mlsanityData to 7 Oct 2026

FOLLOWUPQG: Towards Information-Seeking Follow-up Question Generation

arXiv 2309.05007 ↗First posted 10 Sep 2023cs.CL cs.AIcited by 12

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Abstract (arXiv)

Humans ask follow-up questions driven by curiosity, which reflects a creative human cognitive process. We introduce the task of real-world information-seeking follow-up question generation (FQG), which aims to generate follow-up questions seeking a more in-depth understanding of an initial question and answer. We construct FOLLOWUPQG, a dataset of over 3K real-world (initial question, answer, follow-up question) tuples collected from a Reddit forum providing layman-friendly explanations for open-ended questions. In contrast to existing datasets, questions in FOLLOWUPQG use more diverse pragmatic strategies to seek information, and they also show higher-order cognitive skills (such as applying and relating). We evaluate current question generation models on their efficacy for generating follow-up questions, exploring how to generate specific types of follow-up questions based on step-by-step demonstrations. Our results validate FOLLOWUPQG as a challenging benchmark, as model-generated questions are adequate but far from human-raised questions in terms of informativeness and complexity.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 28 of its 55 references that are in the map. First posted on arXiv 10 Sep 2023.

Builds on

28 of 55 references.

References · 28

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16 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 7; 2026: 2.

12 papers.

  1. 2023BooookScore: A systematic exploration of book-length summarization in the era of LLMscited by 137
  2. 2024InfoLossQA: Characterizing and Recovering Information Loss in Text Simplificationcited by 14
  3. 2025Conversational User-AI Intervention: A Study on Prompt Rewriting for Improved LLM Response Generationcited by 10
  4. 2025Follow-up Question Generation For Enhanced Patient-Provider Conversationscited by 9
  5. 2024Which questions should I answer? Salience Prediction of Inquisitive Questionscited by 8
  6. 2025CHIMERA: A Knowledge Base of Scientific Idea Recombinations for Research Analysis and Ideationcited by 6
  7. 2026InfoGatherer: Principled Information Seeking via Evidence Retrieval and Strategic Questioningcited by 3
  8. 2025Bridging Information Gaps with Comprehensive Answers: Improving the Diversity and Informativeness of Follow-Up Questionscited by 2
  9. 2025From Superficial to Deep: Integrating External Knowledge for Follow-up Question Generation Using Knowledge Graph and LLMcited by 2
  10. 2025From Answers to Guidance: A Proactive Dialogue System for Legal Documentscited by 1
  11. 2025SnappyMeal: Design and Longitudinal Evaluation of a Multimodal AI Food Logging Applicationcited by 0
  12. 2026DiscoTrace: Representing and Comparing Answering Strategies of Humans and LLMs in Information-Seeking Question Answeringcited by 0