BabyLM Turns 4 and Goes Multilingual: Call for Papers for the 2026 BabyLM Workshop
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , , , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866910031907127296 |
|---|---|
| author | Choshen, Leshem Cotterell, Ryan Gul, Mustafa Omer Jumelet, Jaap Linzen, Tal Mueller, Aaron Salhan, Suchir Shah, Raj Sanjay Warstadt, Alex Wilcox, Ethan Gotlieb |
| author_facet | Choshen, Leshem Cotterell, Ryan Gul, Mustafa Omer Jumelet, Jaap Linzen, Tal Mueller, Aaron Salhan, Suchir Shah, Raj Sanjay Warstadt, Alex Wilcox, Ethan Gotlieb |
| contents | The goal of the BabyLM is to stimulate new research connections between cognitive modeling and language model pretraining. We invite contributions in this vein to the BabyLM Workshop, which will also include the 4th iteration of the BabyLM Challenge. As in previous years, the challenge features two ``standard'' tracks (Strict and Strict-Small), in which participants must train language models on under 100M or 10M words of data, respectively. This year, we move beyond our previous English-only pretraining datasets with a new Multilingual track, focusing on English, Dutch, and Chinese. For the workshop, we call for papers related to the overall theme of BabyLM, which includes training efficiency, small-scale training datasets, cognitive modeling, model evaluation, and architecture innovation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_20092 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | BabyLM Turns 4 and Goes Multilingual: Call for Papers for the 2026 BabyLM Workshop Choshen, Leshem Cotterell, Ryan Gul, Mustafa Omer Jumelet, Jaap Linzen, Tal Mueller, Aaron Salhan, Suchir Shah, Raj Sanjay Warstadt, Alex Wilcox, Ethan Gotlieb Computation and Language The goal of the BabyLM is to stimulate new research connections between cognitive modeling and language model pretraining. We invite contributions in this vein to the BabyLM Workshop, which will also include the 4th iteration of the BabyLM Challenge. As in previous years, the challenge features two ``standard'' tracks (Strict and Strict-Small), in which participants must train language models on under 100M or 10M words of data, respectively. This year, we move beyond our previous English-only pretraining datasets with a new Multilingual track, focusing on English, Dutch, and Chinese. For the workshop, we call for papers related to the overall theme of BabyLM, which includes training efficiency, small-scale training datasets, cognitive modeling, model evaluation, and architecture innovation. |
| title | BabyLM Turns 4 and Goes Multilingual: Call for Papers for the 2026 BabyLM Workshop |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2602.20092 |