Skip to content

AMU-EURANOVA at CASE 2021 Task 1: Assessing the stability of multilingual BERT

This paper explains our participation in task 1of the CASE 2021 shared task. This task is about multilingual event extraction from the news. We focused on sub-task 4, event information extraction. This sub-task has a small training dataset, and we fine-tuned a multilingual BERT to solve this sub-task. We studied the instability problem on the dataset and tried to mitigate it.

Léo Bouscarrat, Antoine Bonnefoy, Cécile Capponi, Carlos Ramisch, AMU-EURANOVA at CASE 2021 Task 1: Assessing the stability of multilingual BERT, In Proc. of the 4th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021). Association for Computational Linguistics (ACL), 2021.

Click here to access the paper.

Releated Posts

Evaluation of GraphRAG Strategies for Efficient Information Retrieval

Traditional RAG systems struggle to capture relationships and cross-references between different sources unless explicitly mentioned. This challenge is common in real-world scenarios, where information is often distributed and interlinked, making graphs a more effective representation. Our work provides a technical contribution through a comparative evaluation of retrieval strategies within GraphRAG, focusing on context relevance rather than abstract metrics. We aim to offer practitioners actionable insights into the retrieval component of the GraphRAG pipeline.
Read More

Flight Load Factor Predictions based on Analysis of Ticket Prices and other Factors

The ability to forecast traffic and to size the operation accordingly is a determining factor, for airports. However, to realise its full potential, it needs to be considered as part of a holistic approach, closely linked to airport planning and operations. To ensure airport resources are used efficiently, accurate information about passenger numbers and their effects on the operation is essential. Therefore, this study explores machine learning capabilities enabling predictions of aircraft load factors.
Read More