5 citations · 13 across the 4 of their papers we have counts for
5 papers
Which Discriminator for Cooperative Text Generation?
Antoine Chaffin, Thomas Scialom, Sylvain Lamprier +4
Language models generate texts by successively predicting probability distributions for next tokens given past ones. A growing field of interest tries to leverage external informat…
Generative Cooperative Networks for Natural Language Generation
Sylvain Lamprier, Thomas Scialom, Antoine Chaffin +4
Generative Adversarial Networks (GANs) have known a tremendous success for many continuous generation tasks, especially in the field of image generation. However, for discrete outp…
Generating artificial texts as substitution or complement of training data
Vincent Claveau, Antoine Chaffin, Ewa Kijak
The quality of artificially generated texts has considerably improved with the advent of transformers. The question of using these models to generate learning data for supervised l…
PPL-MCTS: Constrained Textual Generation Through Discriminator-Guided MCTS Decoding
Antoine Chaffin, Vincent Claveau, Ewa Kijak
Large language models (LM) based on Transformers allow to generate plausible long texts. In this paper, we explore how this generation can be further controlled at decoding time to…
Query expansion with artificially generated texts
Vincent Claveau
A well-known way to improve the performance of document retrieval is to expand the user's query. Several approaches have been proposed in the literature, and some of them are consi…