8 papers
Enriching Speech Emotion Representations with Conversational Context
Arthur Peuvot, Romaric Besançon, Gaël de Chalendar +2
Detecting emotions is necessary for building systems that can accurately and adaptively interact with humans. Speech Emotion Recognition (SER) has become an important research focu…
The Deleuzian Representation Hypothesis
Clément Cornet, Romaric Besançon, Hervé Le Borgne
We propose an alternative to sparse autoencoders (SAEs) as a simple and effective unsupervised method for extracting interpretable concepts from neural networks. The core idea is t…
ManufactuBERT: Efficient Continual Pretraining for Manufacturing
Robin Armingaud, Romaric Besançon
While large general-purpose Transformer-based encoders excel at general language understanding, their performance diminishes in specialized domains like manufacturing due to a lack…
GLiDRE: Generalist Lightweight model for Document-level Relation Extraction
Robin Armingaud, Romaric Besançon
Relation Extraction (RE) is a fundamental task in Natural Language Processing, and its document-level variant poses significant challenges, due to complex interactions between enti…
Explaining How Visual, Textual and Multimodal Encoders Share Concepts
Clément Cornet, Romaric Besançon, Hervé Le Borgne
Sparse autoencoders (SAEs) have emerged as a powerful technique for extracting human-interpretable features from neural networks activations. Previous works compared different mode…
From LIMA to DeepLIMA: following a new path of interoperability
Victor Bocharov, Romaric Besançon, Gaël de Chalendar +2
In this article, we describe the architecture of the LIMA (Libre Multilingual Analyzer) framework and its recent evolution with the addition of new text analysis modules based on d…
Automatic Die Studies for Ancient Numismatics
Clément Cornet, Héloïse Aumaître, Romaric Besançon +3
Die studies are fundamental to quantifying ancient monetary production, providing insights into the relationship between coinage, politics, and history. The process requires tediou…
Probing Pretrained Language Models with Hierarchy Properties
Jesús Lovón-Melgarejo, Jose G. Moreno, Romaric Besançon +2
Since Pretrained Language Models (PLMs) are the cornerstone of the most recent Information Retrieval (IR) models, the way they encode semantic knowledge is particularly important.…