---
title: "Stanley Jungkyu Choi — author profile and papers · Reasoning"
description: "Stanley Jungkyu Choi, LG AI Research: 2 papers on Elamur Research (2026), h-index 4 — affiliations, topics, co-authors and who cites them…"
canonical: "https://research.elamur.ai/free/en/authors/stanley-jungkyu-choi/"
---
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# Stanley Jungkyu Choi

Stanley Jungkyu Choi has 2 papers in our library, in 2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Code & programming languages](https://md.research.elamur.ai/free/en/topics/code-and-programming/), [Semantic parsing & meaning representation](https://md.research.elamur.ai/free/en/topics/semantic-parsing/); often with [Dilek Hakkani-Tür](https://md.research.elamur.ai/free/en/authors/dilek-hakkani-tur/), [Minjun Park](https://md.research.elamur.ai/free/en/authors/minjun-park/), [Takyoung Kim](https://md.research.elamur.ai/free/en/authors/takyoung-kim/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5021052817) · [ORCID](https://orcid.org/0009-0001-0297-4269) · [**h-index 4**](https://openalex.org/authors/A5021052817) · [32 works](https://openalex.org/works?filter=author.id:A5021052817) · [72 citations](https://openalex.org/works?filter=author.id:A5021052817&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/stanley-jungkyu-choi/#papers) · [⭐ Paper Stars ranking: #12229](https://md.research.elamur.ai/free/en/paper-stars/page/123/#star-12229)

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=Stanley+Jungkyu+Choi) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Stanley+Jungkyu+Choi) · [dblp](https://dblp.org/search?q=Stanley+Jungkyu+Choi) · [ACL Anthology](https://aclanthology.org/search/?q=Stanley+Jungkyu+Choi)

## Affiliations

[🏢**LG AI Research** Seoul · South Korea 2021–2026 · 16 papers*current*](https://md.research.elamur.ai/free/en/companies/lg-ai-research/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Networks and Communications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-networks-and-communications/) · [General Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/general-social-sciences/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/)

🧭 Topics 3 Research subjects and languages the work is about.[Code & programming languages · 1 work](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Semantic parsing & meaning representation · 1 work](https://md.research.elamur.ai/free/en/topics/semantic-parsing/)

💡 Concepts 1 Key ideas and methods explained on our concept pages.[Topic modeling · 1 work](https://md.research.elamur.ai/free/en/concepts/topic-modeling/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/stanley-jungkyu-choi/year/2026/)

## Papers

The most cited first (OpenAlex and our library).

1. **[From Documents to Segments: A Contextual Reformulation for Topic Assignment](https://md.research.elamur.ai/free/en/papers/yoon-2026-documents-segments-contextual-reformulation-topic/)** *(2026)* Standard topic models treat a whole document as the unit that receives topics. Many real texts, such as reviews or survey answers, mix several themes in a few sentences. This causes "topic contamination": a retrieved topic drags in unrelated content.
2. **[ReSQL: Self-Improving Framework for Reasoning-Aware Text-to-SQL Dataset Generation](https://md.research.elamur.ai/free/en/papers/park-2026-resql-self-improving-framework-reasoning/)** *(2026)* Small and mid-sized LLMs often produce SQL that fails to execute, and they are poor at repairing their own mistakes.

## Co-authors here

3 co-authors with a page, the most papers together first.

- [Dilek Hakkani-Tür](https://md.research.elamur.ai/free/en/authors/dilek-hakkani-tur/)
- [Minjun Park](https://md.research.elamur.ai/free/en/authors/minjun-park/)
- [Takyoung Kim](https://md.research.elamur.ai/free/en/authors/takyoung-kim/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×2

Updated 1 November 2026
