Data to 7 Oct 2026

End-to-End Synthetic Data Generation for Domain Adaptation of Question Answering Systems

arXiv 2010.06028 ↗First posted 12 Oct 2020cs.CLcited by 65

Not on the map. Why?

Abstract (arXiv)

We propose an end-to-end approach for synthetic QA data generation. Our model comprises a single transformer-based encoder-decoder network that is trained end-to-end to generate both answers and questions. In a nutshell, we feed a passage to the encoder and ask the decoder to generate a question and an answer token-by-token. The likelihood produced in the generation process is used as a filtering score, which avoids the need for a separate filtering model. Our generator is trained by fine-tuning a pretrained LM using maximum likelihood estimation. The experimental results indicate significant improvements in the domain adaptation of QA models outperforming current state-of-the-art methods.

Key facts. Cited by 65 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Oct 2020.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 14; 2022: 23; 2023: 15; 2024: 5; 2025: 8.

65 papers.

Sort:

By area:

2021Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Surveycited by 457
2022Promptagator: Few-shot Dense Retrieval From 8 Examplescited by 233
2022Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answeringcited by 126
2021Improving Factual Consistency of Abstractive Summarization via Question Answeringcited by 55
2023FactKB: Generalizable Factuality Evaluation using Language Models Enhanced with Factual Knowledgecited by 55
2022RHO (ρ): Reducing Hallucination in Open-domain Dialogues with Knowledge Groundingcited by 47
2022StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvementcited by 37
2021Zero-shot Generalization in Dialog State Tracking through Generative Question Answeringcited by 33
2021ArchivalQA: A Large-scale Benchmark Dataset for Open Domain Question Answering over Historical News Collectionscited by 30
2022Generative Language Models for Paragraph-Level Question Generationcited by 28
2022QAmeleon: Multilingual QA with Only 5 Examplescited by 25
2021It is AI's Turn to Ask Humans a Question: Question-Answer Pair Generation for Children's Story Bookscited by 23

38 more

2021Improving Unsupervised Question Answering via Summarization-Informed Question Generationcited by 21
2021Contrastive Domain Adaptation for Question Answering using Limited Text Corporacited by 20
2021MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Groundingcited by 19
2023LIQUID: A Framework for List Question Answering Dataset Generationcited by 19
2023An Empirical Comparison of LM-based Question and Answer Generation Methodscited by 15
2025AdaptiVocab: Enhancing LLM Efficiency in Focused Domains through Lightweight Vocabulary Adaptationcited by 15
2022Low-Resource Dense Retrieval for Open-Domain Question Answering: A Comprehensive Surveycited by 14
2022Synthetic Question Value Estimation for Domain Adaptation of Question Answeringcited by 12
2023Diversify Question Generation with Retrieval-Augmented Style Transfercited by 10
2021Towards Robust Neural Retrieval Models with Synthetic Pre-Trainingcited by 9
2022ED2LM: Encoder-Decoder to Language Model for Faster Document Re-ranking Inferencecited by 9
2023Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challengescited by 9
2024Prompting-based Synthetic Data Generation for Few-Shot Question Answeringcited by 9
2023GSQA: An End-to-End Model for Generative Spoken Question Answeringcited by 8
2024Synthetic Multimodal Question Generationcited by 8
2024A Survey of Data Synthesis Approachescited by 8
2021Topic Transferable Table Question Answeringcited by 7
2022The Dialog Must Go On: Improving Visual Dialog via Generative Self-Trainingcited by 7
2022Domain Adaptation for Question Answering via Question Classificationcited by 7
2023Test-Time Self-Adaptive Small Language Models for Question Answeringcited by 7
2021Self-Teaching Machines to Read and Comprehend with Large-Scale Multi-Subject Question-Answering Datacited by 6
2022Optimization Techniques for Unsupervised Complex Table Reasoning via Self-Training Frameworkcited by 6
2023Neural Architecture Search for Effective Teacher-Student Knowledge Transfer in Language Modelscited by 6
2023Modeling What-to-ask and How-to-ask for Answer-unaware Conversational Question Generationcited by 6
2021Cooperative Self-training of Machine Reading Comprehensioncited by 5
2022When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentationcited by 5
2022Entity-Conditioned Question Generation for Robust Attention Distribution in Neural Information Retrievalcited by 5
2022Combining Data Generation and Active Learning for Low-Resource Question Answeringcited by 5
2022To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answeringcited by 5
2023Towards Diverse and Effective Question-Answer Pair Generation from Children Storybookscited by 5
2023Generative Data Augmentation using LLMs improves Distributional Robustness in Question Answeringcited by 5
2023Self-Specialization: Uncovering Latent Expertise within Large Language Modelscited by 5
2022Understanding Domain Learning in Language Models Through Subpopulation Analysiscited by 4
2022IDK-MRC: Unanswerable Questions for Indonesian Machine Reading Comprehensioncited by 4
2025QuArch: A Question-Answering Dataset for AI Agents in Computer Architecturecited by 4
2022REKnow: Enhanced Knowledge for Joint Entity and Relation Extractioncited by 3
2025A Scoping Review of Synthetic Data Generation by Language Models in Biomedical Research and Application: Data Utility and Quality Perspectivescited by 3
2021Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation Learningcited by 2

50 most cited of 65 All 65 (JSON)