563 citations · 573 across the 6 of their papers we have counts for
3 papers · 1 filter
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…
Multitask Prompted Training Enables Zero-Shot Task Generalization
Victor Sanh, Albert Webson, Colin Raffel +38
Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks (Brown et al., 2020). It has been hypothesized that this is a…
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…