Scholar4AI Updated 2026-11-03 14:43 UTC+09:00

openai/baselines: papers linking to it

GitHub · 16,775 stars · 4,918 forks · Python · license MIT · created 2017 · github.com/openai/baselines

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to openai/baselines (https://github.com/openai/baselines), 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.

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Key findings#

  • 10 papers in the tracked journals link to the GitHub repository openai/baselines in their Crossref records, the first in 2019; most of them (3) in 2022.
  • By category: AI (10); the journals with the most are Applied Intelligence (3), Expert Systems with Applications (2) and Machine Learning (2).
  • Linked repositories derived from it: 1, such as hill-a/stable-baselines.

By year#

2019: 1 paper2020: 2 papers2021: 2 papers2022: 3 papers2023: 1 paper2025: 1 paper
20192025
Papers linking to openai/baselines by publication year
YearPapers
20191
20202
20212
20223
20231
20251

Journals#

Journals whose papers link to openai/baselines most
JournalPapers
Applied Intelligence3
Expert Systems with Applications2
Machine Learning2
Neural Networks1
Neural Computing and Applications1
Linked repositories openai/baselines derives from or that derive from it
RepositoryRelationPapers
hill-a/stable-baselinesfork of openai/baselines12
Papers linking to openai/baselines, most cited first
PublishedTitleJournalAuthorsCitationsLink
2019-10-29Reward-driven U-Net training for obstacle avoidance droneExpert Systems with ApplicationsSangyun Shin, Yong-Won Kang, Yong-Guk Kim42cites it
2022-03-14Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networksNature Machine IntelligenceYuqin Chen, Yu Chen, Chee‐Kong Lee et al.38cites it
2020-09-16Fast and slow curiosity for high-level exploration in reinforcement learningApplied IntelligenceNicolas Bougie, Ryutaro Ichise32cites it
2020-06-01Combining a gradient-based method and an evolution strategy for multi-objective reinforcement learningApplied IntelligenceDiqi Chen, Yizhou Wang, Wen Gao31cites it
2021-05-07Importance sampling in reinforcement learning with an estimated behavior policyMachine LearningJosiah P. Hanna, Scott Niekum, Peter Stone27cites it
2022-03-23MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learningNeural NetworksMarko Vasić, Andrija Petrović, Kaiyuan Wang et al.26cites it
2022-05-19Towards designing a generic and comprehensive deep reinforcement learning frameworkApplied IntelligenceNgoc Duy Nguyen, Thanh Thi Nguyen, Nhat Truong Pham et al.7cites it
2023-10-26Deep intrinsically motivated exploration in continuous controlMachine LearningBaturay Sağlam, Süleyman S. Kozat5cites it
2021-03-03Self-guided deep deterministic policy gradient with multi-actorNeural Computing and ApplicationsHongming Chen, Quan Liu, Shan Zhong4cites it
2025-12-04CLARIFID: Improving radiology report generation by reinforcing clinically accurate impressions and enforcing detailed findingsExpert Systems with ApplicationsKyeongkyu Lee, Seonghwan Yoon, Hongki Lim2cites 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). openai/baselines: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-openai-baselines

@misc{scholar4ai-code-github-openai-baselines,
  author = {{Scholar4AI}},
  title = {openai/baselines: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-openai-baselines}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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