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Question Generation

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하위 태스크: 1
평가표: 11
보존된 평가 기록: 42

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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/qipeng/stay-hungry-stay-focused

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Stay Hungry, Stay Focused: Generating Informative and Specific Questions in Information-Seeking Conversations

https://github.com/raidium-med/mqg

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Efficient Medical Question Answering with Knowledge-Augmented Question Generation

https://github.com/recitalAI/QuestEval

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Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation

https://github.com/renmengye/imageqa-public

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Exploring Models and Data for Image Question Answering

https://github.com/rifkiaputri/idk-mrc

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IDK-MRC: Unanswerable Questions for Indonesian Machine Reading Comprehension

https://github.com/ritikamangla/qsalience

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Which questions should I answer? Salience Prediction of Inquisitive Questions

https://github.com/roemmele/answerquest

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AnswerQuest: A System for Generating Question-Answer Items from Multi-Paragraph Documents

https://github.com/ruckbreasoning/sgsh

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SGSH: Stimulate Large Language Models with Skeleton Heuristics for Knowledge Base Question Generation

https://github.com/ryokamoi/qa-metrics-human-annotation

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Shortcomings of Question Answering Based Factuality Frameworks for Error Localization

https://github.com/salesforce/discord_questions

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Discord Questions: A Computational Approach To Diversity Analysis in News Coverage

https://github.com/salesforce/nnd_evaluation

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Near-Negative Distinction: Giving a Second Life to Human Evaluation Datasets

https://github.com/salesforce/qafacteval

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QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization

https://github.com/salesforce/qgen

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MixQG: Neural Question Generation with Mixed Answer Types

https://github.com/salesforce/socratic-pretraining

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Socratic Pretraining: Question-Driven Pretraining for Controllable Summarization

https://github.com/sarthak268/c3vqg-official

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C3VQG: Category Consistent Cyclic Visual Question Generation

https://github.com/seanie12/CLAPS

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Contrastive Learning with Adversarial Perturbations for Conditional Text Generation

https://github.com/seanie12/Info-HCVAE

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

https://github.com/searchableai/ChainCQG

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ChainCQG: Flow-Aware Conversational Question Generation

https://github.com/semerekiros/dist-retrieval

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Learning to Reuse Distractors to support Multiple Choice Question Generation in Education

https://github.com/seonjeonghwang/e2eqr

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Explainable Multi-hop Question Generation: An End-to-End Approach without Intermediate Question Labeling

https://github.com/shmsw25/DecompRC

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Multi-hop Reading Comprehension through Question Decomposition and Rescoring

https://github.com/shwetanlp/CHQ-Summ

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Reinforcement Learning for Abstractive Question Summarization with Question-aware Semantic Rewards

https://github.com/smatsumori/uniqer

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Unified Questioner Transformer for Descriptive Question Generation in Goal-Oriented Visual Dialogue

https://github.com/ssu-humane/hero

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HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World Claims

https://github.com/sulcantonin/llm_neuralips23

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PACuna: Automated Fine-Tuning of Language Models for Particle Accelerators

https://github.com/sunjiao123sun/llm-controlgen

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Evaluating Large Language Models on Controlled Generation Tasks

https://github.com/sunlab-osu/CliniQG4QA

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CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answering

https://github.com/sylinrl/truthfulqa

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TruthfulQA: Measuring How Models Mimic Human Falsehoods

https://github.com/tagoyal/dae-factuality

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Evaluating Factuality in Generation with Dependency-level Entailment

https://github.com/tal-ai/make_emnlp2021

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Mathematical Word Problem Generation from Commonsense Knowledge Graph and Equations

https://github.com/teacherpeterpan/Unsupervised-Multi-hop-QA

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Unsupervised Multi-hop Question Answering by Question Generation

https://github.com/thephukan/ecis-vqg

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ECIS-VQG: Generation of Entity-centric Information-seeking Questions from Videos

https://github.com/thu-coai/JointGT

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JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs

https://github.com/tshu-w/dbcopilot

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DBCopilot: Natural Language Querying over Massive Databases via Schema Routing

https://github.com/tuhinjubcse/opendomainquestiongeneration

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CONSISTENT: Open-Ended Question Generation From News Articles

https://github.com/tushar117/Transformer-Models-for-Text-Coherence-Assessment

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Transformer Models for Text Coherence Assessment

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