Papers by Caroline Brun
Semantic Context Path Labeling for Semantic Exploration of User Reviews (2021.emnlp-demo)
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| Challenge: | a prototype system for semantic exploration of user reviews is presented . the system enables effective navigation in a rich contextual semantic schema . |
| Approach: | They propose a system that extracts rich and diverse information from informative texts . they use a task to assign types and semantic roles to entities in the reviews . |
| Outcome: | The proposed system can extract rich and diverse information from informative texts . it can be used to explore large quantities of user reviews, which contain useful information . |
What Do Compressed Multilingual Machine Translation Models Forget? (2022.findings-emnlp)
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Alireza Mohammadshahi, Vassilina Nikoulina, Alexandre Berard, Caroline Brun, James Henderson, Laurent Besacier
| Challenge: | Recent studies show that pre-trained models achieve state-of-the-art results in NLP tasks but their size makes it more challenging to apply them in resource-constrained environments. |
| Approach: | They assess the impact of compression methods on multilingual Neural Machine Translation models for various language groups, gender, and semantic biases. |
| Outcome: | The proposed compression methods improve models on different benchmarks for language groups, gender, and semantic biases. |
SMaLL-100: Introducing Shallow Multilingual Machine Translation Model for Low-Resource Languages (2022.emnlp-main)
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Alireza Mohammadshahi, Vassilina Nikoulina, Alexandre Berard, Caroline Brun, James Henderson, Laurent Besacier
| Challenge: | Existing models for multilingual machine translation use scaling up the number of parameters to overcome the curse of multilinguality. |
| Approach: | They propose a multilingual machine translation model that shares information between similar languages and scales up the number of parameters to overcome the curse of multilinguality. |
| Outcome: | The proposed model outperforms previous models on low-resource benchmarks while improving inference latency and memory usage. |