CxMP: A Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models
arXiv:2602.21978v1 Announce Type: new Abstract: Recent work has examined language models from a linguistic perspective to better understand how they acquire language. Most existing benchmarks focus on judging grammatical acceptability, whereas the ability to interpret meanings conveyed by grammatical forms has received much less attention. We introduce the Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models (CxMP), a benchmark grounded in Construction Grammar that treats form-meaning pairings, or constructions, as fundamental linguistic units. CxMP evaluates whether models can interpret the semantic relations implied by constructions, using a controlled minimal-pair design across nine construction types, including the let-alone, caused motion, and ditransitive constructions. Our results show that while syntactic competence emerges early, constructional understanding develops more gradually and remains limited even in large language models (
arXiv:2602.21978v1 Announce Type: new Abstract: Recent work has examined language models from a linguistic perspective to better understand how they acquire language. Most existing benchmarks focus on judging grammatical acceptability, whereas the ability to interpret meanings conveyed by grammatical forms has received much less attention. We introduce the Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models (CxMP), a benchmark grounded in Construction Grammar that treats form-meaning pairings, or constructions, as fundamental linguistic units. CxMP evaluates whether models can interpret the semantic relations implied by constructions, using a controlled minimal-pair design across nine construction types, including the let-alone, caused motion, and ditransitive constructions. Our results show that while syntactic competence emerges early, constructional understanding develops more gradually and remains limited even in large language models (LLMs). CxMP thus reveals persistent gaps in how language models integrate form and meaning, providing a framework for studying constructional understanding and learning trajectories in language models.
Executive Summary
The article introduces the Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models (CxMP), a novel benchmark that assesses language models' ability to interpret grammatical forms and their meanings. The CxMP benchmark evaluates nine construction types, including the let-alone, caused motion, and ditransitive constructions. The results indicate that while syntactic competence emerges early, constructional understanding develops more gradually and remains limited even in large language models. This study highlights the need for a more nuanced understanding of language models' linguistic capabilities, particularly in the areas of form-meaning pairings and constructional understanding. The CxMP benchmark provides a valuable framework for studying constructional understanding and learning trajectories in language models, shedding light on the persistent gaps in how language models integrate form and meaning.
Key Points
- ▸ CxMP is a novel benchmark for evaluating constructional understanding in language models.
- ▸ The benchmark assesses language models' ability to interpret grammatical forms and their meanings.
- ▸ Constructional understanding develops more gradually than syntactic competence, even in large language models.
Merits
Strengths the Field
The CxMP benchmark provides a much-needed framework for studying constructional understanding and learning trajectories in language models, shedding light on the persistent gaps in how language models integrate form and meaning.
Improves Understanding of Language Models
The study highlights the need for a more nuanced understanding of language models' linguistic capabilities, particularly in the areas of form-meaning pairings and constructional understanding.
Demerits
Limited Scope
The CxMP benchmark currently only evaluates nine construction types, which may not be representative of the full range of linguistic constructions.
Need for Further Research
The study suggests that constructional understanding develops more gradually than syntactic competence, but further research is needed to fully understand the implications of this finding.
Expert Commentary
The introduction of the CxMP benchmark marks a significant step forward in the development of language models, as it provides a more comprehensive understanding of their linguistic capabilities. However, the study also highlights the need for further research to fully understand the implications of the findings. Specifically, the study suggests that constructional understanding develops more gradually than syntactic competence, which has important implications for language model development and deployment. The CxMP benchmark provides a valuable framework for studying constructional understanding and learning trajectories in language models, shedding light on the persistent gaps in how language models integrate form and meaning. As the field continues to evolve, it will be essential to consider the implications of this study and to develop more effective and accurate language processing applications.
Recommendations
- ✓ Further research is needed to fully understand the implications of the finding that constructional understanding develops more gradually than syntactic competence.
- ✓ The CxMP benchmark should be expanded to include a broader range of linguistic constructions to provide a more comprehensive understanding of language models' linguistic capabilities.
