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    <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 **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.</abstract>
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%0 Conference Proceedings
%T Child-directed speech facilitates production, not comprehension, in BabyLMs
%A Bunzeck, Bastian
%A Zarrieß, Sina
%Y Bonial, Claire
%Y Berzak, Yevgeni
%S Proceedings of the 30th Conference on Computational Natural Language Learning
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-410-1
%F bunzeck-zarriess-2026-child
%X 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 **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.
%U https://aclanthology.org/2026.conll-main.14/
%P 227-249

Markdown (Informal)

[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://aclanthology.org/2026.conll-main.14/) (Bunzeck & Zarrieß, CoNLL 2026)

• Child-directed speech facilitates production, not comprehension, in BabyLMs (Bunzeck & Zarrieß, CoNLL 2026)

ACL

• Bastian Bunzeck and Sina Zarrieß. 2026. Child-directed speech facilitates production, not comprehension, in BabyLMs. In Proceedings of the 30th Conference on Computational Natural Language Learning, pages 227–249, San Diego, California, USA. Association for Computational Linguistics.