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Found 7 papers, 0 papers with code
Automatic Analysis of Substantiation in Scientific Peer Reviews
With the increasing amount of problematic peer reviews in top AI conferences, the community is urgently in need of automatic quality control measures.
The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text
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.
Questioning the Validity of Summarization Datasets and Improving Their Factual Consistency
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.
Political Communities on Twitter: Case Study of the 2022 French Presidential Election
We perform community detection on a retweet graph of users and propose an in-depth analysis of the stance of each community.
NLP Research and Resources at DaSciM, Ecole Polytechnique
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.
BERTweetFR : Domain Adaptation of Pre-Trained Language Models for French Tweets
We make our model publicly available in the transformers library with the aim of promoting future research in analytic tasks for French tweets.
How COVID-19 Is Changing Our Language : Detecting Semantic Shift in Twitter Word Embeddings
We employ an alignment-based approach to compare these embeddings with a general-purpose Twitter embedding unrelated to COVID-19.
