Idiom Understanding as a Tool to Measure the Dialect Gap

David Beauchemin; Mohamed Amine Youssef; Richard Khoury; Yan Tremblay

arxiv: 2510.05026 · v4 · submitted 2025-10-06 · 💻 cs.CL

Idiom Understanding as a Tool to Measure the Dialect Gap

David Beauchemin , Yan Tremblay , Mohamed Amine Youssef , Richard Khoury This is my paper

Pith reviewed 2026-05-18 09:46 UTC · model grok-4.3

classification 💻 cs.CL

keywords idiom understandingdialect gapQuebec Frenchlanguage model evaluationbenchmark datasetsregional dialectsFrench language varietiesprestige language

0 comments

The pith

Regional idioms serve as a reliable probe to measure how much language models lag in understanding dialects beyond the prestige variety.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper sets out to show that idiom comprehension tasks can be turned into a practical instrument for detecting dialect gaps in large language models. It does this by building large collections of Quebec-specific idiomatic phrases and words alongside a matched set of standard French expressions, then running the same models on both. The results indicate that most models perform markedly worse on the Quebec material even when they handle the standard version well. A reader should care because this gap matters for any real-world deployment where local speech patterns appear, and the method offers a replicable way to test other dialects without inventing entirely new evaluation types.

Core claim

The authors claim that by constructing three new corpora—QFrCoRE with 4,633 Quebec idiomatic phrases, QFrCoRT with 171 Quebec idiomatic words, and MFrCoE with 4,938 Metropolitan phrases—then testing 111 large language models, they can quantify the dialect gap: 65.77 percent of the models perform significantly worse on the Quebec idioms while only 9 percent favor the regional dialect. This demonstrates that strong performance on prestige-language idioms does not guarantee competence with regional ones and that the new benchmarks reliably expose the disparity.

What carries the argument

Parallel corpora of regional and prestige-language idioms that turn performance differences into a direct measure of dialect competence.

If this is right

Proficiency on standard French benchmarks does not transfer to regional dialect understanding for the majority of models.
The construction method can be repeated for other dialects to produce comparable gap measurements.
Existing general benchmarks may overstate model readiness for language use in specific regions.
Only a small minority of models show any advantage on the regional dialect material.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

Training pipelines could add targeted regional idiom data to close the measured gaps.
The same idiom-based test could be applied to spoken transcripts or mixed-language settings to check broader dialect coverage.
Model developers might adopt these benchmarks for pre-deployment audits in particular geographic markets.

Load-bearing premise

The idiom collections must reflect authentic dialect usage and the observed performance gaps must arise chiefly from differences in dialect knowledge rather than from topic, length, or annotation differences.

What would settle it

A follow-up evaluation that matches Quebec and Metropolitan idioms for length, topic, and frequency and then finds no remaining performance difference across the same models.

read the original abstract

The tasks of idiom understanding and dialect understanding are both well-established benchmarks in natural language processing. In this paper, we propose combining them, and using regional idioms as a test of dialect understanding. Towards this end, we propose three new benchmark datasets for the Quebec dialect of French: QFrCoRE, which contains 4,633 instances of idiomatic phrases, and QFrCoRT, which comprises 171 regional instances of idiomatic words, and a new benchmark for French Metropolitan expressions, MFrCoE, which comprises 4,938 phrases. We explain how to construct these corpora, so that our methodology can be replicated for other dialects. Our experiments with 111 LLMs reveal a critical disparity in dialectal competence: while models perform well on French Metropolitan, 65.77% of them perform significantly worse on Quebec idioms, with only 9.0% favoring the regional dialect. These results confirm that our benchmarks are a reliable tool for quantifying the dialect gap and that prestige-language proficiency does not guarantee regional dialect understanding.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

This paper builds three new idiom datasets for Quebec French and shows most of 111 LLMs do worse on them than on standard French, but the controls for non-dialect factors look thin.

read the letter

The main thing to know is that the authors created QFrCoRE, QFrCoRT, and MFrCoE as targeted idiom benchmarks for Quebec versus Metropolitan French, then ran them across 111 LLMs and found 65% of models performed worse on the regional set with only 9% favoring it. They also describe the construction steps so the approach can be copied for other dialects. That combination of new data and a replicable method is the clearest addition here. The broad model sweep gives a practical snapshot of where current systems sit on this kind of task. The scale makes the reported disparity easy to see and potentially useful for fairness checks in deployment. The softer part is the missing detail on whether the two corpora were matched on frequency, length, or complexity. Without those controls or statistical checks, the gap could partly reflect general rarity or annotation choices rather than dialect competence alone. The abstract is light on those specifics, so the central claim rests more on the raw performance numbers than on ruled-out alternatives. This work is aimed at NLP people who build or audit LLMs for regional language handling. Readers who need fresh test sets for dialect gaps or want to extend the method will get direct value from the datasets. It has enough new empirical content and a clear question to deserve peer review, though the methods section will likely draw questions on comparability.

Referee Report

1 major / 2 minor

Summary. The paper proposes combining idiom understanding and dialect understanding tasks to measure dialect gaps in LLMs. It introduces three new benchmark datasets: QFrCoRE (4,633 Quebec idiomatic phrases), QFrCoRT (171 regional idiomatic words), and MFrCoE (4,938 Metropolitan French phrases). The construction methodology is described as replicable. Experiments across 111 LLMs report that 65.77% of models perform significantly worse on Quebec idioms than on Metropolitan ones, with only 9.0% favoring the regional dialect. The authors conclude that these benchmarks reliably quantify the dialect gap and that prestige-language proficiency does not guarantee regional dialect understanding.

Significance. If the performance differences can be attributed to dialect competence rather than confounds, the work supplies a practical, replicable tool for quantifying dialect gaps in LLMs and highlights limitations of current models on regional varieties. The scale of the evaluation (111 models) provides a broad empirical basis that could inform more inclusive model development and benchmarking practices.

major comments (1)

[Construction methodology section] Construction methodology section (as referenced in the abstract): the paper does not describe explicit matching, balancing, or covariate controls for non-dialect factors such as idiom rarity/token frequency in pretraining data, sentence length, syntactic complexity, or topic between QFrCoRE and MFrCoE. Without these, the headline result that 65.77% of models perform significantly worse on Quebec idioms cannot be confidently interpreted as evidence of a dialect gap rather than differences in general difficulty or annotation artifacts. This directly affects the central claim.

minor comments (2)

[Abstract] The abstract states that models 'perform significantly worse' on Quebec idioms but provides no details on the statistical test, p-value threshold, sample sizes per condition, or multiple-comparison correction.
Clarify the exact operational definition and calculation of the '9.0% favoring the regional dialect' figure, including how ties or non-significant differences are handled.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive feedback on our manuscript. We address the major comment regarding the construction methodology below and will make revisions to strengthen the paper.

read point-by-point responses

Referee: [Construction methodology section] Construction methodology section (as referenced in the abstract): the paper does not describe explicit matching, balancing, or covariate controls for non-dialect factors such as idiom rarity/token frequency in pretraining data, sentence length, syntactic complexity, or topic between QFrCoRE and MFrCoE. Without these, the headline result that 65.77% of models perform significantly worse on Quebec idioms cannot be confidently interpreted as evidence of a dialect gap rather than differences in general difficulty or annotation artifacts. This directly affects the central claim.

Authors: We acknowledge that the manuscript does not explicitly detail matching or balancing for non-dialect factors such as token frequency, sentence length, syntactic complexity, or topic. Our construction methodology prioritized collecting authentic idiomatic expressions from dialect-specific resources for Quebec French and standard resources for Metropolitan French to ensure ecological validity. However, we agree that controlling for these potential confounds would provide stronger evidence. In the revised manuscript, we will add a new subsection in the construction methodology describing the average sentence lengths, estimated frequencies (using available French corpora), syntactic complexity measures, and topic distributions for both QFrCoRE and MFrCoE. We will also perform and report statistical tests for differences in these factors. If significant differences are found, we will discuss them as potential limitations to the interpretation of the dialect gap. This revision will allow for a more nuanced understanding of the results. revision: yes

Circularity Check

0 steps flagged

No circularity: empirical benchmark construction and LLM evaluation

full rationale

The paper constructs three new idiom corpora (QFrCoRE, QFrCoRT, MFrCoE) via a replicable methodology and evaluates 111 LLMs on them to measure performance differences between Quebec and Metropolitan French. No equations, fitted parameters, or derivations are present that would reduce the reported 65.77% disparity or the claim of dialect gap quantification to a self-definition or input by construction. Results follow directly from model inference on the constructed test sets rather than any predictive modeling or self-referential steps. The work is self-contained empirical measurement against external model outputs.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the validity of the new idiom corpora as faithful measures of dialect competence and on standard assumptions that benchmark accuracy reflects model understanding.

axioms (1)

domain assumption Model performance differences on idiom benchmarks primarily reflect dialectal competence rather than confounding factors such as data selection or annotation bias.
Invoked when interpreting the 65.77% worse performance as evidence of a dialect gap.

pith-pipeline@v0.9.0 · 5716 in / 1160 out tokens · 28155 ms · 2026-05-18T09:46:35.202385+00:00 · methodology

discussion (0)

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

IndisputableMonolith/Foundation/RealityFromDistinction.lean reality_from_one_distinction unclear

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unclear
Relation between the paper passage and the cited Recognition theorem.

We propose two new benchmark datasets for the Quebec dialect of French: QFrCoRE... and QFrCoRT... Our experiments with 94 LLM demonstrate that our regional idiom benchmarks are a reliable tool for measuring a model’s proficiency in a specific dialect.
IndisputableMonolith/Cost/FunctionalEquation.lean washburn_uniqueness_aczel unclear

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unclear
Relation between the paper passage and the cited Recognition theorem.

For each idiom, nine distractors... generated using... GPT-4o-mini... validated... using a weighted average of BLEU, ROUGE and BERTScore

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