---
title: "Zhaoye Fei · Fudan University — author profile and papers"
description: "Zhaoye Fei, Fudan University: 5 papers on Elamur Research (2024–2026), h-index 3 — affiliations, topics, co-authors and who cites them in…"
canonical: "https://research.elamur.ai/free/en/authors/zhaoye-fei/"
---
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# Zhaoye Fei

Zhaoye Fei has 5 papers in our library, in 2024–2026, most of them on [Speech & spoken language](https://md.research.elamur.ai/free/en/topics/speech/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Xipeng Qiu](https://md.research.elamur.ai/free/en/authors/xipeng-qiu/), [Qinyuan Cheng](https://md.research.elamur.ai/free/en/authors/qinyuan-cheng/), [Dong Zhang](https://md.research.elamur.ai/free/en/authors/dong-zhang/).

5 papers in our library · 2024–2026

[OpenAlex](https://openalex.org/A5052255999) · [**h-index 3**](https://openalex.org/authors/A5052255999) · [39 works](https://openalex.org/works?filter=author.id:A5052255999) · [62 citations](https://openalex.org/works?filter=author.id:A5052255999&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/zhaoye-fei/#papers) · [🔗 Cited 383 times in our library](https://md.research.elamur.ai/free/en/authors/zhaoye-fei/cited-by/) · [⭐ Paper Stars ranking: #7607](https://md.research.elamur.ai/free/en/paper-stars/page/77/#star-7607)

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

## Affiliations

[🎓**Fudan University** Shanghai · China 2022–2026 · 14 papers*current*](https://md.research.elamur.ai/free/en/universities/fudan-university/) · [🔬**Shanghai Artificial Intelligence Laboratory** Shanghai · China 2024 · 4 papers](https://md.research.elamur.ai/free/en/labs/shanghai-artificial-intelligence-laboratory/) · [🏢**Huawei Technologies** Shenzhen · China 2022 · 2 papers](https://md.research.elamur.ai/free/en/companies/huawei-technologies/)

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 10 The field of science this work belongs to (OpenAlex fields).[Computer Science · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [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/) · [Signal Processing · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/signal-processing/)

🧭 Topics 6 Research subjects and languages the work is about.[Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [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/) · [Speech & spoken language · 2 works](https://md.research.elamur.ai/free/en/topics/speech/) · [Tokenization & segmentation · 1 work](https://md.research.elamur.ai/free/en/topics/tokenization/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/zhaoye-fei/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/zhaoye-fei/year/2025/) · [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/zhaoye-fei/year/2024/)

## Papers

The most cited first (OpenAlex and our library).

1. **[InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning](https://md.research.elamur.ai/free/en/papers/ying-2024-internlm-math-open-math-large/)** *(2024 · 90 citations)* InternLM-Math is a family of open math-specialised LLMs from Shanghai AI Laboratory and partner universities.
2. **[VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search](https://md.research.elamur.ai/free/en/papers/wang-2025-visuothink-empowering-lvlm-reasoning-multimodal/)** *(2025 · 13 citations)* Large vision-language models (LVLMs) still struggle with geometry problems and spatial navigation. People handle such tasks by sketching, checking intermediate pictures and trying alternative routes. Earlier multimodal "slow thinking" methods either reason purely in text over a fixed input image or add visual help…
3. **[Unearthing Large Scale Domain-Specific Knowledge from Public Corpora](https://md.research.elamur.ai/free/en/papers/fei-2024-unearthing-large-scale-domain-specific/)** *(2024 · 10 citations)* Building domain-specific corpora for LLMs usually requires experts to pick sources and engineers to scrape them.
4. **[XY-Tokenizer: Mitigating the Semantic-Acoustic Conflict in Low-Bitrate Speech Codecs](https://md.research.elamur.ai/free/en/papers/gong-2026-xy-tokenizer-mitigating-semantic-acoustic/)** *(2026 · 4 citations)* Speech LLMs need discrete tokens that carry both linguistic content and acoustic detail. At low bitrates, codecs typically trade one for the other. This paper introduces XY-Tokenizer, a codec of roughly 1 kbps designed to reduce that tension.
5. **[WESR: A Benchmark and Strong Baseline for Word-level Event-Speech Recognition](https://md.research.elamur.ai/free/en/papers/yang-2026-wesr-benchmark-strong-baseline-word/)** *(2026)* Most speech recognition systems discard non-verbal vocalizations such as laughter, coughing or whispering.

## Co-authors here

12 of 26 co-authors with a page, the most papers together first.

- [Xipeng Qiu](https://md.research.elamur.ai/free/en/authors/xipeng-qiu/) ×4
- [Qinyuan Cheng](https://md.research.elamur.ai/free/en/authors/qinyuan-cheng/) ×3
- [Dong Zhang](https://md.research.elamur.ai/free/en/authors/dong-zhang/) ×2
- [Linyang Li](https://md.research.elamur.ai/free/en/authors/linyang-li/) ×2
- [Qipeng Guo](https://md.research.elamur.ai/free/en/authors/qipeng-guo/) ×2
- [Shimin Li](https://md.research.elamur.ai/free/en/authors/shimin-li/) ×2
- [Yunfan Shao](https://md.research.elamur.ai/free/en/authors/yunfan-shao/) ×2
- [Conghui He](https://md.research.elamur.ai/free/en/authors/conghui-he/)
- [Dacheng Tao](https://md.research.elamur.ai/free/en/authors/dacheng-tao/)
- [Dahua Lin](https://md.research.elamur.ai/free/en/authors/dahua-lin/)
- [Hang Yan](https://md.research.elamur.ai/free/en/authors/hang-yan/)
- [Huaiyuan Ying](https://md.research.elamur.ai/free/en/authors/huaiyuan-ying/)

## 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/), [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/)
- [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/)

## Cited by

Papers of our library cite their works 383 times (of the 149,439 papers whose bibliographies we read); [120 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/zhaoye-fei/cited-by/).

Updated 2 November 2026
