Team Groningen-Bielefeld @ BabyLM 2025
Bastian Bunzeck
bbunzeck
AI & ML interests
Cognitive and usage-based approaches to language modeling, language acquisition in humans and machines, small and efficient language models
Recent Activity
upvoted
a
collection
5 days ago
BabyBabelLM
updated
a collection
16 days ago
Communicative BabyLM
updated
a collection
16 days ago
Communicative BabyLM
Organizations
German BabyLM
Data that can be used for developing developmentally plausible language models in German.
Fifty shapes of BLiMP: syntactic learning curves in LMs
Models analyzed in our 2024 MILLing paper: https://aclanthology.org/2024.clasp-1.7/
Word learning in small LMs
Small Language Models Also Work With Small Vocabularies
Models and evaluation data for our 2025 COLING paper (https://aclanthology.org/2025.coling-main.404/).
GPT-wee: How Small Can a Small Language Model Really Get?
Models trained as submission for BabyLM challenge 2023. Paper: https://aclanthology.org/2023.conll-babylm.2
BabyLM 2025
Team Groningen-Bielefeld @ BabyLM 2025
Word learning in small LMs
German BabyLM
Data that can be used for developing developmentally plausible language models in German.
Small Language Models Also Work With Small Vocabularies
Models and evaluation data for our 2025 COLING paper (https://aclanthology.org/2025.coling-main.404/).
Fifty shapes of BLiMP: syntactic learning curves in LMs
Models analyzed in our 2024 MILLing paper: https://aclanthology.org/2024.clasp-1.7/
GPT-wee: How Small Can a Small Language Model Really Get?
Models trained as submission for BabyLM challenge 2023. Paper: https://aclanthology.org/2023.conll-babylm.2