---
title: "tatsu-lab/alpaca_eval: papers citing it"
description: "3 papers in the tracked journals link to the GitHub repository tatsu-lab/alpaca_eval in their Crossref records, the first in 2025; most of them (2) in 2025."
url: https://scholar4ai.com/code/github-tatsu-lab-alpaca-eval
markdown_url: https://scholar4ai.com/code/github-tatsu-lab-alpaca-eval.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "3 papers in the tracked journals link to the GitHub repository tatsu-lab/alpaca_eval in their Crossref records, the first in 2025; most of them (2) in 2025. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# tatsu-lab/alpaca_eval: papers linking to it

Research papers in the 480 tracked journals that link to tatsu-lab/alpaca_eval (https://github.com/tatsu-lab/alpaca_eval), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- GitHub
- 2,023 stars
- 314 forks
- Jupyter Notebook
- license Apache-2.0
- created 2023
- https://github.com/tatsu-lab/alpaca_eval

All repositories: https://scholar4ai.com/code.md

## Key findings

- 3 papers in the tracked journals link to the GitHub repository tatsu-lab/alpaca_eval in their Crossref records, the first in 2025; most of them (2) in 2025.
- By category: AI (3); the journals with the most are Neural Networks (1), Applied Intelligence (1) and AI & Society (1).

## By year

*Papers linking to tatsu-lab/alpaca_eval by publication year*

| Year | Papers |
|---|---:|
| 2025 | 2 |
| 2026 | 1 |

## Journals

*Journals whose papers link to tatsu-lab/alpaca_eval most*

| Journal | Papers |
|---|---:|
| [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 1 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [AI & Society](https://scholar4ai.com/journals/ai-society.md) | 1 |

## Papers

*Papers linking to tatsu-lab/alpaca_eval, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2025-04-02 | [Large language models: assessment for singularity](https://doi.org/10.1007/s00146-025-02271-4) | [AI & Society](https://scholar4ai.com/journals/ai-society.md) | Ryunosuke Ishizaki, Mahito Sugiyama | 3 | cites it |
| 2025-11-20 | [Chain-of-Detection enables robust and efficient jailbreak defense](https://doi.org/10.1016/j.neunet.2025.108217) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Tingting Wu, Hao Zhang | 2 | cites it |
| 2026-01-01 | [SIPA: a self-iterative preference alignment method for generative language models](https://doi.org/10.1007/s10489-025-07079-9) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Yongping Du, Binrui Wang, Yin Hou et al. | 0 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). tatsu-lab/alpaca_eval: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-tatsu-lab-alpaca-eval

```bibtex
@misc{scholar4ai-code-github-tatsu-lab-alpaca-eval,
  author = {{Scholar4AI}},
  title = {tatsu-lab/alpaca_eval: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-tatsu-lab-alpaca-eval}},
  urldate = {2026-11-03},
  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/).