244 citations · 360 across the 13 of their papers we have counts for
5 papers · 1 filter
Can GPT models Follow Human Summarization Guidelines? A Study for Targeted Communication Goals
Yongxin Zhou, Fabien Ringeval, François Portet
This study investigates the ability of GPT models (ChatGPT, GPT-4 and GPT-4o) to generate dialogue summaries that adhere to human guidelines. Our evaluation involved experimenting…
LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech
Titouan Parcollet, Ha Nguyen, Solene Evain +19
Self-supervised learning (SSL) is at the origin of unprecedented improvements in many different domains including computer vision and natural language processing. Speech processing…
PSentScore: Evaluating Sentiment Polarity in Dialogue Summarization
Yongxin Zhou, Fabien Ringeval, François Portet
Automatic dialogue summarization is a well-established task with the goal of distilling the most crucial information from human conversations into concise textual summaries. Howeve…
Effectiveness of French Language Models on Abstractive Dialogue Summarization Task
Yongxin Zhou, François Portet, Fabien Ringeval
Pre-trained language models have established the state-of-the-art on various natural language processing tasks, including dialogue summarization, which allows the reader to quickly…
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
Solene Evain, Ha Nguyen, Hang Le +15
Self-Supervised Learning (SSL) using huge unlabeled data has been successfully explored for image and natural language processing. Recent works also investigated SSL from speech. T…