--- title: "Yong Qin · Nankai University — author profile and papers" description: "Yong Qin, Nankai University: 5 papers on Elamur Research (2023–2026), h-index 1 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/yong-qin/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yong-qin/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yong Qin # Yong Qin Yong Qin has 5 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Speech & spoken language](https://md.research.elamur.ai/free/en/topics/speech/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/); often with [Jiaming Zhou](https://md.research.elamur.ai/free/en/authors/jiaming-zhou/), [Shiwan Zhao](https://md.research.elamur.ai/free/en/authors/shiwan-zhao/), [Aobo Kong](https://md.research.elamur.ai/free/en/authors/aobo-kong/). 5 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5139723216) · [ORCID](https://orcid.org/0009-0000-2748-3020) · [**h-index 1**](https://openalex.org/authors/A5139723216) · [10 works](https://openalex.org/works?filter=author.id:A5139723216) · [6 citations](https://openalex.org/works?filter=author.id:A5139723216&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/yong-qin/#papers) · [🔗 Cited 90 times in our library](https://md.research.elamur.ai/free/en/authors/yong-qin/cited-by/) · [⭐ Paper Stars ranking: #7675](https://md.research.elamur.ai/free/en/paper-stars/page/77/#star-7675) 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=Yong+Qin) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yong+Qin) · [dblp](https://dblp.org/search?q=Yong+Qin) · [ACL Anthology](https://aclanthology.org/search/?q=Yong+Qin) ## Affiliations [🎓**Nankai University** Tianjin · China 2021–2026 · 10 papersEmployment since 2021 · Professor, College of Computer Sciences*current*](https://md.research.elamur.ai/free/en/universities/nankai-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 6 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 5 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/) · [Signal Processing · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/signal-processing/) 🧭 Topics 5 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Speech & spoken language · 2 works](https://md.research.elamur.ai/free/en/topics/speech/) · [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/) 💡 Concepts 1 Key ideas and methods explained on our concept pages.[Child-directed speech · 1 work](https://md.research.elamur.ai/free/en/concepts/child-directed-speech/) ## Works by year ### 2020s [**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/yong-qin/year/2026/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/yong-qin/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Better Zero-Shot Reasoning with Role-Play Prompting](https://md.research.elamur.ai/free/en/papers/kong-2023-better-zero-shot-reasoning-role/)** *(2023 · 110 citations)* Conversational LLMs are good at adopting personas, but it was unclear whether this helps them reason. The authors test whether assigning a task-appropriate role, such as a math teacher, improves zero-shot reasoning. Their method has two stages. First, a hand-written role-setting prompt is sent to the model, and its… 2. **[SpeechLLM-as-Judges: Towards General and Interpretable Speech Quality Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2026-speechllm-as-judges-general-interpretable/)** *(2026 · 3 citations)* Judging how good synthetic speech sounds is still difficult. Common tools such as MOS ratings, A/B tests, or MCD produce a single number or a binary choice, which explains nothing about the judgment. Learned predictors such as UTMOS are usually limited to one task and one language. The authors propose… 3. **[ChildTalk: A Multi-Dialect Chinese Child Speech Corpus with Full-Length Child–Caregiver Conversations for Speech Recognition](https://md.research.elamur.ai/free/en/papers/zhou-2026-childtalk-multi-dialect-chinese-child/)** *(2026)* Recognizing children's speech is hard for ASR systems. Child voices differ acoustically from the adult data most models are trained on, and Mandarin child corpora are scarce. Existing ones are often closed, built from read speech, cut into isolated utterances, or limited to standard Mandarin. The authors address this… 4. **[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… 5. **[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 12 of 21 co-authors with a page, the most papers together first. - [Jiaming Zhou](https://md.research.elamur.ai/free/en/authors/jiaming-zhou/) ×4 - [Shiwan Zhao](https://md.research.elamur.ai/free/en/authors/shiwan-zhao/) ×4 - [Aobo Kong](https://md.research.elamur.ai/free/en/authors/aobo-kong/) ×2 - [Enzhi Wang](https://md.research.elamur.ai/free/en/authors/enzhi-wang/) ×2 - [Haoqin Sun](https://md.research.elamur.ai/free/en/authors/haoqin-sun/) ×2 - [Hui Wang](https://md.research.elamur.ai/free/en/authors/hui-wang/) ×2 - [Qicheng Li](https://md.research.elamur.ai/free/en/authors/qicheng-li/) ×2 - [Yuhang Jia](https://md.research.elamur.ai/free/en/authors/yuhang-jia/) ×2 - [Cao Liu](https://md.research.elamur.ai/free/en/authors/cao-liu/) - [Hao Chen](https://md.research.elamur.ai/free/en/authors/hao-chen/) - [Jinghua Zhao](https://md.research.elamur.ai/free/en/authors/jinghua-zhao/) - [Jinyu Li](https://md.research.elamur.ai/free/en/authors/jinyu-li/) ## 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/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2 - [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 ## Cited by Papers of our library cite their works 90 times (of the 149,439 papers whose bibliographies we read); [18 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yong-qin/cited-by/). Updated 2 November 2026