Question Generation
221 papers with code • 10 benchmarks • 25 datasets
The goal of Question Generation is to generate a valid and fluent question according to a given passage and the target answer. Question Generation can be used in many scenarios, such as automatic tutoring systems, improving the performance of Question Answering models and enabling chatbots to lead a conversation.
Benchmarks
These leaderboards are used to track progress in Question Generation
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Libraries
Use these libraries to find Question Generation models and implementations
MS COCO
SQuAD
Natural Questions
TriviaQA
OK-VQA
XQuAD
SciQ
VQG
HybridQA
ROPES
Most implemented papers
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
huggingface/transformers
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arXiv 2019
Transfer learning, where a model is first pre-trained on a data-rich task before being fine-tuned on a downstream task, has emerged as a powerful technique in natural language processing (NLP).
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models
ashwinkalyan/dbs
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We observe that our method consistently outperforms BS and previously proposed techniques for diverse decoding from neural sequence models.
Learning to Ask: Neural Question Generation for Reading Comprehension
xinyadu/nqg
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ACL 2017
We study automatic question generation for sentences from text passages in reading comprehension.
Unified Language Model Pre-training for Natural Language Understanding and Generation
microsoft/unilm
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NeurIPS 2019
This paper presents a new Unified pre-trained Language Model (UniLM) that can be fine-tuned for both natural language understanding and generation tasks.
Neural Question Generation from Text: A Preliminary Study
magic282/NQG
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Automatic question generation aims to generate questions from a text passage where the generated questions can be answered by certain sub-spans of the given passage.
Machine Comprehension by Text-to-Text Neural Question Generation
bloomsburyai/question-generation
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WS 2017
We propose a recurrent neural model that generates natural-language questions from documents, conditioned on answers.
Synthetic QA Corpora Generation with Roundtrip Consistency
patil-suraj/question_generation
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ACL 2019
We introduce a novel method of generating synthetic question answering corpora by combining models of question generation and answer extraction, and by filtering the results to ensure roundtrip consistency.
ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training
This paper presents a new sequence-to-sequence pre-training model called ProphetNet, which introduces a novel self-supervised objective named future n-gram prediction and the proposed n-stream self-attention mechanism.
ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation
Current pre-training works in natural language generation pay little attention to the problem of exposure bias on downstream tasks.
Simplifying Paragraph-level Question Generation via Transformer Language Models
patil-suraj/question_generation
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Question generation (QG) is a natural language generation task where a model is trained to ask questions corresponding to some input text.
