---
title: "WonJune Jang · Myongji University — author profile and papers"
description: "WonJune Jang, Myongji University: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them in…"
canonical: "https://research.elamur.ai/free/en/authors/wonjune-jang/"
---
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# WonJune Jang

WonJune Jang has 2 papers in our library, in 2026, most of them on [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Interpretability](https://md.research.elamur.ai/free/en/topics/interpretability/); often with [Jaewoo Kang](https://md.research.elamur.ai/free/en/authors/jaewoo-kang/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5153480532) · [**h-index 0**](https://openalex.org/authors/A5153480532) · [6 works](https://openalex.org/works?filter=author.id:A5153480532) · [0 citations](https://openalex.org/works?filter=author.id:A5153480532&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/wonjune-jang/#papers) · [⭐ Paper Stars ranking: #12280](https://md.research.elamur.ai/free/en/paper-stars/page/123/#star-12280)

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

## Affiliations

[🎓**Myongji University** Seoul · South Korea 2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/universities/myongji-university/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

## Fields, topics and concepts

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

📚 Shelves 10 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Materials Chemistry · 1 work](https://md.research.elamur.ai/free/en/shelves/materials-science/materials-chemistry/) · [Materials Science · 1 work](https://md.research.elamur.ai/free/en/shelves/materials-science/) · [Small Animals · 1 work](https://md.research.elamur.ai/free/en/shelves/veterinary/small-animals/) · [Veterinary · 1 work](https://md.research.elamur.ai/free/en/shelves/veterinary/)

🧭 Topics 4 Research subjects and languages the work is about.[Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Interpretability · 1 work](https://md.research.elamur.ai/free/en/topics/interpretability/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/)

## Works by year

### 2020s

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

## Papers

The most cited first (OpenAlex and our library).

1. **[CLAG: Adaptive Memory Organization via Agent-Driven Clustering for Small Language Model Agents](https://md.research.elamur.ai/free/en/papers/roh-2026-clag-adaptive-memory-organization-agent/)** *(2026)* Memory-augmented agents usually keep every stored experience in one flat retrieval pool. As that pool grows, retrieval surfaces more plausible but off-topic entries, and memory-updating ("evolution") steps operate on mixed-topic neighbourhoods that can gradually corrupt the store. Small language models (SLMs, under…
2. **[ToxReason: A Benchmark for Mechanistic Chemical Toxicity Reasoning via Adverse Outcome Pathway](https://md.research.elamur.ai/free/en/papers/park-2026-toxreason-benchmark-mechanistic-chemical-toxicity/)** *(2026)* ToxReason is a benchmark that tests whether LLMs can explain chemical toxicity through biologically plausible causal mechanisms, not only predict whether a compound is toxic.

## Co-authors here

1 co-author with a page, the most papers together first.

- [Jaewoo Kang](https://md.research.elamur.ai/free/en/authors/jaewoo-kang/) ×2

## 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
