Papers by Benoit Favre
Typological Features for Multilingual Delexicalised Dependency Parsing (N19-1)
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| Challenge: | Existing universal models to describe the syntax of languages are debated for decades . a new study examines the plausibility of universal grammars in dependency parsing . |
| Approach: | They propose to use typological features to describe the syntax of languages to train a multilingual dependency parser. |
| Outcome: | The proposed model can be trained on 40 languages with the help of typological features. |
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. |
Adding Syntactic Annotations to Flickr30k Entities Corpus for Multimodal Ambiguous Prepositional-Phrase Attachment Resolution (L18-1)
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| Challenge: | Using visual features extracted from an image, we propose to study the joint processing of image and language features for the Preposition-Phrase attachment disambiguation task. |
| Approach: | They propose to add syntactic annotations to the captions of the Flickr30k Entities corpus to study the joint processing of image and language features for the Preposition-Phrase attachment disambiguation task. |
| Outcome: | The proposed framework is based on the captions of the Flickr30k Entities corpus and is automatically projected on their French and German translations. |
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. |
Statistical Deficiency for Task Inclusion Estimation (2025.acl-long)
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Loïc Fosse, Frederic Bechet, Benoit Favre, Géraldine Damnati, Gwénolé Lecorvé, Maxime Darrin, Philippe Formont, Pablo Piantanida
| Challenge: | Tasks are central in machine learning, as they are the most natural objects to assess the capabilities of current models. |
| Approach: | They propose a theoretically grounded setup to define the notion of task and compute the inclusion between two tasks from a statistical deficiency point of view. |
| Outcome: | The proposed model estimates the degree of inclusion between tasks on synthetic data and reconstructs the classic NLP pipeline. |