Browse SoTA > Natural Language Processing > Text Generation > Question-Answer-Generation

Question-Answer-Generation

2 papers with code · Natural Language Processing
Subtask of Text Generation

Benchmarks

No evaluation results yet. Help compare methods by submit evaluation metrics.

Greatest papers with code

Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs

ACL 2020 seanie12/Info-HCVAE

We validate our Information Maximizing Hierarchical Conditional Variational AutoEncoder (Info-HCVAE) on several benchmark datasets by evaluating the performance of the QA model (BERT-base) using only the generated QA pairs (QA-based evaluation) or by using both the generated and human-labeled pairs (semi-supervised learning) for training, against state-of-the-art baseline models.

LATENT VARIABLE MODELS QUESTION-ANSWER-GENERATION QUESTION ANSWERING QUESTION GENERATION

Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus

27 Jan 2020bangliu/ACS-QG

In this paper, we propose Answer-Clue-Style-aware Question Generation (ACS-QG), which aims at automatically generating high-quality and diverse question-answer pairs from unlabeled text corpus at scale by imitating the way a human asks questions.

CHATBOT MACHINE READING COMPREHENSION QUESTION-ANSWER-GENERATION QUESTION ANSWERING QUESTION GENERATION