no code implementations • 20 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.
no code implementations • 16 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.
no code implementations • 31 Oct 2022 • Yanzhu Guo, Chloé Clavel, Moussa Kamal Eddine, Michalis Vazirgiannis
Due to this lack of well-defined formulation, a large number of popular abstractive summarization datasets are constructed in a manner that neither guarantees validity nor meets one of the most essential criteria of summarization: factual consistency.
no code implementations • PoliticalNLP (LREC) 2022 • Hadi Abdine, Yanzhu Guo, Virgile Rennard, Michalis Vazirgiannis
We perform community detection on a retweet graph of users and propose an in-depth analysis of the stance of each community.
no code implementations • 1 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.
no code implementations • WNUT (ACL) 2021 • Yanzhu Guo, Virgile Rennard, Christos Xypolopoulos, Michalis Vazirgiannis
We make our model publicly available in the transformers library with the aim of promoting future research in analytic tasks for French tweets.
no code implementations • 15 Feb 2021 • Yanzhu Guo, Christos Xypolopoulos, Michalis Vazirgiannis
We employ an alignment-based approach to compare these embeddings with a general-purpose Twitter embedding unrelated to COVID-19.