Search Results for author: Guokan Shang

Found 13 papers, 6 papers with code

Leveraging Discourse Structure for Extractive Meeting Summarization

no code implementations17 May 2024 Virgile Rennard, Guokan Shang, Michalis Vazirgiannis, Julie Hunter

We introduce an extractive summarization system for meetings that leverages discourse structure to better identify salient information from complex multi-party discussions.

Extractive Summarization Meeting Summarization +1

FREDSum: A Dialogue Summarization Corpus for French Political Debates

1 code implementation8 Dec 2023 Virgile Rennard, Guokan Shang, Damien Grari, Julie Hunter, Michalis Vazirgiannis

In this paper, we present a dataset of French political debates for the purpose of enhancing resources for multi-lingual dialogue summarization.

Abstractive Text Summarization Decoder

The Claire French Dialogue Dataset

no code implementations28 Nov 2023 Julie Hunter, Jérôme Louradour, Virgile Rennard, Ismaïl Harrando, Guokan Shang, Jean-Pierre Lorré

We present the Claire French Dialogue Dataset (CFDD), a resource created by members of LINAGORA Labs in the context of the OpenLLM France initiative.

Automatic Analysis of Substantiation in Scientific Peer Reviews

no code implementations20 Nov 2023 Yanzhu Guo, Guokan Shang, Virgile Rennard, Michalis Vazirgiannis, Chloé Clavel

With the increasing amount of problematic peer reviews in top AI conferences, the community is urgently in need of automatic quality control measures.

Argument Mining

The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

no code implementations16 Nov 2023 Yanzhu Guo, Guokan Shang, Michalis Vazirgiannis, Chloé Clavel

This study investigates the consequences of training language models on synthetic data generated by their predecessors, an increasingly prevalent practice given the prominence of powerful generative models.

Text Generation

DATScore: Evaluating Translation with Data Augmented Translations

no code implementations12 Oct 2022 Moussa Kamal Eddine, Guokan Shang, Michalis Vazirgiannis

The rapid development of large pretrained language models has revolutionized not only the field of Natural Language Generation (NLG) but also its evaluation.

Data Augmentation Language Modelling +3

Abstractive Meeting Summarization: A Survey

2 code implementations8 Aug 2022 Virgile Rennard, Guokan Shang, Julie Hunter, Michalis Vazirgiannis

A system that could reliably identify and sum up the most important points of a conversation would be valuable in a wide variety of real-world contexts, from business meetings to medical consultations to customer service calls.

Abstractive Dialogue Summarization Abstractive Text Summarization +3

NLP Research and Resources at DaSciM, Ecole Polytechnique

no code implementations1 Dec 2021 Hadi Abdine, Yanzhu Guo, Moussa Kamal Eddine, Giannis Nikolentzos, Stamatis Outsios, Guokan Shang, Christos Xypolopoulos, Michalis Vazirgiannis

DaSciM (Data Science and Mining) part of LIX at Ecole Polytechnique, established in 2013 and since then producing research results in the area of large scale data analysis via methods of machine and deep learning.

Energy-based Self-attentive Learning of Abstractive Communities for Spoken Language Understanding

1 code implementation Asian Chapter of the Association for Computational Linguistics 2020 Guokan Shang, Antoine Jean-Pierre Tixier, Michalis Vazirgiannis, Jean-Pierre Lorré

Abstractive community detection is an important spoken language understanding task, whose goal is to group utterances in a conversation according to whether they can be jointly summarized by a common abstractive sentence.

Clustering Community Detection +2

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