Irene Huang, Wei Lin, et al.
NeurIPS 2024
Models for text generation have become focal for many research tasks and especially for the generation of sentence corpora. However, understanding the properties of an automatically generated text corpus remains challenging. We propose a set of tools that examine the properties of generated text corpora. Applying these tools on various generated corpora allowed us to gain new insights into the properties of the generative models. As part of our characterization process, we found remarkable differences in the corpora generated by two leading generative technologies.
Irene Huang, Wei Lin, et al.
NeurIPS 2024
Oscar Sainz, Iker García-ferrero, et al.
ACL 2024
Ilya Shnayderman, Liat Ein-Dor, et al.
arXiv
Masayasu Muraoka, Tetsuya Nasukawa, et al.
EMNLP 2020