---
title: "MMLU: papers using this data, journals and trends"
description: "From Nov 2023 to Oct 2026, 79 archived papers mentioned MMLU in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jul 2026 (10)."
url: https://scholar4ai.com/datasets/mmlu
markdown_url: https://scholar4ai.com/datasets/mmlu.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "From Nov 2023 to Oct 2026, 79 archived papers mentioned MMLU in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jul 2026 (10). (as of 2026-11-05)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-05T06:02:37+09:00
window: 2026-10-07 to 2026-11-05
source: OpenAlex (CC0)
---

# MMLU

[Browse dataset profiles](https://scholar4ai.com/datasets/directory/page/4.md)

Benchmarks used to compare large language models on knowledge, reasoning, math and code.

- data category: LLM evaluation benchmarks
- 0 papers in the last 7 days
- Names searched for: MMLU, Massive Multitask Language Understanding

Most-used data: https://scholar4ai.com/rankings/datasets.md · All LLM evaluation benchmarks datasets: https://scholar4ai.com/datasets/llm-evaluation-benchmarks.md



## Key findings

- From Nov 2023 to Oct 2026, 79 archived papers mentioned MMLU in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jul 2026 (10).
- MMLU was mentioned in 1 paper in the last 30 days (2026-10-07 to 2026-11-05), ranking #165 of the 246 datasets mentioned.
- By journal category: AI (1).
- Most of them appeared in Artificial Intelligence Review (1).
- From 2017 to 2026 (so far), MMLU was mentioned in 79 papers in the tracked journals, most of them in AI (72), operations research (2) and information systems (1).
- 34 of them were published in 2025, against 0 in 2017.
- Since 2023, the institutions with the most of these papers were National University of Singapore (4), East China Normal University (3) and South China University of Technology (3).
- The journals publishing most of them were IEEE Transactions on Pattern Analysis and Machine Intelligence (9), Artificial Intelligence Review (9) and Information Fusion (7).
- The most-cited of them is “Large language models in medical and healthcare fields: applications, advances, and challenges” (Artificial Intelligence Review, 2024), with 247 citations.
- Papers use MMLU most often with Hugging Face Hub (27), TruthfulQA / HellaSwag / ARC (25) and GSM8K / MATH (24); it has 21 partners in the code and data network, in the group around Twitter / X, Facebook, YouTube / TikTok.

## Mentions over 36 months

*Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)*

| Trend | Nov 23–Oct 24 | Nov 24–Oct 25 | Nov 25–Oct 26 | 36 months |
|---|---:|---:|---:|---:|
|  | 8 | 29 | 42 | 79 |

## Papers per year

*Papers per publication year and category*

| Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (so far) |
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
| [AI](https://scholar4ai.com/categories/ai.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 32 | 32 |
| [Operations Research](https://scholar4ai.com/categories/operations-research.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
| [Information Systems](https://scholar4ai.com/categories/information-systems.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| [Economics](https://scholar4ai.com/categories/economics.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| [Management](https://scholar4ai.com/categories/management.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| [Accounting](https://scholar4ai.com/categories/accounting.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| [Higher Education and Research](https://scholar4ai.com/categories/higher-education-and-research.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
| All categories | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 34 | 36 |

## Where the papers come from

*Journals with the most papers, since 2023*

| # | Journal | Papers |
|---:|---|---:|
| 1 | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 9 |
| 2 | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 9 |
| 3 | [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | 7 |
| 4 | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 7 |
| 5 | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 5 |
| 6 | [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | 4 |
| 7 | [AI & Society](https://scholar4ai.com/journals/ai-society.md) | 3 |
| 8 | [IEEE Transactions on Knowledge and Data Engineering](https://scholar4ai.com/journals/ieee-transactions-on-knowledge-and-data-engineering.md) | 3 |
| 9 | [Language Resources and Evaluation](https://scholar4ai.com/journals/language-resources-and-evaluation.md) | 3 |
| 10 | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | 3 |

*Institutions with the most papers, since 2023*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [National University of Singapore](https://scholar4ai.com/institutions/national-university-of-singapore.md) | 4 |
| 2 | [East China Normal University](https://scholar4ai.com/institutions/east-china-normal-university.md) | 3 |
| 3 | [South China University of Technology](https://scholar4ai.com/institutions/south-china-university-of-technology.md) | 3 |
| 4 | The Hong Kong University of Science and Technology (Guangzhou) | 3 |
| 5 | [University of Hong Kong](https://scholar4ai.com/institutions/university-of-hong-kong.md) | 3 |
| 6 | Beijing National Research Center for Information Science and Technology | 2 |
| 7 | [Carnegie Mellon University](https://scholar4ai.com/institutions/carnegie-mellon-university.md) | 2 |
| 8 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 2 |
| 9 | [City University of Hong Kong](https://scholar4ai.com/institutions/city-university-of-hong-kong.md) | 2 |
| 10 | [Harvard University](https://scholar4ai.com/institutions/harvard-university.md) | 2 |

*Countries with the most papers, since 2023*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 29 |
| 2 | United States | 19 |
| 3 | Hong Kong | 7 |
| 4 | Singapore | 7 |
| 5 | Australia | 6 |
| 6 | United Kingdom | 6 |
| 7 | Canada | 5 |
| 8 | Spain | 5 |
| 9 | United Arab Emirates | 3 |
| 10 | Brazil | 3 |

*Keywords with the most papers, since 2023*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 56 |
| 2 | prompt engineering | 6 |
| 3 | parameter-efficient fine-tuning | 5 |
| 4 | clinical decision support | 4 |
| 5 | fine-tuning | 4 |
| 6 | hallucination mitigation | 4 |
| 7 | medical question answering | 4 |
| 8 | responsible AI | 4 |
| 9 | trustworthy AI | 4 |
| 10 | [ChatGPT](https://scholar4ai.com/keywords/chatgpt.md) | 3 |

## Most-cited papers

*Most-cited papers since 2017*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 247 | 9.7 | [Large language models in medical and healthcare fields: applications, advances, and challenges](https://doi.org/10.1007/s10462-024-10921-0) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 2024-09-20 | Dandan Wang, Shiqing Zhang |
| 2 | 210 | 9.8 | [What large language models know and what people think they know](https://doi.org/10.1038/s42256-024-00976-7) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2025-01-21 | Mark Steyvers, Heliodoro Tejeda, Aakriti Kumar et al. |
| 3 | 172 | 7.8 | [A Survey on Mixture of Experts in Large Language Models](https://doi.org/10.1109/tkde.2025.3554028) | [IEEE Transactions on Knowledge and Data Engineering](https://scholar4ai.com/journals/ieee-transactions-on-knowledge-and-data-engineering.md) | 2025-01-01 | Weilin Cai, Juyong Jiang, Fan Wang et al. |
| 4 | 158 | 6.0 | [Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives](https://doi.org/10.1109/tai.2024.3444742) | [IEEE Transactions on Artificial Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-artificial-intelligence.md) | 2024-08-19 | Desta Haileselassie Hagos, Rick Battle, Danda B. Rawat |
| 5 | 136 | 14.7 | [Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment](https://doi.org/10.1109/tpami.2026.3657354) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2026-01-27 | Lingling Xu, Haoran Xie, S. Joe Qin et al. |

## Used together with

Papers use MMLU most often with Hugging Face Hub (27), TruthfulQA / HellaSwag / ARC (25) and GSM8K / MATH (24); it has 21 partners in the code and data network, in the group around Twitter / X, Facebook, YouTube / TikTok.

*What papers use MMLU together with (at least 3 papers; lift 1 = chance)*

| Used with | Type | Papers using both | Lift |
|---|---|---:|---:|
| [Hugging Face Hub](https://scholar4ai.com/datasets/hugging-face-hub.md) | Dataset | 27 | 35.0 |
| [TruthfulQA / HellaSwag / ARC](https://scholar4ai.com/datasets/truthfulqa-hellaswag-arc.md) | Dataset | 25 | 216.3 |
| [GSM8K / MATH](https://scholar4ai.com/datasets/gsm8k-math.md) | Dataset | 24 | 274.2 |
| [Wikipedia](https://scholar4ai.com/datasets/wikipedia.md) | Dataset | 20 | 11.9 |
| [HumanEval / MBPP](https://scholar4ai.com/datasets/humaneval-mbpp.md) | Dataset | 18 | 320.6 |
| [MT-Bench / Chatbot Arena](https://scholar4ai.com/datasets/mt-bench-chatbot-arena.md) | Dataset | 14 | 102.1 |
| [Twitter / X](https://scholar4ai.com/datasets/twitter-x.md) | Dataset | 12 | 1.6 |
| [BIG-bench](https://scholar4ai.com/datasets/big-bench.md) | Dataset | 10 | 195.3 |
| [Natural language inference (SNLI, MultiNLI)](https://scholar4ai.com/datasets/natural-language-inference-snli-multinli.md) | Dataset | 9 | 58.0 |
| [Pre-training corpora (Common Crawl, C4, The Pile)](https://scholar4ai.com/datasets/pre-training-corpora-common-crawl-c4-the-pile.md) | Dataset | 9 | 49.5 |
| [CoNLL](https://scholar4ai.com/datasets/conll.md) | Dataset | 8 | 38.1 |
| [Facebook](https://scholar4ai.com/datasets/facebook.md) | Dataset | 8 | 1.6 |

The whole network: https://scholar4ai.com/code/network.md

## Papers

*Papers mentioning MMLU in the last 30 days, newest first.*

| Date | Title | Journal | Authors | Affiliations |
|---|---|---|---|---|
| 2026-10-23 | [Retrieval-augmented generation in biomedicine: a survey of technologies, datasets, and clinical applications](https://doi.org/10.1007/s10462-026-11743-y) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | Jiawei He, Boya Zhang, Hossein Rouhizadeh et al. | University of Geneva; Hunan City University; Henan University; … |

## Cite this page

Scholar4AI. (2026). MMLU. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/mmlu

```bibtex
@misc{scholar4ai-datasets-mmlu,
  author = {{Scholar4AI}},
  title = {MMLU},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/mmlu}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).