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 201225 of 664 papers

TitleStatusHype
Pre-Training With Scientific Text Improves Educational Question Generation0
Automatically generating question-answer pairs for assessing basic reading comprehension in SwedishCode0
Question Answering and Question Generation for Finnish0
Automatic Generation of Socratic Subquestions for Teaching Math Word ProblemsCode1
Look, Read and Ask: Learning to Ask Questions by Reading Text in Images0
Best-k Search Algorithm for Neural Text Generation0
Consecutive Question Generation via Dynamic Multitask Learning0
Collaborative and AI-aided Exam Question Generation using Wikidata in EducationCode1
Reasoning Circuits: Few-shot Multihop Question Generation with Structured Rationales0
Learning to Answer Multilingual and Code-Mixed Questions0
Why Did the Chicken Cross the Road? Rephrasing and Analyzing Ambiguous Questions in VQACode0
Multi-VQG: Generating Engaging Questions for Multiple ImagesCode0
Discord Questions: A Computational Approach To Diversity Analysis in News CoverageCode0
RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the QuestionCode1
Applying Information Extraction to Storybook Question and Answer Generation0
Learning to Reuse Distractors to support Multiple Choice Question Generation in EducationCode0
IDK-MRC: Unanswerable Questions for Indonesian Machine Reading ComprehensionCode0
Varifocal Question Generation for Fact-checkingCode0
P^3LM: Probabilistically Permuted Prophet Language Modeling for Generative Pre-Training0
CONSISTENT: Open-Ended Question Generation From News ArticlesCode0
Adversarial and Safely Scaled Question Generation0
PACIFIC: Towards Proactive Conversational Question Answering over Tabular and Textual Data in FinanceCode1
Shortcomings of Question Answering Based Factuality Frameworks for Error LocalizationCode0
Closed-book Question Generation via Contrastive LearningCode0
Towards End-to-End Open Conversational Machine ReadingCode0
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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