---
title: "Liqun Chen — author profile and papers · Sentiment & emotion"
description: "Liqun Chen, Harbin Institute of Technology: 2 papers on Elamur Research (2021–2026), h-index 0 — affiliations, topics, co-authors and who…"
canonical: "https://research.elamur.ai/free/en/authors/liqun-chen/"
---
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# Liqun Chen

Liqun Chen has 2 papers in our library, in 2021–2026, most of them on [Sentiment & emotion](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/); often with [Bill Dolan](https://md.research.elamur.ai/free/en/authors/bill-dolan/), [Chris Brockett](https://md.research.elamur.ai/free/en/authors/chris-brockett/), [Dong She](https://md.research.elamur.ai/free/en/authors/dong-she/).

2 papers in our library · 2021–2026

[OpenAlex](https://openalex.org/A5133184227) · [**h-index 0**](https://openalex.org/authors/A5133184227) · [7 works](https://openalex.org/works?filter=author.id:A5133184227) · [0 citations](https://openalex.org/works?filter=author.id:A5133184227&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/liqun-chen/#papers) · [🔗 Cited 105 times in our library](https://md.research.elamur.ai/free/en/authors/liqun-chen/cited-by/) · [⭐ Paper Stars ranking: #5080](https://md.research.elamur.ai/free/en/paper-stars/page/51/#star-5080)

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

## Affiliations

[🎓**Harbin Institute of Technology** Harbin · China *current*](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/)

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 7 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/) · [Language and Linguistics · 1 work](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/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/)

🧭 Topics 1 Research subjects and languages the work is about.[Sentiment & emotion · 1 work](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/)

## Works by year

### 2020s

[**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/liqun-chen/year/2026/) · [**2021** 1 paper](https://md.research.elamur.ai/free/en/authors/liqun-chen/year/2021/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Contextualized Perturbation for Textual Adversarial Attack](https://md.research.elamur.ai/free/en/papers/li-2021-contextualized-perturbation-textual-adversarial-attack/)** *(2021 · 283 citations)* Adversarial attacks on NLP classifiers should fool the model while still reading naturally. Most earlier methods swap words using context-blind rules such as synonym lists, which often produces awkward or ungrammatical text. The authors propose CLARE, a black-box attack that masks part of the input and lets a…
2. **[AICA-Bench: Holistically Examining the Capabilities of VLMs in Affective Image Content Analysis](https://md.research.elamur.ai/free/en/papers/she-2026-aica-bench-holistically-examining-capabilities/)** *(2026)* Existing emotion benchmarks for vision-language models mostly check whether a model can choose the right emotion label for an image. AICA-Bench tests a broader skill set across three tasks:

## Co-authors here

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

- [Bill Dolan](https://md.research.elamur.ai/free/en/authors/bill-dolan/)
- [Chris Brockett](https://md.research.elamur.ai/free/en/authors/chris-brockett/)
- [Dong She](https://md.research.elamur.ai/free/en/authors/dong-she/)
- [Hao Peng](https://md.research.elamur.ai/free/en/authors/hao-peng/)
- [Xianrong Yao](https://md.research.elamur.ai/free/en/authors/xianrong-yao/)
- [Yang Gao](https://md.research.elamur.ai/free/en/authors/yang-gao/)
- [Yizhe Zhang](https://md.research.elamur.ai/free/en/authors/yizhe-zhang/)
- [Zhanpeng Jin](https://md.research.elamur.ai/free/en/authors/zhanpeng-jin/)

## 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/)
- [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/): [NAACL 2021](https://md.research.elamur.ai/free/en/venues/naacl/2021/)

## Cited by

Papers of our library cite their works 105 times (of the 149,439 papers whose bibliographies we read); [12 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/liqun-chen/cited-by/).

Updated 1 November 2026
