---
title: "Jun Kuang — author profile and papers — Elamur Research"
description: "Jun Kuang, Meituan: 2 papers on Elamur Research (2023–2026), h-index 0 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/jun-kuang/"
---
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# Jun Kuang

Jun Kuang has 2 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/); often with [Peng Ding](https://md.research.elamur.ai/free/en/authors/peng-ding/), [Xuezhi Cao](https://md.research.elamur.ai/free/en/authors/xuezhi-cao/), [Jiajun Chen](https://md.research.elamur.ai/free/en/authors/jiajun-chen/).

2 papers in our library · 2023–2026

[OpenAlex](https://openalex.org/A5139793332) · [**h-index 0**](https://openalex.org/authors/A5139793332) · [2 works](https://openalex.org/works?filter=author.id:A5139793332) · [0 citations](https://openalex.org/works?filter=author.id:A5139793332&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/jun-kuang/#papers) · [🔗 Cited 80 times in our library](https://md.research.elamur.ai/free/en/authors/jun-kuang/cited-by/) · [⭐ Paper Stars ranking: #8213](https://md.research.elamur.ai/free/en/paper-stars/page/83/#star-8213)

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

## Affiliations

[🏢**Meituan** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/meituan/)

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 5 The field of science this work belongs to (OpenAlex fields).[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/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/)

🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [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/)

## Works by year

### 2020s

[**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/jun-kuang/year/2026/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/jun-kuang/year/2023/)

## Papers

The most cited first (OpenAlex and our library).

1. **[A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily](https://md.research.elamur.ai/free/en/papers/ding-2023-wolf-sheep-s-clothing-generalized/)** *(2023 · 85 citations)* Safety-aligned LLMs can still be manipulated into giving harmful answers through jailbreak prompts. Existing attacks either depend on laborious hand-written templates (e.g., DAN) or on slow gradient search over white-box models (e.g., GCG). GCG produces nonsensical suffixes that are easy to filter and work poorly on…
2. **[Meeseeks: A Feedback-Driven, Iterative Self-Correction Benchmark evaluating LLMs' Instruction Following Capability](https://md.research.elamur.ai/free/en/papers/wang-2026-meeseeks-feedback-driven-iterative-self/)** *(2026 · 1 citation)* Large language models often fail to satisfy every requirement in prompts that contain many constraints. Meeseeks is a benchmark that measures how far models can improve when they get repeated, targeted feedback. It works in cycles. The tested model answers a prompt, and each constraint is checked automatically. The…

## Co-authors here

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

- [Peng Ding](https://md.research.elamur.ai/free/en/authors/peng-ding/) ×2
- [Xuezhi Cao](https://md.research.elamur.ai/free/en/authors/xuezhi-cao/) ×2
- [Jiajun Chen](https://md.research.elamur.ai/free/en/authors/jiajun-chen/)
- [Jiaming Wang](https://md.research.elamur.ai/free/en/authors/jiaming-wang/)
- [Shujian Huang](https://md.research.elamur.ai/free/en/authors/shujian-huang/)
- [Xiaoyu Li](https://md.research.elamur.ai/free/en/authors/xiaoyu-li/)
- [Yilin Jin](https://md.research.elamur.ai/free/en/authors/yilin-jin/)
- [Zhe Tang](https://md.research.elamur.ai/free/en/authors/zhe-tang/)
- [ZongYu Wang](https://md.research.elamur.ai/free/en/authors/zongyu-wang/)

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

## Cited by

Papers of our library cite their works 80 times (of the 149,439 papers whose bibliographies we read); [25 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/jun-kuang/cited-by/).

Updated 2 November 2026
