mlsanityData to 14 Oct 2026

Elaborative Simplification as Implicit Questions Under Discussion

arXiv 2305.10387 ↗First posted 17 May 2023cs.CLcited by 14

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Abstract (arXiv)

Automated text simplification, a technique useful for making text more accessible to people such as children and emergent bilinguals, is often thought of as a monolingual translation task from complex sentences to simplified sentences using encoder-decoder models. This view fails to account for elaborative simplification, where new information is added into the simplified text. This paper proposes to view elaborative simplification through the lens of the Question Under Discussion (QUD) framework, providing a robust way to investigate what writers elaborate upon, how they elaborate, and how elaborations fit into the discourse context by viewing elaborations as explicit answers to implicit questions. We introduce ElabQUD, consisting of 1.3K elaborations accompanied with implicit QUDs, to study these phenomena. We show that explicitly modeling QUD (via question generation) not only provides essential understanding of elaborative simplification and how the elaborations connect with the rest of the discourse, but also substantially improves the quality of elaboration generation.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 13 of its 47 references that are in the map. First posted on arXiv 17 May 2023.

Builds on

13 of 47 references.

References · 13

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  3. 2019EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editingcited by 63
  4. 2021Paragraph-level Simplification of Medical Textscited by 53
  5. 2022Conditional Generation with a Question-Answering Blueprintcited by 44
  6. 2021Controllable Open-ended Question Generation with A New Question Type Ontologycited by 36
  7. 2020Inquisitive Question Generation for High Level Text Comprehensioncited by 32
  8. 2020Elaborative Simplification: Content Addition and Explanation Generation in Text Simplificationcited by 27
  9. 2021Document-Level Text Simplification: Dataset, Criteria and Baselinecited by 27
  10. 2022An Imitation Learning Curriculum for Text Editing with Non-Autoregressive Modelscited by 20
  11. 2021Discourse Comprehension: A Question Answering Framework to Represent Sentence Connectionscited by 19
  12. 2022Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under Discussioncited by 13
1 more
  1. 2022Text Simplification of College Admissions Instructions: A Professionally Simplified and Verified Corpuscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 4; 2024: 2; 2025: 5; 2026: 3.

14 papers.

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