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Question Generation
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/CZWin32768/xnlg
공식 코드https://github.com/DevSinghSachan/unsupervised-passage-reranking
공식 코드Improving Passage Retrieval with Zero-Shot Question Generation
https://github.com/Evan-Gao/conversational-QG
공식 코드Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling
https://github.com/FerdiantJoshua/question-generator
공식 코드Sequence-to-Sequence Learning for Indonesian Automatic Question Generator
https://github.com/GSidiropoulos/kgsqa_for_unseen_domains
공식 코드Knowledge Graph Simple Question Answering for Unseen Domains
https://github.com/HLTCHKUST/MulQG
공식 코드Multi-hop Question Generation with Graph Convolutional Network
https://github.com/McGill-NLP/MLQuestions
공식 코드https://github.com/NAACL2018Anonymous/submission
공식 코드Zero-Shot Question Generation from Knowledge Graphs for Unseen Predicates and Entity Types
https://github.com/PaddlePaddle/Research
공식 코드Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsing
https://github.com/PrekshaNema25/Answerability-Metric
공식 코드Towards a Better Metric for Evaluating Question Generation Systems
https://github.com/PrekshaNema25/RefNet-QG
공식 코드Let's Ask Again: Refine Network for Automatic Question Generation
https://github.com/RUCAIBox/TextBox
공식 코드TextBox 2.0: A Text Generation Library with Pre-trained Language Models
https://github.com/Rcrossmeister/RLQG
공식 코드Towards Better Question Generation in QA-based Event Extraction
https://github.com/Shawn617/Multi-hop-NQG
공식 코드Asking Complex Questions with Multi-hop Answer-focused Reasoning
https://github.com/ShuyangCao/open-ended_question_ontology
공식 코드Controllable Open-ended Question Generation with A New Question Type Ontology
https://github.com/ThomasScialom/QuestEval
공식 코드Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation
https://github.com/UKPLab/plms-graph2text
공식 코드Investigating Pretrained Language Models for Graph-to-Text Generation
https://github.com/USArmyResearchLab/ARL-HuRDL
공식 코드How Should Agents Ask Questions For Situated Learning? An Annotated Dialogue Corpus
https://github.com/WING-NUS/SG-Deep-Question-Generation
공식 코드https://github.com/X1AOX1A/UniPoll
공식 코드UniPoll: A Unified Social Media Poll Generation Framework via Multi-Objective Optimization
https://github.com/Yifan-Gao/Discern
공식 코드Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading
https://github.com/YuxiXie/RL-for-Question-Generation
공식 코드Exploring Question-Specific Rewards for Generating Deep Questions
https://github.com/ZJULearning/ReDR
공식 코드Reinforced Dynamic Reasoning for Conversational Question Generation
https://github.com/ZhangShiyue/QGforQA
공식 코드Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering
https://github.com/academiasinicanlplab/locavqg
공식 코드Location-Aware Visual Question Generation with Lightweight Models
https://github.com/academiasinicanlplab/mvqg-dataset-of-generating-engaging-questions-for-multiple-images
공식 코드Multi-VQG: Generating Engaging Questions for Multiple Images
https://github.com/alibaba/AliceMind/tree/main/PALM
공식 코드PALM: Pre-training an Autoencoding&Autoregressive Language Model for Context-conditioned Generation
https://github.com/alirezamshi/rquge
공식 코드RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question
https://github.com/allenai/clarifydelphi
공식 코드https://github.com/allenai/tess-diffusion
공식 코드https://github.com/amazon-research/sc2qa-dril
공식 코드https://github.com/antoyang/just-ask
공식 코드Just Ask: Learning to Answer Questions from Millions of Narrated Videos
https://github.com/asahi417/lm-question-generation
공식 코드Generative Language Models for Paragraph-Level Question Generation
https://github.com/ashura5/treeeval
공식 코드TreeEval: Benchmark-Free Evaluation of Large Language Models through Tree Planning
https://github.com/ashwinkalyan/dbs
공식 코드Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models
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