M Chen Google Scholar: h-index, Total Citations, and Citation Map
M Chen's h-index is 38 (52 i10-index, 180,897+ total citations across 62+ publications) according to Google Scholar as of October 2026. M Chen is affiliated with OpenAI.
M Chen is a researcher affiliated with OpenAI, specializing in various fields. Their work has been cited 180,897 times. This profile visualizes their global influence, highlighting strong citation networks in China.
M Chen's Citation Metrics
Bibliometric impact based on 62 indexed publications.
- H-Index
- 38
- i10-Index
- 52
- Total Citations
- 180,897
- Citing Countries
- 85
As of October 2026.
M Chen has an h-index of 38 and 180,897 total citations across 62 publications, with research cited by institutions in 85 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing M Chen's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
Showing partial map from open academic databases
Upgrade ($39.98) for the complete Google Scholar crawl.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Language models are few-shot learners
202074,502
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
The researcher advanced the field by demonstrating that large-scale language models can perform complex tasks with minimal examples, establishing few-shot learning as a viable paradigm.
The researcher advanced the field by demonstrating that large-scale language models can perform complex tasks with minimal examples, establishing few-shot learning as a viable paradigm.
The researcher advanced the field of large language models by publishing the seminal technical report on GPT-4, establishing a foundational benchmark for multimodal AI capabilities.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
Related Guides
Learn how to use citation maps for your research and visa applications.
About M Chen's research
M Chen is a researcher at OpenAI. Their work has been cited 180,897 times across 62 publications (h-index 38), according to Google Scholar.
Their most-cited work, “Language models are few-shot learners” (2020), has accumulated 74,502 citations. Other influential works include “Gpt-4 technical report” (2023) with 27,979 citations and “Evaluating large language models trained on code” (2021) with 12,104 citations.
Citations of M Chen's research come primarily from China, United States and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
