---
title: "Yuhang Jia · Nankai University — author profile and papers"
description: "Yuhang Jia, Nankai University: 2 papers on Elamur Research (2026), h-index 1 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/yuhang-jia/"
---
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# Yuhang Jia

Yuhang Jia has 2 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/), [Speech & spoken language](https://md.research.elamur.ai/free/en/topics/speech/); often with [Jiaming Zhou](https://md.research.elamur.ai/free/en/authors/jiaming-zhou/), [Yong Qin](https://md.research.elamur.ai/free/en/authors/yong-qin/), [Aobo Kong](https://md.research.elamur.ai/free/en/authors/aobo-kong/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5129826497) · [**h-index 1**](https://openalex.org/authors/A5129826497) · [3 works](https://openalex.org/works?filter=author.id:A5129826497) · [1 citations](https://openalex.org/works?filter=author.id:A5129826497&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yuhang-jia/#papers) · [⭐ Paper Stars ranking: #14087](https://md.research.elamur.ai/free/en/paper-stars/page/141/#star-14087)

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

## Affiliations

[🎓**Nankai University** Tianjin · China 2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/universities/nankai-university/) · [🏢**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).[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/) · [Signal Processing · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/signal-processing/)

🧭 Topics 4 Research subjects and languages the work is about.[Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Speech & spoken language · 1 work](https://md.research.elamur.ai/free/en/topics/speech/)

## Works by year

### 2020s

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

## Papers

The most cited first (OpenAlex and our library).

1. **[DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffa-2-practical-diffusion-large/)** *(2026)* Large audio language models are mostly autoregressive. They need a lot of data and compute to scale, and their token-by-token decoding slows inference. The earlier DIFFA work showed that a diffusion LLM backbone can help audio understanding, but only at a small, proof-of-concept scale. DIFFA-2 develops this into a…
2. **[RealTalk-CN: A Realistic Chinese Speech Task-Oriented Dialogue Benchmark with Cross-Modal Analysis](https://md.research.elamur.ai/free/en/papers/wang-2026-realtalk-cn-realistic-chinese-speech/)** *(2026)* Speech LLMs such as GPT-4o can now handle spoken interaction end to end. However, it is unclear how well they help users finish concrete tasks when speech is spontaneous, spans many turns, varies across speakers, or alternates with typed input. Existing task-oriented dialogue (TOD) benchmarks are mostly text-only…

## Co-authors here

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

- [Jiaming Zhou](https://md.research.elamur.ai/free/en/authors/jiaming-zhou/) ×2
- [Yong Qin](https://md.research.elamur.ai/free/en/authors/yong-qin/) ×2
- [Aobo Kong](https://md.research.elamur.ai/free/en/authors/aobo-kong/)
- [Cao Liu](https://md.research.elamur.ai/free/en/authors/cao-liu/)
- [Enzhi Wang](https://md.research.elamur.ai/free/en/authors/enzhi-wang/)
- [Ke Zeng](https://md.research.elamur.ai/free/en/authors/ke-zeng/)
- [Qicheng Li](https://md.research.elamur.ai/free/en/authors/qicheng-li/)
- [Shiwan Zhao](https://md.research.elamur.ai/free/en/authors/shiwan-zhao/)
- [Xunliang Cai](https://md.research.elamur.ai/free/en/authors/xunliang-cai/)
- [Xuxin Cheng](https://md.research.elamur.ai/free/en/authors/xuxin-cheng/)

## 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/)
- [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/)

Updated 2 November 2026
