---
title: "Jinyu Li — author profile and papers — Elamur Research"
description: "Jinyu Li, Microsoft: 5 papers on Elamur Research (2020–2026), h-index 53 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/jinyu-li/"
---
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# Jinyu Li

Jinyu Li has 5 papers in our library, in 2020–2026, 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/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Shujie Liu](https://md.research.elamur.ai/free/en/authors/shujie-liu/), [Long Zhou](https://md.research.elamur.ai/free/en/authors/long-zhou/), [Sanyuan Chen](https://md.research.elamur.ai/free/en/authors/sanyuan-chen/).

5 papers in our library · 2020–2026

[OpenAlex](https://openalex.org/A5100365053) · [ORCID](https://orcid.org/0000-0002-1089-9748) · [Wikidata](https://www.wikidata.org/wiki/Q130800665) · [**h-index 53**](https://openalex.org/authors/A5100365053) · [315 works](https://openalex.org/works?filter=author.id:A5100365053) · [12,903 citations](https://openalex.org/works?filter=author.id:A5100365053&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/jinyu-li/#papers) · [🔗 Cited 326 times in our library](https://md.research.elamur.ai/free/en/authors/jinyu-li/cited-by/) · [3 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #4543](https://md.research.elamur.ai/free/en/paper-stars/page/46/#star-4543)

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

## Affiliations

[🏢**Microsoft** Redmond · United States 2007–2026 · 207 papers*current*](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🔬**Laboratoire de Phonétique et Phonologie** Paris · France 2018–2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/labs/laboratoire-de-phonetique-et-phonologie/) · [🎓**Université Sorbonne Nouvelle** Paris · France 2024–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/universite-sorbonne-nouvelle/) · [🔬**Centre National de la Recherche Scientifique** Paris · France 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/labs/centre-national-de-la-recherche-scientifique/) · [🔬**Savoirs, Textes, Langage** Villeneuve-d'Ascq · France 2026 · 1 paper*current*](https://ror.org/003fs1j49) · [🎓**Université de Lille** Lille · France 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/universite-de-lille/) · [🎓**Georgia Institute of Technology** Atlanta · United States 2006–2009 · 7 papers](https://md.research.elamur.ai/free/en/universities/georgia-institute-of-technology/) · [🏢**Microsoft Research** Cambridge · United Kingdom 2021–2025 · 2 papers](https://md.research.elamur.ai/free/en/companies/microsoft-research-united-kingdom/) · [🎓**Kunming Medical University** Kunming · China 2022 · 2 papers](https://ror.org/038c3w259) · [🏢**IFlyTek** Hefei · China 2004–2005 · 2 papers](https://md.research.elamur.ai/free/en/companies/iflytek/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 9 more institutions on single bylines are not listed.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 10 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/) · [Signal Processing · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/signal-processing/) · [Medicine · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Physiology · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/physiology/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/)

🧭 Topics 4 Research subjects and languages the work is about.[Speech & spoken language · 2 works](https://md.research.elamur.ai/free/en/topics/speech/) · [Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/jinyu-li/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/jinyu-li/year/2025/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/jinyu-li/year/2023/) · [**2020** 1 paper](https://md.research.elamur.ai/free/en/authors/jinyu-li/year/2020/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers](https://md.research.elamur.ai/free/en/papers/wang-2023-neural-codec-language-models-zero/)** *(2023 · 335 citations)* Zero-shot text-to-speech means reproducing a voice the system never saw during training. Earlier approaches relied on speaker adaptation or dedicated speaker encoders. Models trained on small, studio-clean corpora tend to generalize poorly to new speakers.
2. **[Autoregressive Speech Synthesis without Vector Quantization](https://md.research.elamur.ai/free/en/papers/meng-2025-autoregressive-speech-synthesis-without-vector/)** *(2025 · 25 citations)* Codec-based zero-shot TTS systems such as VALL-E represent speech as vector-quantized tokens. These tokens lose fidelity compared with continuous features. Sampling from them can also produce silences or noise loops, and the systems need a two-pass AR+NAR decoder. MELLE removes quantization entirely: a single…
3. **[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…
4. **[Closing the Modality Reasoning Gap for Speech Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-closing-modality-reasoning-gap-speech/)** *(2026 · 2 citations)* Speech LLMs, which pair a speech encoder and adapter with a text LLM, reason noticeably worse on spoken questions than on the same questions in text.
5. **[Sequence-level self-learning with multiple hypotheses](https://md.research.elamur.ai/free/en/papers/kumatani-2021-sequence-level-self-learning-multiple/)** *(2020)* The paper addresses self-training for end-to-end speech recognition when untranscribed audio is the only adaptation material.

## All works

8 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

1. **[Restructuring of deep neural network acoustic models with singular value decomposition ↗](https://doi.org/10.21437/interspeech.2013-552) Interspeech (USB) · no summary yet**Jian Xue, Jinyu Li, Yifan Gong*2013 · 421 citations*
2. [**Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers arXiv:2301.02111**Chengyi Wang, Sanyuan Chen, Yu Wu, et al.*2023 · 335 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-neural-codec-language-models-zero/)
3. **[WavLLM: Towards Robust and Adaptive Speech Large Language Model ↗](https://aclanthology.org/2024.findings-emnlp.263/) Findings of the Association for Computational Linguistics: EMNLP 2024 · no summary yet**Shujie Hu et al.*2024 · 98 citations*
4. **[Autoregressive Speech Synthesis without Vector Quantization](https://md.research.elamur.ai/free/en/papers/meng-2025-autoregressive-speech-synthesis-without-vector/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingwei Meng, Long Zhou, Shujie Liu, et al.*2025 · 25 citations*
5. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wang, Jinghua Zhao, Yifan Yang, et al.*2026 · 3 citations*
6. **[Closing the Modality Reasoning Gap for Speech Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-closing-modality-reasoning-gap-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoren Wang, Heng Lu, Xueyao Zhang, et al.*2026 · 2 citations*
7. **[Sequence-level self-learning with multiple hypotheses](https://md.research.elamur.ai/free/en/papers/kumatani-2021-sequence-level-self-learning-multiple/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, et al.*2020*
8. **[Production de la parole en réponse à de multiples perturbations du feedback auditif (Speech production in response to multiple perturbations of auditory feedback) ↗](https://aclanthology.org/2020.jeptalnrecital-jep.42/) Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 1 : Journées d'Études sur la Parole · no summary yet**Jinyu Li, Leonardo Lancia*2020*

## Co-authors here

12 of 24 co-authors with a page, the most papers together first.

- [Shujie Liu](https://md.research.elamur.ai/free/en/authors/shujie-liu/) ×4
- [Long Zhou](https://md.research.elamur.ai/free/en/authors/long-zhou/) ×2
- [Sanyuan Chen](https://md.research.elamur.ai/free/en/authors/sanyuan-chen/) ×2
- [Sheng Zhao](https://md.research.elamur.ai/free/en/authors/sheng-zhao/) ×2
- [Yan Lu](https://md.research.elamur.ai/free/en/authors/yan-lu/) ×2
- [Yanqing Liu](https://md.research.elamur.ai/free/en/authors/yanqing-liu/) ×2
- [Bing Han](https://md.research.elamur.ai/free/en/authors/bing-han/)
- [Chengyi Wang](https://md.research.elamur.ai/free/en/authors/chengyi-wang/)
- [Dimitrios Dimitriadis](https://md.research.elamur.ai/free/en/authors/dimitrios-dimitriadis/)
- [Furu Wei](https://md.research.elamur.ai/free/en/authors/furu-wei/)
- [Haoqin Sun](https://md.research.elamur.ai/free/en/authors/haoqin-sun/)
- [Helen Meng](https://md.research.elamur.ai/free/en/authors/helen-meng/)

## 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/) ×4: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/)
- [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/) ×2: [Interspeech 2020](https://md.research.elamur.ai/free/en/venues/interspeech-usb/2020/)
- Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 1 : Journées d'Études sur la Parole
- Findings of the Association for Computational Linguistics: EMNLP 2024

## Cited by

Papers of our library cite their works 326 times (of the 149,439 papers whose bibliographies we read); [69 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/jinyu-li/cited-by/).

Updated 1 November 2026