SOTAVerified

Question Generation

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.

Source: Generating Highly Relevant Questions

Papers

Showing 351400 of 664 papers

TitleStatusHype
A Unified Abstractive Model for Generating Question-Answer Pairs0
How Well Do You Know Your Audience? Toward Socially-aware Question Generation0
MixQG: Neural Question Generation with Mixed Answer TypesCode1
Guiding Visual Question Generation0
Retrieval-guided Counterfactual Generation for QA0
MMIU: Dataset for Visual Intent Understanding in Multimodal Assistants0
Simple or Complex? Complexity-Controllable Question Generation with Soft Templates and Deep Mixture of Experts Model0
Decision-Theoretic Question Generation for Situated Reference Resolution: An Empirical Study and Computational Model0
I Do Not Understand What I Cannot Define: Automatic Question Generation With Pedagogically-Driven Content Selection0
The Impact of Answers in Referential Visual Dialog0
A Survey of Approaches to Automatic Question Generation:from 2019 to Early 20210
Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical OverlapCode0
A Simple and Effective Model for Multi-Hop Question Generation0
Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules0
Question Generation for Generating Textbook Flashcards0
Context-NER : Contextual Phrase Generation at ScaleCode1
Reframing Instructional Prompts to GPTk's Language0
Improving Unsupervised Question Answering via Summarization-Informed Question Generation0
Topic Transferable Table Question AnsweringCode0
Asking Questions Like Educational Experts: Automatically Generating Question-Answer Pairs on Real-World Examination Data0
Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation LearningCode0
Asking It All: Generating Contextualized Questions for any Semantic RoleCode0
Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints0
TruthfulQA: Measuring How Models Mimic Human FalsehoodsCode1
Transformer Models for Text Coherence AssessmentCode1
On Generating Fact-Infused Question VariationsCode0
Contrastive Domain Adaptation for Question Answering using Limited Text CorporaCode1
Generating Answer Candidates for Quizzes and Answer-Aware Question Generators0
Smoothing Dialogue States for Open Conversational Machine ReadingCode0
Semantic-Based Self-Critical Training For Question GenerationCode1
INVIGORATE: Interactive Visual Grounding and Grasping in Clutter0
MTG: A Benchmark Suite for Multilingual Text GenerationCode0
Automatic Learning Assistant in Telugu0
Multi-Lingual Question Generation with Language Agnostic Language ModelCode0
Latent Reasoning for Low-Resource Question Generation0
Restatement and Question Generation for Counsellor Chatbot0
Exploring Input Representation Granularity for Generating Questions Satisfying Question-Answer Congruence0
基于迭代信息传递和滑动窗口注意力的问题生成模型研究(Question Generation Model Based on Iterative Message Passing and Sliding Windows Hierarchical Attention)0
Continuous Language Generative FlowCode1
Engage the Public: Poll Question Generation for Social Media PostsCode0
On Training Instance Selection for Few-Shot Neural Text Generation0
Incremental temporal summarization in multi-party meetings0
Controllable Open-ended Question Generation with A New Question Type OntologyCode1
Reinforcement Learning for Abstractive Question Summarization with Question-aware Semantic RewardsCode1
Unified Questioner Transformer for Descriptive Question Generation in Goal-Oriented Visual DialogueCode0
DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation by Augmenting Pretrained Multilingual EncodersCode0
Learning to Rank Question Answer Pairs with Bilateral Contrastive Data Augmentation0
Enhancing Question Generation with Commonsense Knowledge0
JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge GraphsCode1
To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ERNIE-GENLARGE (beam size=5)BLEU-425.41Unverified
2BART (TextBox 2.0)BLEU-425.08Unverified
3ProphetNet + ASGenBLEU-424.44Unverified
4UniLMv2BLEU-424.43Unverified
5ProphetNet + syn. mask + localnessBLEU-424.37Unverified
6ProphetNetBLEU-423.91Unverified
7UniLM + ASGenBLEU-423.7Unverified
8UniLMBLEU-422.78Unverified
9BERTSQGBLEU-422.17Unverified
10Selector & NQG++BLEU-415.87Unverified
#ModelMetricClaimedVerifiedStatus
1MDNBLEU-165.1Unverified
2coco-Caption [[Karpathy and Li2014]]BLEU-162.5Unverified
3Max(Yang,2015)BLEU-159.4Unverified
4Sample(Yang,2015)BLEU-138.8Unverified
#ModelMetricClaimedVerifiedStatus
1FactJointGTMETEOR36.21Unverified
2JointGTMETEOR36.08Unverified
3FactT5BMETEOR35.72Unverified
4T5BMETEOR35.64Unverified
#ModelMetricClaimedVerifiedStatus
1FactT5BBLEU46.1Unverified
2JointGTBLEU45.95Unverified
3T5BBLEU44.51Unverified
4FactJointGTBLEU43.61Unverified
#ModelMetricClaimedVerifiedStatus
1JointGTMETEOR37.69Unverified
2FactJointGTMETEOR37.55Unverified
3FactT5BMETEOR37.39Unverified
4T5BMETEOR37.35Unverified
#ModelMetricClaimedVerifiedStatus
1BART fine-tuned on FairytaleQAROUGE-L0.53Unverified
2BART fine-tuned on NarrativeQA and FairytaleQAROUGE-L0.52Unverified
3BART fine-tuned on NarrativeQAROUGE-L0.44Unverified
#ModelMetricClaimedVerifiedStatus
1UniPollROUGE-149.6Unverified
2T5ROUGE-144.46Unverified
3Dual DecROUGE-138.24Unverified
#ModelMetricClaimedVerifiedStatus
1Info-HCVAEQAE37.18Unverified
2HCVAEQAE31.45Unverified
#ModelMetricClaimedVerifiedStatus
1Info-HCVAEQAE71.18Unverified
2HCVAEQAE69.46Unverified
#ModelMetricClaimedVerifiedStatus
1Info-HCVAEQAE35.45Unverified
2HCVAEQAE30.2Unverified
#ModelMetricClaimedVerifiedStatus
1MDNBLEU-136Unverified