Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- en
|
| 4 |
+
---
|
| 5 |
+
This repository contains the pretraining data for [the models](https://huggingface.co/LaurensWink/SmolLM2-135M_variants) probed in _[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://aclanthology.org/2026.conll-main.14/)_ (Bunzeck & Zarrieß @ CoNLL 2026).
|
| 6 |
+
|
| 7 |
+
If you use this data, please cite:
|
| 8 |
+
```
|
| 9 |
+
@inproceedings{bunzeck-zarriess-2026-child,
|
| 10 |
+
title = "Child-directed speech facilitates production, not comprehension, in {B}aby{LM}s",
|
| 11 |
+
author = "Bunzeck, Bastian and
|
| 12 |
+
Zarrie{\ss}, Sina",
|
| 13 |
+
editor = "Bonial, Claire and
|
| 14 |
+
Berzak, Yevgeni",
|
| 15 |
+
booktitle = "Proceedings of the 30th Conference on Computational Natural Language Learning",
|
| 16 |
+
month = jul,
|
| 17 |
+
year = "2026",
|
| 18 |
+
address = "San Diego, California, USA",
|
| 19 |
+
publisher = "Association for Computational Linguistics",
|
| 20 |
+
url = "https://aclanthology.org/2026.conll-main.14/",
|
| 21 |
+
doi = "10.18653/v1/2026.conll-main.14",
|
| 22 |
+
pages = "227--249",
|
| 23 |
+
ISBN = "979-8-89176-410-1",
|
| 24 |
+
abstract = "Recent studies suggest that child-directed speech is not conducive to language learning in BabyLMs. However, current evaluations focus predominantly on comprehension and not production, which is central to usage-based theories of language acquisition which argue how CDS facilitates early language use through constructional ``frames'' (frequent lexical patterns with open slots). We introduce a novel generation-based evaluation inspired by such theories in form of a \textbf{frame-completion task}, and compare Llama models trained with CDS, the BabyLM corpus, and web-crawl data (FineWeb-edu) on comprehension benchmarks and our novel framework. Our results reveal a clear dissociation between models' comprehension and production capabilities: while FineWeb-trained models excel at minimal pairs, CDS-trained models produce grammatical completions substantially earlier in training and concentrate probability mass on appropriate slot-fillers. These findings show that comprehension benchmarks underestimate what CDS affords to BabyLMs."
|
| 25 |
+
}
|
| 26 |
+
```
|