---
title: "Are BabyLMs Deaf to Gricean Maxims? A — Askari 2025"
description: "The authors test whether language models trained on small amounts of data (BabyLM) can detect violations of Grice's conversational maxims."
authors: ["Raha Askari", "Sina Zarrieß", "Özge Alacam", "Judith Sieker"]
year: 2025
venue: "Proceedings of the First BabyLM Workshop"
source: "https://aclanthology.org/2025.babylm-main.4/"
doi: "10.18653/v1/2025.babylm-main.4"
arxiv: "2510.04764"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/papers/askari-2025-are-babylms-deaf-gricean-maxims/"
---
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# Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models

**Authors:** Raha Askari, [Sina Zarrieß](https://md.research.elamur.ai/free/authors/sina-zarries/), Özge Alacam, [Judith Sieker](https://md.research.elamur.ai/free/authors/judith-sieker/) · **Year:** 2025 · **Venue:** Proceedings of the First BabyLM Workshop · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2025.babylm-main.4/) · [PDF](https://aclanthology.org/2025.babylm-main.4.pdf) · [DOI 10.18653/v1/2025.babylm-main.4](https://doi.org/10.18653/v1/2025.babylm-main.4) · [arXiv 2510.04764](https://arxiv.org/abs/2510.04764) · [OpenAlex](https://openalex.org/W4416037637)

**Citations:** 1 citations (openalex-snapshot · 2026-10-14) · 3 in our library, of the 140673 papers whose bibliographies we read

## Summary
The authors test whether language models trained on small amounts of data (BabyLM) can detect violations of Grice's conversational maxims. The study builds on the psycholinguistic Conversational Violations Test (CVT) by Surian et al. (1996), which was used to measure children's pragmatic abilities. Each test item has a short question and two answers: one follows the maxim and the other violates it. The authors automatically expanded the 25 original dialogues to 2,250 examples, then checked and edited them by hand. Eight BabyLM baseline models and the OLMo model were scored by which answer each model assigns the higher probability. The results were compared with the children's scores from the original study. Models trained on \<100M tokens generally outperform those trained on \<10M, but neither group reaches the children's level. Even OLMo outperforms the children only in some cases. The benchmark is publicly released. It extends the BabyLM evaluation suite with pragmatics, which has so far been tested far less often than syntax.

## Key points
- The `gricean_baby` dataset is available on Hugging Face (rahaaskari/gricean_baby). It covers five maxims: Quantity I (be sufficiently informative), Quantity II (avoid saying more than needed), Quality, Relation, and Politeness.
- 4 models from the Strict-small track (\<10M) and 4 from the Strict track (\<100M) were evaluated, along with a 1B-parameter OLMo pretrained on 3T tokens. In total, this gives 20,250 data points.
- The comparison group was 8 neurotypical children with a mean age of 6–7 years. No model reached their overall accuracy.
- The BabyLM models are best at detecting violations of truthfulness (Quality) and worst at judging the appropriate amount of information (Quantity). They do not prefer more polite or more relevant answers.
- A correlation analysis showed that models trained on small data conflate different pragmatic abilities. With more data, these correlations weaken, meaning the models separate individual dimensions of pragmatics more clearly. Limitations of the work: English only, and the dialogues give minimal context.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/shelves/linguistics/)

Topics: [Implicature](https://md.research.elamur.ai/free/topics/implicature/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{askari2025are,
  title = {{Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models}},
  author = {Askari, Raha and Zarrieß, Sina and Alacam, Özge and Sieker, Judith},
  booktitle = {Proceedings of the First BabyLM Workshop},
  year = {2025},
  doi = {10.18653/v1/2025.babylm-main.4},
  eprint = {2510.04764},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.18653/v1/2025.babylm-main.4}
}
```

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