---
title: "Dingyu Yao — author profile and papers — Elamur Research"
description: "Dingyu Yao, Chinese Academy of Sciences: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites…"
canonical: "https://research.elamur.ai/free/en/authors/dingyu-yao/"
---
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# Dingyu Yao

Dingyu Yao has 2 papers in our library, in 2026, most of them on [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Chenxu Yang](https://md.research.elamur.ai/free/en/authors/chenxu-yang/), [Weiping Wang](https://md.research.elamur.ai/free/en/authors/weiping-wang/), [Zheng Lin](https://md.research.elamur.ai/free/en/authors/zheng-lin/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5013346368) · [**h-index 0**](https://openalex.org/authors/A5013346368) · [13 works](https://openalex.org/works?filter=author.id:A5013346368) · [0 citations](https://openalex.org/works?filter=author.id:A5013346368&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/dingyu-yao/#papers) · [🔗 Cited 37 times in our library](https://md.research.elamur.ai/free/en/authors/dingyu-yao/cited-by/) · [⭐ Paper Stars ranking: #10159](https://md.research.elamur.ai/free/en/paper-stars/page/102/#star-10159)

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

## Affiliations

[🔬**Institute of Information Engineering** Beijing · China 2026 · 8 papers*current*](https://md.research.elamur.ai/free/en/labs/institute-of-information-engineering/) · [🏛️**Chinese Academy of Sciences** Beijing · China 2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🎓**University of Chinese Academy of Sciences** Beijing · China 2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/) · [🎓**Cyber University** Fukuoka · Japan 2026 · 2 papers*current*](https://ror.org/038sdcw17) · [🎓**Aerospace Information Research Institute** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/aerospace-information-research-institute/)

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/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/)

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

## Works by year

### 2020s

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

## Papers

The most cited first (OpenAlex and our library).

1. **[Self-Distilled RLVR](https://md.research.elamur.ai/free/en/papers/yang-2026-self-distilled-rlvr/)** *(2026 · 37 citations)* Training reasoning LLMs with RLVR (for example, GRPO) assigns one sequence-level reward per rollout, so every token receives the same credit.
2. **[VecInfer: Efficient LLM Inference with Low-Bit KV Cache via Outlier-Suppressed Vector Quantization](https://md.research.elamur.ai/free/en/papers/yao-2026-vecinfer-efficient-llm-inference-low/)** *(2026)* During LLM inference, the KV cache grows with context length and takes up a large share of GPU memory. Vector quantization (VQ) can shrink it flexibly across bit-widths, but at very low bit-widths accuracy drops sharply. The authors trace this to outliers in the key cache, which sit far from the learned centroids and…

## Co-authors here

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

- [Chenxu Yang](https://md.research.elamur.ai/free/en/authors/chenxu-yang/) ×2
- [Weiping Wang](https://md.research.elamur.ai/free/en/authors/weiping-wang/) ×2
- [Zheng Lin](https://md.research.elamur.ai/free/en/authors/zheng-lin/) ×2
- [Jian Luan](https://md.research.elamur.ai/free/en/authors/jian-luan/)
- [Jiaqi Wang](https://md.research.elamur.ai/free/en/authors/jiaqi-wang/)
- [Minghui Chen](https://md.research.elamur.ai/free/en/authors/minghui-chen/)
- [Naibin Gu](https://md.research.elamur.ai/free/en/authors/naibin-gu/)
- [Nan Duan](https://md.research.elamur.ai/free/en/authors/nan-duan/)
- [Qingyi Si](https://md.research.elamur.ai/free/en/authors/qingyi-si/)
- [Wei Liu](https://md.research.elamur.ai/free/en/authors/wei-liu/)

## 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 37 times (of the 149,439 papers whose bibliographies we read); [6 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/dingyu-yao/cited-by/).

Updated 3 November 2026
