---
title: "Mark I-Cheng Chen — author profile and papers in our library"
description: "Mark I-Cheng Chen, Tan Tock Seng Hospital: 6 papers on Elamur Research (2020–2022), h-index 58 — affiliations, topics, co-authors and…"
canonical: "https://research.elamur.ai/free/en/authors/mark-i-cheng-chen/"
---
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# Mark I-Cheng Chen

Mark I-Cheng Chen has 6 papers in our library, in 2020–2022, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Heewoo Jun](https://md.research.elamur.ai/free/en/authors/heewoo-jun/), [Jerry Tworek](https://md.research.elamur.ai/free/en/authors/jerry-tworek/), [Aditya Ramesh](https://md.research.elamur.ai/free/en/authors/aditya-ramesh/).

6 papers in our library · 2020–2022

[OpenAlex](https://openalex.org/A5030935953) · [ORCID](https://orcid.org/0000-0001-9369-5830) · [Wikidata](https://www.wikidata.org/wiki/Q56037108) · [**h-index 58**](https://openalex.org/authors/A5030935953) · [324 works](https://openalex.org/works?filter=author.id:A5030935953) · [34,608 citations](https://openalex.org/works?filter=author.id:A5030935953&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/mark-i-cheng-chen/#papers) · [🔗 Cited 20,687 times in our library](https://md.research.elamur.ai/free/en/authors/mark-i-cheng-chen/cited-by/) · [20 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #274](https://md.research.elamur.ai/free/en/paper-stars/page/3/#star-274)

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=Mark+I-Cheng+Chen) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Mark+I-Cheng+Chen) · [dblp](https://dblp.org/search?q=Mark+I-Cheng+Chen) · [ACL Anthology](https://aclanthology.org/search/?q=Mark+I-Cheng+Chen)

## Affiliations

[🏥**Tan Tock Seng Hospital** Singapore · Singapore 2001–2026 · 89 papers*current*](https://ror.org/032d59j24) · [🎓**Columbia University** New York · United States 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/columbia-university/) · [🎓**National University of Singapore** Singapore · Singapore 2003–2024 · 105 papers](https://md.research.elamur.ai/free/en/universities/national-university-of-singapore/) · [🏥**National Centre for Infectious Diseases** Singapore · Singapore 2001–2025 · 103 papers](https://ror.org/03rtrce80) · [🎓**National University Health System** Singapore · Singapore 2013–2023 · 36 papers](https://ror.org/05tjjsh18) · [🎓**Duke-NUS Medical School** Singapore · Singapore 2009–2022 · 15 papers](https://ror.org/02j1m6098) · [🔬**Sandia National Laboratories** Albuquerque · United States 2020–2025 · 14 papers](https://md.research.elamur.ai/free/en/labs/sandia-national-laboratories/) · [🏛️**Ministry of Health** Singapore · Singapore 2019–2023 · 9 papers](https://ror.org/00mrhvv69) · [🎓**University of Washington** Seattle · United States 2005–2011 · 9 papers](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🏢**Taiwan Semiconductor Manufacturing Company** Hsinchu · Taiwan 2016–2020 · 8 papers](https://ror.org/02wx79d08)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 33 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).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Computer Vision and Pattern Recognition · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [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/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Applied Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/applied-mathematics/) · [Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/)

🧭 Topics 4 Research subjects and languages the work is about.[Vision & language · 2 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/)

💡 Concepts 3 Key ideas and methods explained on our concept pages.[Language model · 1 work](https://md.research.elamur.ai/free/en/concepts/language-model/) · [Large language models · 1 work](https://md.research.elamur.ai/free/en/concepts/large-language-models/) · [Scaling laws · 1 work](https://md.research.elamur.ai/free/en/concepts/scaling-laws/)

## Works by year

### 2020s

[**2022** 2 papers](https://md.research.elamur.ai/free/en/authors/mark-i-cheng-chen/year/2022/) · [**2021** 3 papers](https://md.research.elamur.ai/free/en/authors/mark-i-cheng-chen/year/2021/) · [**2020** 1 paper](https://md.research.elamur.ai/free/en/authors/mark-i-cheng-chen/year/2020/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Training Verifiers to Solve Math Word Problems](https://md.research.elamur.ai/free/en/papers/cobbe-2021-training-verifiers-solve-math-word/)** *(2021 · 3,796 citations)* Large language models still make fatal mistakes on reasoning that needs several arithmetic steps. One cause is that a left-to-right generator cannot repair an early slip. The authors address this with a new benchmark and a reranking method. GSM8K holds 8.5K grade-school word problems written by people, split 7.5K for…
2. **[Hierarchical Text-Conditional Image Generation with CLIP Latents](https://md.research.elamur.ai/free/en/papers/ramesh-2022-hierarchical-text-conditional-image-generation/)** *(2022 · 2,713 citations)* The paper addresses text-to-image generation by building on CLIP, a model that maps images and captions into a shared embedding space.
3. **[Evaluating Large Language Models Trained on Code](https://md.research.elamur.ai/free/en/papers/chen-2021-evaluating-large-language-models-trained/)** *(2021 · 2,659 citations)* Code generation models were usually scored by how closely their output text matched a reference, for example with BLEU.
4. **[Zero-Shot Text-to-Image Generation](https://md.research.elamur.ai/free/en/papers/ramesh-2021-zero-shot-text-image-generation/)** *(2021 · 1,528 citations)* Earlier text-to-image systems improved mainly through hand-designed modeling choices tuned to small benchmarks such as MS-COCO and CUB.
5. **[Scaling Laws for Autoregressive Generative Modeling](https://md.research.elamur.ai/free/en/papers/henighan-2020-scaling-laws-autoregressive-generative-modeling/)** *(2020 · 277 citations)* The authors from OpenAI examine whether the scaling laws previously found for language models also hold for other data types.
6. **[Efficient Training of Language Models to Fill in the Middle](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)** *(2022 · 144 citations)* Causal decoder-only language models such as the GPT family generate text strictly left to right. They cannot use context that follows the insertion point, which limits tasks like editing code inside an existing file. The authors (OpenAI) teach such models to fill in the middle (FIM) through data reformatting alone…

## All works

26 works of theirs in our library, the most cited first; 6 with a page here, the others link their original until we summarise them.

1. [**Training Verifiers to Solve Math Word Problems arXiv:2110.14168**Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, et al.*2021 · 3,796 citations*](https://md.research.elamur.ai/free/en/papers/cobbe-2021-training-verifiers-solve-math-word/)
2. [**Hierarchical Text-Conditional Image Generation with CLIP Latents arXiv:2204.06125**Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, et al.*2022 · 2,713 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2022-hierarchical-text-conditional-image-generation/)
3. [**Evaluating Large Language Models Trained on Code arXiv:2107.03374**Mark Chen, Jerry Tworek, Heewoo Jun, et al.*2021 · 2,659 citations*](https://md.research.elamur.ai/free/en/papers/chen-2021-evaluating-large-language-models-trained/)
4. [**Zero-Shot Text-to-Image Generation arXiv:2102.12092**Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, et al.*2021 · 1,528 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2021-zero-shot-text-image-generation/)
5. **[GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗](https://arxiv.org/abs/2112.10741) arXiv (Cornell University) · no summary yet**Alex Nichol et al.*2021 · 1,180 citations*
6. **[Generative Pretraining From Pixels ↗](https://openalex.org/W3034445277) International Conference on Machine Learning · no summary yet**Mark I-Cheng Chen et al.*2020 · 614 citations*
7. [**Scaling Laws for Autoregressive Generative Modeling arXiv:2010.14701**Tom Henighan, Jared Kaplan, Mor Katz, et al.*2020 · 277 citations*](https://md.research.elamur.ai/free/en/papers/henighan-2020-scaling-laws-autoregressive-generative-modeling/)
8. **[Consistency Models ↗](https://arxiv.org/abs/2303.01469) arXiv (Cornell University) · no summary yet**Yang Song et al.*2023 · 235 citations*
9. **[Point-E: A System for Generating 3D Point Clouds from Complex Prompts ↗](https://arxiv.org/abs/2212.08751) arXiv:2212.08751 · no summary yet**Alex Nichol et al.*2022 · 185 citations*
10. [**Efficient Training of Language Models to Fill in the Middle arXiv:2207.14255**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)
11. **[Competitive Programming with Large Reasoning Models ↗](https://arxiv.org/abs/2502.06807) arXiv:2502.06807 · no summary yet**OpenAI: Ahmed El-Kishky et al.*2025 · 68 citations*
12. **[Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety ↗](https://arxiv.org/abs/2507.11473) arXiv (Cornell University) · no summary yet**Tomek Korbak et al.*2025 · 35 citations*
13. **[Distribution Augmentation for Generative Modeling ↗](https://openalex.org/W3114951884) International Conference on Machine Learning · no summary yet**Heewoo Jun et al.*2020 · 30 citations*
14. **[Parsing Line Chart Images Using Linear Programming ↗](https://doi.org/10.1109/wacv51458.2022.00261) IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) · no summary yet**Hajime Kato et al.*2022 · 16 citations*
15. **[Identifying FinTech Innovations Using BERT ↗](https://doi.org/10.1109/bigdata50022.2020.9378169) IEEE International Conference on Big Data (BigData) · no summary yet**Doina Caragea et al.*2020 · 16 citations*
16. **[An Individual-Based Model of Influenza in Nosocomial Environments ↗](https://doi.org/10.1007/978-3-540-69384-0_64) Lecture notes in computer science · no summary yet**Boon Som Ong et al.*2008 · 14 citations*
17. **[When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA ↗](https://arxiv.org/abs/2308.06849) arXiv:2308.06849 · no summary yet**Hongxiang Fan et al.*2023 · 9 citations*
18. **[An extensible micro-world for learning in the data networking professions ↗](https://doi.org/10.1016/j.ins.2013.10.024) Information Sciences · no summary yet**Dennis C. Frezzo et al.*2013 · 5 citations*
19. **[Protocol failures related to order of encryption and signature computation of discrete logarithms in RSA groups ↗](https://doi.org/10.1007/bfb0053737) Lecture notes in computer science · no summary yet**Mark I-Cheng Chen, Eric Hughes*1998 · 4 citations*
20. **[Microfluidic Platforms for Nanoparticle Delivery and Nanomanufacturing in Biology and Medicine ↗](https://doi.org/10.1007/978-1-4419-0531-4_10) Springer eBooks · no summary yet**Owen Y. Loh et al.*2009 · 1 citation*
21. **[Game Review ↗](https://doi.org/10.2304/elea.2008.5.3.358) E-Learning and Digital Media · no summary yet**Mark I-Cheng Chen*2008 · 1 citation*
22. **[CityOS: Privacy Architecture for Urban Sensing ↗](https://arxiv.org/abs/2605.02886) arXiv (Cornell University) · no summary yet**Giorgio Cavicchioli et al.*2026*
23. **[Big Bird: Resilient Privacy Budgeting Across Untrusted Web Domains ↗](https://doi.org/10.1145/3830418.3843897) ACM SIGOPS Symposium on Operating Systems Principles (SOSP) · no summary yet**Pierre Tholoniat et al.*2026*
24. **[Conditional Augmentation for Generative Modeling ↗](https://openalex.org/W3035610106) International Conference on Machine Learning · no summary yet**Heewoo Jun et al.*2020*
25. **[How a New Actor Was Temporarily Enrolled Into the Network of Game Playing. ↗](https://openalex.org/W3157453428) Computer Supported Collaborative Learning · no summary yet**Mark I-Cheng Chen*2011*

[See all 26 works by Mark I-Cheng Chen →](https://md.research.elamur.ai/free/en/authors/mark-i-cheng-chen/works/)

## Co-authors here

12 of 29 co-authors with a page, the most papers together first.

- [Heewoo Jun](https://md.research.elamur.ai/free/en/authors/heewoo-jun/) ×4
- [Jerry Tworek](https://md.research.elamur.ai/free/en/authors/jerry-tworek/) ×3
- [Aditya Ramesh](https://md.research.elamur.ai/free/en/authors/aditya-ramesh/) ×2
- [Christopher Hesse](https://md.research.elamur.ai/free/en/authors/christopher-hesse/) ×2
- [Jared Kaplan](https://md.research.elamur.ai/free/en/authors/jared-kaplan/) ×2
- [John Schulman](https://md.research.elamur.ai/free/en/authors/john-schulman/) ×2
- [Mohammad Bavarian](https://md.research.elamur.ai/free/en/authors/mohammad-bavarian/) ×2
- [Prafulla Dhariwal](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/) ×2
- [Scott Gray](https://md.research.elamur.ai/free/en/authors/scott-gray/) ×2
- [Alec Radford](https://md.research.elamur.ai/free/en/authors/alec-radford/)
- [Alex Ray](https://md.research.elamur.ai/free/en/authors/alex-ray/)
- [Benjamin Mann](https://md.research.elamur.ai/free/en/authors/benjamin-mann/)

## Venues

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

- International Conference on Machine Learning ×3
- Lecture notes in computer science ×2
- ACM SIGOPS Symposium on Operating Systems Principles (SOSP)
- Australasian Conference on Information Security and Privacy
- Computer Supported Collaborative Learning
- E-Learning and Digital Media
- IEEE International Conference on Big Data (BigData)
- IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
- Information Sciences
- Springer eBooks

## Cited by

Papers of our library cite their works 20,687 times (of the 149,439 papers whose bibliographies we read); [2,701 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/mark-i-cheng-chen/cited-by/).

Updated 30 October 2026