cross Abstract: When several answers fit a riddle, exact-match scoring can penalise a valid response. CulturalCrosswords tests how answer constraints affect large language models (LLMs) solving cultural riddles, whose solutions draw on kn…

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