---
title: "langchain-ai/langchain: papers citing it"
description: "9 papers in the tracked journals link to the GitHub repository langchain-ai/langchain in their Crossref records, the first in 2024; most of them (4) in 2025."
url: https://scholar4ai.com/code/github-langchain-ai-langchain
markdown_url: https://scholar4ai.com/code/github-langchain-ai-langchain.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "9 papers in the tracked journals link to the GitHub repository langchain-ai/langchain in their Crossref records, the first in 2024; most of them (4) 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)
---

# langchain-ai/langchain: papers linking to it

Research papers in the 480 tracked journals that link to langchain-ai/langchain (https://github.com/langchain-ai/langchain), 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
- 148,922 stars
- 25,036 forks
- Python
- license MIT
- created 2022
- https://github.com/langchain-ai/langchain

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

## Key findings

- 9 papers in the tracked journals link to the GitHub repository langchain-ai/langchain in their Crossref records, the first in 2024; most of them (4) in 2025.
- By category: AI (7), Information Systems (1) and Economics (1); the journals with the most are Expert Systems with Applications (4), Journal of Industrial Information Integration (1) and Neural Computing and Applications (1).

## By year

*Papers linking to langchain-ai/langchain by publication year*

| Year | Papers |
|---|---:|
| 2024 | 4 |
| 2025 | 4 |
| 2026 | 1 |

## Journals

*Journals whose papers link to langchain-ai/langchain most*

| Journal | Papers |
|---|---:|
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 4 |
| [Journal of Industrial Information Integration](https://scholar4ai.com/journals/journal-of-industrial-information-integration.md) | 1 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |
| [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 1 |
| [Transport Policy](https://scholar4ai.com/journals/transport-policy.md) | 1 |

## Papers

*Papers linking to langchain-ai/langchain, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2024-05-08 | [Augmenting large language models with chemistry tools](https://doi.org/10.1038/s42256-024-00832-8) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Andres M Bran, Sam Cox, Oliver Tobias Schilter et al. | 795 | cites it |
| 2024-03-14 | [TrafficGPT: Viewing, processing and interacting with traffic foundation models](https://doi.org/10.1016/j.tranpol.2024.03.006) | [Transport Policy](https://scholar4ai.com/journals/transport-policy.md) | Siyao Zhang, Daocheng Fu, Wenzhe Liang et al. | 166 | cites it |
| 2024-04-18 | [Building a knowledge graph to enrich ChatGPT responses in manufacturing service discovery](https://doi.org/10.1016/j.jii.2024.100612) | [Journal of Industrial Information Integration](https://scholar4ai.com/journals/journal-of-industrial-information-integration.md) | Yunqing Li, Binil Starly | 37 | cites it |
| 2024-12-08 | [Can Large Language Models beat wall street? Evaluating GPT-4’s impact on financial decision-making with MarketSenseAI](https://doi.org/10.1007/s00521-024-10613-4) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Georgios Fatouros, Kostas Metaxas, John K. Soldatos et al. | 25 | cites it |
| 2025-06-25 | [ChatSOS: Vector database augmented generative question answering assistant in safety engineering](https://doi.org/10.1016/j.eswa.2025.128644) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Haiyang Tang, Dongping Chen, Qingzhao Chu et al. | 5 | cites it |
| 2025-02-19 | [FinCaKG-Onto: the financial expertise depiction via causality knowledge graph and domain ontology](https://doi.org/10.1007/s10489-025-06247-1) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Ziwei Xu, Ryutaro Ichise | 4 | cites it |
| 2025-08-12 | [WADSeg: Exploiting weak attention associations for enhanced knowledge segmentation in RAG](https://doi.org/10.1016/j.eswa.2025.129297) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Tiezheng Guo, Chen Wang, Qingwen Yang et al. | 4 | cites it |
| 2025-10-06 | [AI-enhanced structured dataset building for generating meaningful knowledge relationships and diversified questions](https://doi.org/10.1016/j.eswa.2025.129939) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Wu‐Yuin Hwang, Quoc-Viet Nguyen, Min-Te Sun | 1 | cites it |
| 2026-02-04 | [OntoLLM: Enhancing LLM grounding and digression prevention with ontologies and knowledge graphs](https://doi.org/10.1016/j.eswa.2026.131505) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Pruthvi Raj Venkatesh, P. Radha Krishna | 1 | 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). langchain-ai/langchain: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-langchain-ai-langchain

```bibtex
@misc{scholar4ai-code-github-langchain-ai-langchain,
  author = {{Scholar4AI}},
  title = {langchain-ai/langchain: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-langchain-ai-langchain}},
  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/).