Papers by Abdellah Fourtassi
Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies? (2022.emnlp-main)
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| Challenge: | a recent study examines whether vision-and-language models learn syntactic dependencies . a controlled evaluation of the models is crucial for a precise and rigorous test of their knowledge . |
| Approach: | They propose a task to evaluate understanding of predicate-noun dependencies in a controlled setup. |
| Outcome: | This study compares state-of-the-art models with a case study on predicate-noun dependencies. |
CHICA: A Developmental Corpus of Child-Caregiver’s Face-to-face vs. Video Call Conversations in Middle Childhood (2024.lrec-main)
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Dhia Elhak Goumri, Abhishek Agrawal, Mitja Nikolaus, Hong Duc Thang Vu, Kübra Bodur, Elias Emmar, Cassandre Armand, Chiara Mazzocconi, Shreejata Gupta, Laurent Prévot, Benoit Favre, Leonor Becerra-Bonache, Abdellah Fourtassi
| Challenge: | Existing studies of language-in-interaction focus on the two ends of the developmental spectrum, i.e., early childhood and adulthood, leaving a gap in our knowledge about how development unfolds, especially across middle childhood. |
| Approach: | They propose to use CHICA to analyze child-caregiver conversations at home . they use mobile, lightweight eye-tracking and head motion detection to optimize the naturalness of the recordings. |
| Outcome: | The proposed corpus of child-caregiver conversations at home was compared with a previous corpus based on a set of conversations between children aged 7, 9, and 11 years old. |
Automatic Coding of Contingency in Child-Caregiver Conversations (2024.lrec-main)
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| Challenge: | Current research on children's language development relies on manual annotation of a small sample of children, which limits our ability to draw general conclusions about development. |
| Approach: | They propose to use automatic tools to assess contingency in children's natural interactions with caregivers by annotating a small set of data with a Transformer-based model. |
| Outcome: | The proposed model replicates existing results and generates new data-driven hypotheses. |
BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Data (2026.eacl-long)
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Jaap Jumelet, Abdellah Fourtassi, Akari Haga, Bastian Bunzeck, Bhargav Shandilya, Diana Galvan-Sosa, Faiz Ghifari Haznitrama, Francesca Padovani, Francois Meyer, Hai Hu, Julen Etxaniz, Laurent Prevot, Linyang He, María Grandury, Mila Marcheva, Negar Foroutan, Nikitas Theodoropoulos, Pouya Sadeghi, Siyuan Song, Suchir Salhan, Susana Zhou, Yurii Paniv, Ziyin Zhang, Arianna Bisazza, Alex Warstadt, Leshem Choshen
| Challenge: | prevailing trend in language modeling research is to prioritize scaling, authors say . from infancy to maturity, English learners acquire language through exposure to less than 100M words . |
| Approach: | They propose a multilingual collection of datasets modeling the language a person observes from birth until they acquire a native language. |
| Outcome: | The proposed models outperform models trained on a fixed, developmentally plausible English corpus on various benchmarks. |
Automatic Annotation of Grammaticality in Child-Caregiver Conversations (2024.lrec-main)
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| Challenge: | Existing methods for analyzing child language acquisition have been tedious and inconsistent. |
| Approach: | They propose a coding scheme for context-dependent grammaticality in child-caregiver conversations and annotate 4,000 utterances from a large corpus of transcribed conversations. |
| Outcome: | The proposed method achieves human inter-annotation agreement levels and is faster and reproducible than manual methods. |