9 citations · 22 across the 9 of their papers we have counts for
7 papers · 1 filter
Benchmarking Linguistic Diversity of Large Language Models
Yanzhu Guo, Guokan Shang, Chloé Clavel
The development and evaluation of Large Language Models (LLMs) has primarily focused on their task-solving capabilities, with recent models even surpassing human performance in som…
Do Large Language Models Have an English Accent? Evaluating and Improving the Naturalness of Multilingual LLMs
Yanzhu Guo, Simone Conia, Zelin Zhou +3
Current Large Language Models (LLMs) are predominantly designed with English as the primary language, and even the few that are multilingual tend to exhibit strong English-centric…
Automatic Analysis of Substantiation in Scientific Peer Reviews
Yanzhu Guo, Guokan Shang, Virgile Rennard +2
With the increasing amount of problematic peer reviews in top AI conferences, the community is urgently in need of automatic quality control measures. In this paper, we restrict ou…
The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text
Yanzhu Guo, Guokan Shang, Michalis Vazirgiannis +1
This study investigates the consequences of training language models on synthetic data generated by their predecessors, an increasingly prevalent practice given the prominence of p…
Questioning the Validity of Summarization Datasets and Improving Their Factual Consistency
Yanzhu Guo, Chloé Clavel, Moussa Kamal Eddine +1
The topic of summarization evaluation has recently attracted a surge of attention due to the rapid development of abstractive summarization systems. However, the formulation of the…
BERTweetFR : Domain Adaptation of Pre-Trained Language Models for French Tweets
Yanzhu Guo, Virgile Rennard, Christos Xypolopoulos +1
We introduce BERTweetFR, the first large-scale pre-trained language model for French tweets. Our model is initialized using the general-domain French language model CamemBERT which…
How COVID-19 Is Changing Our Language : Detecting Semantic Shift in Twitter Word Embeddings
Yanzhu Guo, Christos Xypolopoulos, Michalis Vazirgiannis
Words are malleable objects, influenced by events that are reflected in written texts. Situated in the global outbreak of COVID-19, our research aims at detecting semantic shifts i…