---
title: "Yujia Li — author profile and papers — Elamur Research"
description: "Yujia Li: 2 papers on Elamur Research (2022–2023), h-index 33 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/yujia-li/"
---
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# Yujia Li

Yujia Li has 2 papers in our library, in 2022–2023, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Code & programming languages](https://md.research.elamur.ai/free/en/topics/code-and-programming/); often with [Denny Zhou](https://md.research.elamur.ai/free/en/authors/denny-zhou/), [Ed H. Chi](https://md.research.elamur.ai/free/en/authors/ed-h-chi/), [Felix Gimeno](https://md.research.elamur.ai/free/en/authors/felix-gimeno/).

2 papers in our library · 2022–2023

[OpenAlex](https://openalex.org/A5100680672) · [ORCID](https://orcid.org/0000-0002-1024-9243) · [**h-index 33**](https://openalex.org/authors/A5100680672) · [155 works](https://openalex.org/works?filter=author.id:A5100680672) · [8,998 citations](https://openalex.org/works?filter=author.id:A5100680672&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yujia-li/#papers) · [🔗 Cited 4,197 times in our library](https://md.research.elamur.ai/free/en/authors/yujia-li/cited-by/) · [19 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #1890](https://md.research.elamur.ai/free/en/paper-stars/page/19/#star-1890)

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

## Affiliations

[🎓**University of Pittsburgh** Pittsburgh · United States 2019–2025 · 13 papers](https://md.research.elamur.ai/free/en/universities/university-of-pittsburgh/) · [🎓**University of Toronto** Toronto · Canada 2013–2017 · 12 papers](https://md.research.elamur.ai/free/en/universities/university-of-toronto/) · [🏢**Google DeepMind** London · United Kingdom 2018–2023 · 10 papers](https://md.research.elamur.ai/free/en/companies/google-deepmind/) · [🎓**Fudan University** Shanghai · China 2010–2025 · 9 papers](https://md.research.elamur.ai/free/en/universities/fudan-university/) · [🔬**China Electric Power Research Institute** Beijing 2017–2025 · 6 papers](https://ror.org/05ehpzy81) · [🏛️**Chinese Academy of Sciences** Beijing · China 2019–2025 · 6 papers](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🎓**Heidelberg University** Heidelberg · Germany 2021–2025 · 6 papers](https://md.research.elamur.ai/free/en/universities/heidelberg-university/) · [🎓**Medizinische Fakultät Mannheim** Mannheim 2021–2025 · 6 papers](https://ror.org/02m1z0a87) · [🤝**University Medical Centre Mannheim** Mannheim · Germany 2023–2025 · 5 papers](https://ror.org/05sxbyd35) · [🏢**Eli Lilly** Indianapolis · United States 2023–2024 · 5 papers](https://ror.org/01qat3289)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 43 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 7 The field of science this work belongs to (OpenAlex fields).[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/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Science Applications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-science-applications/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/)

🧭 Topics 3 Research subjects and languages the work is about.[Code & programming languages · 1 work](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/)

## Works by year

### 2020s

[**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/yujia-li/year/2023/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/authors/yujia-li/year/2022/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Competition-Level Code Generation with AlphaCode](https://md.research.elamur.ai/free/en/papers/li-2022-competition-level-code-generation-alphacode/)** *(2022 · 1,564 citations)* AlphaCode addresses the task of writing complete programs for competitive programming problems. In this setting a long natural-language statement must become a correct and fast solution, which is then judged on hidden tests. Earlier large code models handled short, instruction-like tasks but solved only a few percent…
2. **[Large Language Models as Analogical Reasoners](https://md.research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/)** *(2023 · 74 citations)* Chain-of-thought prompting helps LLMs solve multi-step problems, but both common forms have drawbacks. The zero-shot variant gives only generic guidance, and the few-shot variant needs hand-written reasoning demonstrations for every task. Yasunaga et al. (Google DeepMind and Stanford) propose analogical prompting. It…

## All works

21 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. **[Competition-Level Code Generation with AlphaCode](https://md.research.elamur.ai/free/en/papers/li-2022-competition-level-code-generation-alphacode/) [Science](https://md.research.elamur.ai/free/en/venues/science/)**Yujia Li, David Choi, Junyoung Chung, et al.*2022 · 1,564 citations*
2. **[Scaling Language Models: Methods, Analysis & Insights from Training Gopher ↗](https://arxiv.org/abs/2112.11446) arXiv:2112.11446 · no summary yet**Jack W. Rae et al.*2021 · 928 citations*
3. **[Understanding the Effective Receptive Field in Deep Convolutional Neural Networks ↗](https://arxiv.org/abs/1701.04128) arXiv (Cornell University) · no summary yet**Wenjie Luo et al.*2017 · 771 citations*
4. **[Gated Graph Sequence Neural Networks ↗](https://arxiv.org/abs/1511.05493) arXiv:1511.05493 · no summary yet**Yujia Li et al.*2015 · 576 citations*
5. **[Generative Moment Matching Networks ↗](https://arxiv.org/abs/1502.02761) arXiv (Cornell University) · no summary yet**Yujia Li, Kevin Swersky, Rich Zemel*2015 · 560 citations*
6. **[Learning Deep Generative Models of Graphs ↗](https://arxiv.org/abs/1803.03324) arXiv (Cornell University) · no summary yet**Yujia Li et al.*2018 · 422 citations*
7. **[Graph Matching Networks for Learning the Similarity of Graph Structured Objects ↗](https://arxiv.org/abs/1904.12787) arXiv (Cornell University) · no summary yet**Yujia Li et al.*2019 · 298 citations*
8. **[Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer ↗](https://doi.org/10.1609/aaai.v34i01.5400) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Edward Choi et al.*2020 · 256 citations*
9. **[Imagination-Augmented Agents for Deep Reinforcement Learning ↗](https://arxiv.org/abs/1707.06203) arXiv (Cornell University) · no summary yet**Théophane Weber et al.*2017 · 241 citations*
10. **[Efficient Graph Generation with Graph Recurrent Attention Networks ↗](https://arxiv.org/abs/1910.00760) arXiv (Cornell University) · no summary yet**Renjie Liao et al.*2019 · 170 citations*
11. **[Relational Deep Reinforcement Learning ↗](https://arxiv.org/abs/1806.01830) arXiv (Cornell University) · no summary yet**Vinícius Zambaldi et al.*2018 · 160 citations*
12. **[Learning model-based planning from scratch ↗](https://arxiv.org/abs/1707.06170) arXiv (Cornell University) · no summary yet**Razvan Pascanu et al.*2017 · 76 citations*
13. [**Large Language Models as Analogical Reasoners arXiv:2310.01714**Michihiro Yasunaga, Xinyun Chen, Yujia Li, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/)
14. **[Solving Mixed Integer Programs Using Neural Networks ↗](https://arxiv.org/abs/2012.13349) arXiv:2012.13349 · no summary yet**Vinod Nair et al.*2020 · 52 citations*
15. **[Exploring Compositional High Order Pattern Potentials for Structured Output Learning ↗](https://doi.org/10.1109/cvpr.2013.14) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Yujia Li, Daniel Tarlow, Richard S. Zemel*2013 · 33 citations*
16. **[Mean-Field Networks ↗](https://arxiv.org/abs/1410.5884) arXiv (Cornell University) · no summary yet**Yujia Li, Richard S. Zemel*2014 · 23 citations*
17. **[WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset ↗](https://aclanthology.org/2021.textgraphs-1.7/) Proceedings of the Fifteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-15) · no summary yet**Luyu Wang et al.*2021 · 22 citations*
18. **[Strong Generalization and Efficiency in Neural Programs ↗](https://arxiv.org/abs/2007.03629) arXiv (Cornell University) · no summary yet**Yujia Li et al.*2020 · 22 citations*
19. **[Learning unbiased features ↗](https://arxiv.org/abs/1412.5244) arXiv (Cornell University) · no summary yet**Yujia Li, Kevin Swersky, Richard S. Zemel*2014 · 20 citations*
20. **[High Order Regularization for Semi-Supervised Learning of Structured Output Problems ↗](https://openalex.org/W2140045824) no summary yet**Yujia Li, Rich Zemel*2014 · 18 citations*
21. **[Dualing GANs ↗](https://arxiv.org/abs/1706.06216) arXiv (Cornell University) · no summary yet**Yujia Li et al.*2017 · 1 citation*

## Co-authors here

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

- [Denny Zhou](https://md.research.elamur.ai/free/en/authors/denny-zhou/)
- [Ed H. Chi](https://md.research.elamur.ai/free/en/authors/ed-h-chi/)
- [Felix Gimeno](https://md.research.elamur.ai/free/en/authors/felix-gimeno/)
- [Julian Schrittwieser](https://md.research.elamur.ai/free/en/authors/julian-schrittwieser/)
- [Junyoung Chung](https://md.research.elamur.ai/free/en/authors/junyoung-chung/)
- [Jure Leskovec](https://md.research.elamur.ai/free/en/authors/jure-leskovec/)
- [Michihiro Yasunaga](https://md.research.elamur.ai/free/en/authors/michihiro-yasunaga/)
- [Nate Kushman](https://md.research.elamur.ai/free/en/authors/nate-kushman/)
- [Panupong Pasupat](https://md.research.elamur.ai/free/en/authors/panupong-pasupat/)
- [Percy Liang](https://md.research.elamur.ai/free/en/authors/percy-liang/)
- [Xinyun Chen](https://md.research.elamur.ai/free/en/authors/xinyun-chen/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Science](https://md.research.elamur.ai/free/en/venues/science/): [Science 2022](https://md.research.elamur.ai/free/en/venues/science/2022/)
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
- Proceedings of the AAAI Conference on Artificial Intelligence
- Proceedings of the Fifteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-15)

## Cited by

Papers of our library cite their works 4,197 times (of the 149,439 papers whose bibliographies we read); [974 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yujia-li/cited-by/).

Updated 2 November 2026