---
title: "Wei-Jen Ko — papers and cards"
description: "Wei-Jen Ko: 2 paper cards in the Research library (2020–2023), with what each paper is about, the ideas Mova took from it, and the co-authors."
canonical: "https://research.elamur.ai/free/en/authors/wei-jen-ko/"
---
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# Wei-Jen Ko

2 paper cards in the Research library · 2020–2023

Wei-Jen Ko wrote 2 of the papers Mova reads, in 2020–2023, most of them on [Discourse analysis](https://md.research.elamur.ai/free/en/topics/discourse-analysis/), [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/); often with [Greg Durrett](https://md.research.elamur.ai/free/en/authors/greg-durrett/), [Junyi Jessy Li](https://md.research.elamur.ai/free/en/authors/junyi-jessy-li/), Cutter Dalton.

[OpenAlex](https://openalex.org/A5112244864) · [**h-index 8**](https://openalex.org/authors/A5112244864) · [440 citations](https://openalex.org/authors/A5112244864) · [18 works](https://openalex.org/works?filter=author.id:A5112244864) — openalex-snapshot, 2026-10-14

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Wei-Jen+Ko) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Wei-Jen+Ko) · [dblp](https://dblp.org/search?q=Wei-Jen+Ko) · [ACL Anthology](https://aclanthology.org/search/?q=Wei-Jen+Ko) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Wei-Jen+Ko)

Topics: [Discourse analysis](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) 1 · [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) 1

## Papers

1. **[Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under Discussion](https://md.research.elamur.ai/free/en/papers/ko-2023-discourse-analysis-questions-answers-parsing/)** *(2023)* The paper builds the first parser for QUD dependency structures: every sentence after the first gets an anchor sentence earlier in the document and a free-form question, raised by the anchor, that the sentence answers.
2. **[Inquisitive Question Generation for High Level Text Comprehension](https://md.research.elamur.ai/free/en/papers/ko-2020-inquisitive-question-generation-high-level/)** *(2020)* INQUISITIVE is a set of about 19K questions that crowd workers asked while reading the first five sentences of 1,500 news articles one sentence at a time, each question tied to the span it is about and checked not to be answered already by the earlier text.

## Co-authors (7)

- [Greg Durrett](https://md.research.elamur.ai/free/en/authors/greg-durrett/) ×2
- [Junyi Jessy Li](https://md.research.elamur.ai/free/en/authors/junyi-jessy-li/) ×2
- Cutter Dalton
- Dananjay Srinivas
- Te-yuan Chen
- [Yating Wu](https://md.research.elamur.ai/free/en/authors/yating-wu/)
- Yiyan Huang

## More papers in the library (1)

Pages of the Research library: our summary, the ideas, references and who cites each.

- [Assessing Discourse Relations in Language Generation from GPT-2](https://md.research.elamur.ai/free/en/papers/ko-2020-assessing-discourse-relations-language-generation/) — Wei-Jen Ko, Junyi Jessy Li · 2020