Papers with Automatic question generation
Learning to Generate Question by Asking Question: A Primal-Dual Approach with Uncommon Word Generation (2022.emnlp-main)
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| Challenge: | Existing automatic question generation methods focus on encoding passage and answer to generate question. |
| Approach: | They propose an automatic question generation approach which integrates question generation with its dual problem, question answering, into a unified primal-dual framework. |
| Outcome: | The proposed approach outperforms existing methods on SQuAD and HotpotQA benchmarks. |
Cross-lingual Transfer for Automatic Question Generation by Learning Interrogative Structures in Target Languages (2024.emnlp-main)
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| Challenge: | Existing automatic question generation datasets focus on English, resulting in data gaps for other languages. |
| Approach: | They propose a cross-lingual transfer method that allows models to generate questions in low-resource languages. |
| Outcome: | The proposed method outperforms other models and achieves comparable performance across languages. |
Evaluation of Question Answer Generation for Portuguese: Insights and Datasets (2024.findings-emnlp)
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| Challenge: | Automatic question generation is an increasingly important task that can be applied in educational settings, data augmentation for question-answering (QA), and conversational systems. |
| Approach: | They adapt and apply QAG approaches to generate question-answer pairs given context and look into strategies for error filtering and their effects. |
| Outcome: | The proposed methods can generate question-answer pairs in Portuguese, a widely spoken language that is underrepresented in natural language processing research. |
Cross-Lingual Training for Automatic Question Generation (P19-1)
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| Challenge: | Automatic question generation is a challenging problem in natural language understanding . manual curating a dataset of comparable size for a new language is tedious and expensive. |
| Approach: | They propose to reuse available large QG dataset in a secondary language to learn a QG model for a primary language. |
| Outcome: | The proposed model outperforms baseline models in Hindi and Chinese. |
On the Importance of Diversity in Question Generation for QA (2020.acl-main)
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| Challenge: | In this paper, we show that textual diversity in automatic question generation is beneficial for downstream QA. |
| Approach: | They propose to use textual diversity to promote automatic question generation as a quality measure for QA. |
| Outcome: | The proposed measure of QG quality correlates well with evaluation on QA. |
MCQG-SRefine: Multiple Choice Question Generation and Evaluation with Iterative Self-Critique, Correction, and Comparison Feedback (2025.naacl-long)
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| Challenge: | Generating multiple-choice questions (MCQG) for professional exams is challenging due to outdated knowledge, hallucination issues, and prompt sensitivity. |
| Approach: | They propose a framework for converting medical cases into high-quality USMLE-style questions using a self-refine-based framework. |
| Outcome: | The proposed framework improves human expert satisfaction regarding quality and difficulty of medical questions. |