Resources for the "Evaluating the Factual Consistency of Abstractive Text Summarization" paper

Code and Data for EMNLP2020 Paper "KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation"

MS MARCO(Microsoft Machine Reading Comprehension) is a large scale dataset focused on machine reading comprehension, question answering, and passage/document ranking

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Labeled sentences from IMDb movie reviews

BLEURT is a metric for Natural Language Generation based on transfer learning.

S2ORC: The Semantic Scholar Open Research Corpus: https://www.aclweb.org/anthology/2020.acl-main.447/

SPECTER: Document-level Representation Learning using Citation-informed Transformers

Supplementary material for "When and Why Are Pre-trained Word Embeddings Useful for Neural Machine Translation?" at NAACL 2018

Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"