244 citations · 360 across the 13 of their papers we have counts for
3 papers · 2 filters
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…