---
title: "Chun-Liang Li — author profile and papers — Elamur Research"
description: "Chun-Liang Li, Google: 3 papers on Elamur Research (2023–2024), h-index 46 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/chun-liang-li/"
---
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# Chun-Liang Li

Chun-Liang Li has 3 papers in our library, in 2023–2024, 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/); often with [Chen-Yu Lee](https://md.research.elamur.ai/free/en/authors/chen-yu-lee/), [Tomas Pfister](https://md.research.elamur.ai/free/en/authors/tomas-pfister/), [Yasuhisa Fujii](https://md.research.elamur.ai/free/en/authors/yasuhisa-fujii/).

3 papers in our library · 2023–2024

[OpenAlex](https://openalex.org/A5102972645) · [ORCID](https://orcid.org/0000-0002-5938-5510) · [Wikidata](https://www.wikidata.org/wiki/Q91451445) · [**h-index 46**](https://openalex.org/authors/A5102972645) · [335 works](https://openalex.org/works?filter=author.id:A5102972645) · [10,215 citations](https://openalex.org/works?filter=author.id:A5102972645&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/chun-liang-li/#papers) · [🔗 Cited 722 times in our library](https://md.research.elamur.ai/free/en/authors/chun-liang-li/cited-by/) · [10 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #3113](https://md.research.elamur.ai/free/en/paper-stars/page/32/#star-3113)

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

## Affiliations

[🏥**St. Jude Children's Research Hospital** Memphis · United States 2012–2026 · 85 papersEmployment 2014–2017 · Instructor/Research Associate, Tumor Cell BiologyEmployment 2017–2023 · Assistant Member, Tumor Cell BiologyEmployment since 2023 · Associate Member, Tumor Cell Biology*current*](https://ror.org/02r3e0967) · [🏢**Google** Mountain View · United States 2020–2026 · 29 papers*current*](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**University of Kentucky** Lexington · United States 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-kentucky/) · [🎓**Pennsylvania State University** State College · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/pennsylvania-state-university/) · [🎓**University of California, Santa Cruz** Santa Cruz · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/university-of-california-santa-cruz/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 2015–2021 · 28 papers](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🎓**Shanghai Jiao Tong University** Shanghai · China 2008–2023 · 16 papers](https://md.research.elamur.ai/free/en/universities/shanghai-jiao-tong-university/) · [🏛️**Chinese Academy of Sciences** Beijing · China 2004–2016 · 14 papers](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🔬**Shanghai Institutes for Biological Sciences** Shanghai · China 2008–2016 · 13 papers](https://ror.org/011rf9d86) · [🎓**National Taiwan University** Taipei · Taiwan 2011–2015 · 11 papers](https://md.research.elamur.ai/free/en/universities/national-taiwan-university/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 28 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 6 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [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.[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/)

## Works by year

### 2020s

[**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/chun-liang-li/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/chun-liang-li/year/2023/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/)** *(2023 · 690 citations)* Small task-specific models are cheap to serve, but they usually need many human labels (finetuning) or large pools of unlabeled data (distillation from an LLM) to approach LLM quality.
2. **[Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding](https://md.research.elamur.ai/free/en/papers/wang-2024-chain-table-evolving-tables-reasoning/)** *(2024 · 105 citations)* Large language models can answer questions about tables and check claims against them. However, common reasoning methods record intermediate steps either as plain text (Chain-of-Thought) or as one generated program such as SQL. Both approaches struggle with messy tables, for example when a single cell combines a name…
3. **[Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum](https://md.research.elamur.ai/free/en/papers/pouransari-2024-dataset-decomposition-faster-llm-training/)** *(2024 · 16 citations)* Standard LLM pretraining uses concat-and-chunk: documents are shuffled, joined, and cut into fixed-length sequences.

## All works

13 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. **[FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence ↗](https://arxiv.org/abs/2001.07685) arXiv (Cornell University) · no summary yet**Kihyuk Sohn et al.*2020 · 2,292 citations*
2. **[Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.*2023 · 690 citations*
3. [**Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding arXiv:2401.04398**Zilong Wang, Hao Zhang, Chun-Liang Li, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-chain-table-evolving-tables-reasoning/)
4. **[Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models ↗](https://arxiv.org/abs/2308.00675) arXiv (Cornell University) · no summary yet**Cheng-Yu Hsieh et al.*2023 · 71 citations*
5. **[Activation of γ-globin expression by hypoxia-inducible factor 1α ↗](https://doi.org/10.1038/s41586-022-05312-w) Nature · no summary yet**Ruopeng Feng et al.*2022 · 69 citations*
6. **[Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization ↗](https://aclanthology.org/2024.findings-acl.890/) Findings of the Association for Computational Linguistics: ACL 2024 · no summary yet**Cheng-Yu Hsieh et al.*2024 · 61 citations*
7. **[Point Cloud GAN ↗](https://arxiv.org/abs/1810.05795) arXiv (Cornell University) · no summary yet**Chunliang Li et al.*2018 · 22 citations*
8. **[Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum](https://md.research.elamur.ai/free/en/papers/pouransari-2024-dataset-decomposition-faster-llm-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, et al.*2024 · 16 citations*
9. **[The Delta Learning Hypothesis: Preference Tuning on Weak Data can Yield Strong Gains ↗](https://arxiv.org/abs/2507.06187) arXiv (Cornell University) · no summary yet**Scott Geng et al.*2025 · 10 citations*
10. **[The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better ↗](https://doi.org/10.52202/079017-0254) neural information processing systems · no summary yet**Scott Geng et al.*2024 · 9 citations*
11. **[Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systems ↗](https://arxiv.org/abs/2605.23109) arXiv (Cornell University) · no summary yet**Shubham Agarwal et al.*2026 · 1 citation*
12. **[Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions ↗](https://arxiv.org/abs/2407.06723) arXiv (Cornell University) · no summary yet**Yu-Guan Hsieh et al.*2024 · 1 citation*
13. **[FocalLens: Instruction Tuning Enables Zero-Shot Conditional Image Representations ↗](https://arxiv.org/abs/2504.08368) arXiv (Cornell University) · no summary yet**Cheng-Yu Hsieh et al.*2025*

## Co-authors here

12 of 16 co-authors with a page, the most papers together first.

- [Chen-Yu Lee](https://md.research.elamur.ai/free/en/authors/chen-yu-lee/) ×2
- [Tomas Pfister](https://md.research.elamur.ai/free/en/authors/tomas-pfister/) ×2
- [Yasuhisa Fujii](https://md.research.elamur.ai/free/en/authors/yasuhisa-fujii/) ×2
- [Alexander Ratner](https://md.research.elamur.ai/free/en/authors/alexander-ratner/)
- [Cheng-Yu Hsieh](https://md.research.elamur.ai/free/en/authors/cheng-yu-hsieh/)
- [Hao Zhang](https://md.research.elamur.ai/free/en/authors/hao-zhang/)
- [Hootan Nakhost](https://md.research.elamur.ai/free/en/authors/hootan-nakhost/)
- [Jingbo Shang](https://md.research.elamur.ai/free/en/authors/jingbo-shang/)
- [Julian Eisenschlos](https://md.research.elamur.ai/free/en/authors/julian-eisenschlos/)
- [Lesly Miculicich](https://md.research.elamur.ai/free/en/authors/lesly-miculicich/)
- [Oncel Tuzel](https://md.research.elamur.ai/free/en/authors/oncel-tuzel/)
- [Ranjay Krishna](https://md.research.elamur.ai/free/en/authors/ranjay-krishna/)

## Venues

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

- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2023](https://md.research.elamur.ai/free/en/venues/findings/2023/)
- [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/): [NeurIPS 2024](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2024/)
- Findings of the Association for Computational Linguistics: ACL 2024
- Nature
- neural information processing systems

## Cited by

Papers of our library cite their works 722 times (of the 149,439 papers whose bibliographies we read); [146 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/chun-liang-li/cited-by/).

Updated 2 November 2026