---
title: "LLM evaluation benchmarks datasets"
description: "Datasets in the category “LLM evaluation benchmarks” were mentioned in 7 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #40 of the 58 data categories mentioned."
url: https://scholar4ai.com/datasets/llm-evaluation-benchmarks
markdown_url: https://scholar4ai.com/datasets/llm-evaluation-benchmarks.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "Datasets in the category “LLM evaluation benchmarks” were mentioned in 7 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #40 of the 58 data categories mentioned."
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-10-26T14:52:47+09:00
window: 2026-09-27 to 2026-10-26
source: OpenAlex (CC0)
---

# LLM evaluation benchmarks

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

- 0 papers in the last 7 days
- 3 of its 6 datasets mentioned

Back to the ranking: https://scholar4ai.com/rankings/datasets.md

## Key findings

- Datasets in the category “LLM evaluation benchmarks” were mentioned in 7 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #40 of the 58 data categories mentioned.
- The most-mentioned were MT-Bench / Chatbot Arena (4), GSM8K / MATH (2) and TruthfulQA / HellaSwag / ARC (1).
- By journal category: AI (5), Finance (1) and Management (1).
- Most of them appeared in Neural Computing and Applications (2), Neural Networks (1) and Journal of Financial Economics (1).

## Datasets

*Datasets in this category · 2026-09-27 – 2026-10-26 (30 days)*

| Dataset | Papers | Last 7 days | Names searched for |
|---|---:|---:|---|
| MT-Bench / Chatbot Arena | 4 | 0 | MT-Bench, Chatbot Arena |
| GSM8K / MATH | 2 | 0 | GSM8K, MATH benchmark, MATH dataset |
| TruthfulQA / HellaSwag / ARC | 1 | 0 | TruthfulQA, HellaSwag, AI2 Reasoning Challenge, ARC-Challenge, ARC-Easy |
| BIG-bench | 0 | 0 | BIG-bench, BIG-Bench Hard |
| HumanEval / MBPP | 0 | 0 | HumanEval, MBPP |
| MMLU | 0 | 0 | MMLU, Massive Multitask Language Understanding |

## Papers

*Papers mentioning these datasets, newest first.*

| Date | Title | Journal | Authors | Affiliations | Datasets mentioned |
|---|---|---|---|---|---|
| 2026-10-19 | [CODER: Data-efficient activation of mathematical reasoning via difficulty-aware core-set](https://doi.org/10.1016/j.neunet.2026.109765) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Lei Wang, GuoAo Liu, Xiaoyong Zhao | Beijing Information Science & Technology University | GSM8K / MATH |
| 2026-10-06 | [Chronologically consistent large language models](https://doi.org/10.1016/j.jfineco.2026.104374) | [Journal of Financial Economics](https://scholar4ai.com/journals/journal-of-financial-economics.md) | Songrun He, Linying Lv, Asaf Manela et al. | Chinese University of Hong Kong; Washington University in St. Louis; University of Iowa | TruthfulQA / HellaSwag / ARC |
| 2026-10-03 | [StoryReasoning dataset: Using chain-of-thought for scene understanding and grounded story generation](https://doi.org/10.1016/j.patcog.2026.115061) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Daniel A. P. Oliveira, David Martins de Matos | Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento; University of Lisbon; Instituto Superior Técnico | MT-Bench / Chatbot Arena |
| 2026-10-02 | [Assessing inter-rater agreement among large language model judges: Evidence from persona evaluation across varying educational risk contexts](https://doi.org/10.1016/j.techfore.2026.124894) | [Technological Forecasting and Social Change](https://scholar4ai.com/journals/technological-forecasting-and-social-change.md) | Danial Amin, Joni O. Salminen, Bernard J. Jim Jansen | University of Vaasa; Peking University; Nankai University | MT-Bench / Chatbot Arena |
| 2026-10-01 | [Ontology-guided neuro-symbolic GraphRAG for grounded query answering](https://doi.org/10.1007/s00521-026-12495-0) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Domenico Benfenati, Antonio M. Rinaldi | University of Naples Federico II | MT-Bench / Chatbot Arena |
| 2026-10-01 | [Performance within the foundation paradox: the case for small qualitative evaluations](https://doi.org/10.1007/s00521-026-12328-0) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Michael P. Simeone, Jacki Hyatt, Elisa Jayne Bienenstock et al. | Arizona State University | MT-Bench / Chatbot Arena |
| 2026-09-28 | [Mapping the RAG landscape: a four-axis taxonomy of efficiency, defense, interactivity, and reasoning](https://doi.org/10.1007/s10462-026-11715-2) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | Meghana Sunil, Vaddepalli Shravya, Shravan Venkatraman et al. | Vellore Institute of Technology University; Mohamed bin Zayed University of Artificial Intelligence | GSM8K / MATH |

## Cite this page

Scholar4AI. (2026). LLM evaluation benchmarks. Journal Research Rankings. Retrieved October 26, 2026, from https://scholar4ai.com/datasets/llm-evaluation-benchmarks

```bibtex
@misc{scholar4ai-datasets-llm-evaluation-benchmarks,
  author = {{Scholar4AI}},
  title = {LLM evaluation benchmarks},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/llm-evaluation-benchmarks}},
  urldate = {2026-10-26},
  note = {Journal 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/).