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ACL Anthology · ACL 2026:acl:2026.acl-long.2132 · 记录 #1

CxMP: A Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models

来源日期(仅到月份) 2026-07
来源记录日期 2026-07
雷达观测 2026-11-01 21:46
ACL Anthology · ACL 2026 ↗PDF ↗

摘要

Understanding language acquisition in language models remains an open question, yet many benchmarks focus on grammatical acceptability, with far less attention to interpreting meanings conveyed by grammatical forms.We introduce the Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models (CxMP), grounded in Construction Grammar, which treats form–meaning pairings (constructions) as fundamental linguistic units.It evaluates whether models interpret the semantic information implied by constructions, using a controlled minimal-pairs across nine types.Our results show that constructional understanding develops more gradually and remains limited for some constructions even in large language models (LLMs), whereas performance on grammatical acceptability emerges earlier, with shallow heuristics in CxMP exhibiting a U-shaped pattern.These findings highlight the need to broaden existing linguistic evaluations to capture meanings encoded in linguistic form.

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记录 #1 · 2026-07 · 最新观测版本

CxMP: A Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models

Understanding language acquisition in language models remains an open question, yet many benchmarks focus on grammatical acceptability, with far less attention to interpreting meanings conveyed by grammatical forms.We introduce the Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models (CxMP), grounded in Construction Grammar, which treats form–meaning pairings (constructions) as fundamental linguistic units.It evaluates whether models interpret the semantic information implied by constructions, using a controlled minimal-pairs across nine types.Our results show that constructional understanding develops more gradually and remains limited for some constructions even in large language models (LLMs), whereas performance on grammatical acceptability emerges earlier, with shallow heuristics in CxMP exhibiting a U-shaped pattern.These findings highlight the need to broaden existing linguistic evaluations to capture meanings encoded in linguistic form.

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