Teacher Demonstrations in a BabyLM’s Zone of Proximal Development for Contingent Multi-Turn Interaction
Suchir Salhan, Hongyi Gu, Donya Rooein, Diana Galvan-Sosa, Gabrielle Gaudeau, Andrew Caines, Zheng Yuan, Paula Buttery
Correct Metadata for
Abstract
Multi-turn dialogues between a child and caregiver are characterized by a property called contingency – prompt, direct, and meaningful exchanges between interlocutors. We introduce ContingentChat, a Teacher–Student framework that benchmarks and improves multi-turn contingency in a BabyLM trained on 100M words. Using a novel alignment dataset for post-training, BabyLM generates responses that are more grammatical and cohesive. Experiments with adaptive Teacher decoding strategies show limited additional gains. ContingentChat highlights the positive benefits of targeted post-training on dialogue quality and presents contingency as a challenging goal for BabyLMs.- Anthology ID:
- 2025.babylm-main.25
- Volume:
- Proceedings of the First BabyLM Workshop
- Month:
- November
- Year:
- 2025
- Address:
- Suzhou, China
- Editors:
- Lucas Charpentier, Leshem Choshen, Ryan Cotterell, Mustafa Omer Gul, Michael Y. Hu, Jing Liu, Jaap Jumelet, Tal Linzen, Aaron Mueller, Candace Ross, Raj Sanjay Shah, Alex Warstadt, Ethan Gotlieb Wilcox, Adina Williams
- Venue:
- BabyLM
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 323–355
- Language:
- URL:
- https://aclanthology.org/2025.babylm-main.25/
- DOI:
- Bibkey:
- Cite (ACL):
- Suchir Salhan, Hongyi Gu, Donya Rooein, Diana Galvan-Sosa, Gabrielle Gaudeau, Andrew Caines, Zheng Yuan, and Paula Buttery. 2025. Teacher Demonstrations in a BabyLM’s Zone of Proximal Development for Contingent Multi-Turn Interaction. In Proceedings of the First BabyLM Workshop, pages 323–355, Suzhou, China. Association for Computational Linguistics.
- Cite (Informal):
- Teacher Demonstrations in a BabyLM’s Zone of Proximal Development for Contingent Multi-Turn Interaction (Salhan et al., BabyLM 2025)
- Copy Citation:
- PDF:
- https://aclanthology.org/2025.babylm-main.25.pdf
Export citation
@inproceedings{salhan-etal-2025-teacher,
title = "Teacher Demonstrations in a {B}aby{LM}{'}s Zone of Proximal Development for Contingent Multi-Turn Interaction",
author = "Salhan, Suchir and
Gu, Hongyi and
Rooein, Donya and
Galvan-Sosa, Diana and
Gaudeau, Gabrielle and
Caines, Andrew and
Yuan, Zheng and
Buttery, Paula",
editor = "Charpentier, Lucas and
Choshen, Leshem and
Cotterell, Ryan and
Gul, Mustafa Omer and
Hu, Michael Y. and
Liu, Jing and
Jumelet, Jaap and
Linzen, Tal and
Mueller, Aaron and
Ross, Candace and
Shah, Raj Sanjay and
Warstadt, Alex and
Wilcox, Ethan Gotlieb and
Williams, Adina",
booktitle = "Proceedings of the First BabyLM Workshop",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.babylm-main.25/",
pages = "323--355",
ISBN = "TODO",
abstract = "Multi-turn dialogues between a child and caregiver are characterized by a property called contingency {--} prompt, direct, and meaningful exchanges between interlocutors. We introduce ContingentChat, a Teacher{--}Student framework that benchmarks and improves multi-turn contingency in a BabyLM trained on 100M words. Using a novel alignment dataset for post-training, BabyLM generates responses that are more grammatical and cohesive. Experiments with adaptive Teacher decoding strategies show limited additional gains. ContingentChat highlights the positive benefits of targeted post-training on dialogue quality and presents contingency as a challenging goal for BabyLMs."
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%0 Conference Proceedings %T Teacher Demonstrations in a BabyLM’s Zone of Proximal Development for Contingent Multi-Turn Interaction %A Salhan, Suchir %A Gu, Hongyi %A Rooein, Donya %A Galvan-Sosa, Diana %A Gaudeau, Gabrielle %A Caines, Andrew %A Yuan, Zheng %A Buttery, Paula %Y Charpentier, Lucas %Y Choshen, Leshem %Y Cotterell, Ryan %Y Gul, Mustafa Omer %Y Hu, Michael Y. %Y Liu, Jing %Y Jumelet, Jaap %Y Linzen, Tal %Y Mueller, Aaron %Y Ross, Candace %Y Shah, Raj Sanjay %Y Warstadt, Alex %Y Wilcox, Ethan Gotlieb %Y Williams, Adina %S Proceedings of the First BabyLM Workshop %D 2025 %8 November %I Association for Computational Linguistics %C Suzhou, China %@ TODO %F salhan-etal-2025-teacher %X Multi-turn dialogues between a child and caregiver are characterized by a property called contingency – prompt, direct, and meaningful exchanges between interlocutors. We introduce ContingentChat, a Teacher–Student framework that benchmarks and improves multi-turn contingency in a BabyLM trained on 100M words. Using a novel alignment dataset for post-training, BabyLM generates responses that are more grammatical and cohesive. Experiments with adaptive Teacher decoding strategies show limited additional gains. ContingentChat highlights the positive benefits of targeted post-training on dialogue quality and presents contingency as a challenging goal for BabyLMs. %U https://aclanthology.org/2025.babylm-main.25/ %P 323-355
Markdown (Informal)
[Teacher Demonstrations in a BabyLM’s Zone of Proximal Development for Contingent Multi-Turn Interaction](https://aclanthology.org/2025.babylm-main.25/) (Salhan et al., BabyLM 2025)
- Teacher Demonstrations in a BabyLM’s Zone of Proximal Development for Contingent Multi-Turn Interaction (Salhan et al., BabyLM 2025)
ACL
- Suchir Salhan, Hongyi Gu, Donya Rooein, Diana Galvan-Sosa, Gabrielle Gaudeau, Andrew Caines, Zheng Yuan, and Paula Buttery. 2025. Teacher Demonstrations in a BabyLM’s Zone of Proximal Development for Contingent Multi-Turn Interaction. In Proceedings of the First BabyLM Workshop, pages 323–355, Suzhou, China. Association for Computational Linguistics.