---
title: "Yuqi Tang — author profile and papers — Elamur Research"
description: "Yuqi Tang, The Hong Kong University of Science and Technology (Guangzhou): 2 papers on Elamur Research (2024–2026), h-index 0…"
canonical: "https://research.elamur.ai/free/en/authors/yuqi-tang/"
---
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# Yuqi Tang

Yuqi Tang has 2 papers in our library, in 2024–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Kehua Feng](https://md.research.elamur.ai/free/en/authors/kehua-feng/), [Qiang Zhang](https://md.research.elamur.ai/free/en/authors/qiang-zhang/), [Shuliang Liu](https://md.research.elamur.ai/free/en/authors/shuliang-liu/).

2 papers in our library · 2024–2026

[OpenAlex](https://openalex.org/A5139787483) · [**h-index 0**](https://openalex.org/authors/A5139787483) · [1 works](https://openalex.org/works?filter=author.id:A5139787483) · [0 citations](https://openalex.org/works?filter=author.id:A5139787483&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yuqi-tang/#papers) · [🔗 Cited 33 times in our library](https://md.research.elamur.ai/free/en/authors/yuqi-tang/cited-by/) · [⭐ Paper Stars ranking: #8218](https://md.research.elamur.ai/free/en/paper-stars/page/83/#star-8218)

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

## Affiliations

[🎓**The Hong Kong University of Science and Technology (Guangzhou)** Guangzhou · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/the-hong-kong-university-of-science-and-technology-guangzhou/)

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/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/)

## Works by year

### 2020s

[**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/yuqi-tang/year/2026/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/yuqi-tang/year/2024/)

## Papers

The most cited first (OpenAlex and our library).

1. **[SciKnowEval: Evaluating Multi-level Scientific Knowledge of Large Language Models](https://md.research.elamur.ai/free/en/papers/feng-2024-sciknoweval-evaluating-multi-level-scientific/)** *(2024 · 36 citations)* SciKnowEval is a benchmark for measuring how much scientific knowledge large language models hold and how well they use it.
2. **[Vision-Language Introspection: Mitigating Overconfident Hallucinations in MLLMs via Interpretable Bi-Causal Steering](https://md.research.elamur.ai/free/en/papers/liu-2026-vision-language-introspection-mitigating-overconfident/)** *(2026 · 1 citation)* Multimodal LLMs often describe objects that are not in the image. The authors trace this to models trusting language-based expectations over what the image actually shows. They propose Vision-Language Introspection (VLI), a training-free method applied at inference time.

## Co-authors here

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

- [Kehua Feng](https://md.research.elamur.ai/free/en/authors/kehua-feng/)
- [Qiang Zhang](https://md.research.elamur.ai/free/en/authors/qiang-zhang/)
- [Shuliang Liu](https://md.research.elamur.ai/free/en/authors/shuliang-liu/)
- [Weijie Wang](https://md.research.elamur.ai/free/en/authors/weijie-wang/)
- [Xin Zou](https://md.research.elamur.ai/free/en/authors/xin-zou/)
- [Xuming Hu](https://md.research.elamur.ai/free/en/authors/xuming-hu/)
- [Yibo Yan](https://md.research.elamur.ai/free/en/authors/yibo-yan/)

## Venues

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

- [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)

## Cited by

Papers of our library cite their works 33 times (of the 149,439 papers whose bibliographies we read); [7 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yuqi-tang/cited-by/).

Updated 31 October 2026
