Question Generation
223 papers with code • 8 benchmarks • 23 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
SciQ
VQG
HybridQA
ROPES
FairytaleQA
Most implemented papers
Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation
ThomasScialom/QuestEval
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EMNLP 2021
QuestEval is a reference-less metric used in text-to-text tasks, that compares the generated summaries directly to the source text, by automatically asking and answering questions.
DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation by Augmenting Pretrained Multilingual Encoders
microsoft/unilm
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While pretrained encoders have achieved success in various natural language understanding (NLU) tasks, there is a gap between these pretrained encoders and natural language generation (NLG).
Transformer Models for Text Coherence Assessment
tushar117/Transformer-Models-for-Text-Coherence-Assessment
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Coherence is an important aspect of text quality and is crucial for ensuring its readability.
TruthfulQA: Measuring How Models Mimic Human Falsehoods
sylinrl/truthfulqa
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ACL 2022
We crafted questions that some humans would answer falsely due to a false belief or misconception.
All You May Need for VQA are Image Captions
Visual Question Answering (VQA) has benefited from increasingly sophisticated models, but has not enjoyed the same level of engagement in terms of data creation.
Joint Generator-Ranker Learning for Natural Language Generation
Generate-then-rank is a widely used mechanism for text generation, where a generator produces multiple text candidates and a ranker chooses the best one among the text candidates.
ClarifyDelphi: Reinforced Clarification Questions with Defeasibility Rewards for Social and Moral Situations
Context is everything, even in commonsense moral reasoning.
Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus
imatge-upc/vqa-2016-cvprw
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ACL 2016
Over the past decade, large-scale supervised learning corpora have enabled machine learning researchers to make substantial advances.
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
We investigate the integration of a planning mechanism into sequence-to-sequence models using attention.
Zero-Shot Question Generation from Knowledge Graphs for Unseen Predicates and Entity Types
We present a neural model for question generation from knowledge base triples in a "Zero-Shot" setup, that is generating questions for triples containing predicates, subject types or object types that were not seen at training time.
