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@@ -17,11 +17,17 @@ Our mission is to develop efficient, effective, and accessible spaced repetition
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  ## Features
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- - **Multiple Language Support**: [ts-fsrs](https://github.com/open-spaced-repetition/ts-fsrs), [go-fsrs](https://github.com/open-spaced-repetition/go-fsrs), [fsrs-rs](https://github.com/open-spaced-repetition/fsrs-rs), [rs-fsrs](https://github.com/open-spaced-repetition/rs-fsrs), [py-fsrs](https://github.com/open-spaced-repetition/py-fsrs), [cljc-fsrs](https://github.com/open-spaced-repetition/cljc-fsrs), [swift-fsrs](https://github.com/open-spaced-repetition/swift-fsrs), [ex_fsrs](https://github.com/open-spaced-repetition/ex_fsrs) and so on.
 
 
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  - **Scientifically-Backed**:
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- - [A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling | Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining](https://dl.acm.org/doi/10.1145/3534678.3539081)
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- - [Optimizing Spaced Repetition Schedule by Capturing the Dynamics of Memory | IEEE Journals & Magazine | IEEE Xplore](https://ieeexplore.ieee.org/document/10059206)
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  - [open-spaced-repetition/srs-benchmark: A benchmark for spaced repetition schedulers/algorithms (github.com)](https://github.com/open-spaced-repetition/srs-benchmark)
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  - **Plugin & Add-on**: [fsrs4anki-helper](https://github.com/open-spaced-repetition/fsrs4anki-helper), [fsrs4tw](https://github.com/open-spaced-repetition/fsrs4tw), [obsidian-spaced-repetition-recall](https://github.com/open-spaced-repetition/obsidian-spaced-repetition-recall), [fsrs4remnote](https://github.com/open-spaced-repetition/fsrs4remnote) and so on.
 
 
 
 
 
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  ## Features
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+ - **Multiple Language Support**:
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+ - w/o optimization: [ts-fsrs](https://github.com/open-spaced-repetition/ts-fsrs), [go-fsrs](https://github.com/open-spaced-repetition/go-fsrs), [rs-fsrs](https://github.com/open-spaced-repetition/rs-fsrs), [c/cpp binding](https://github.com/open-spaced-repetition/rs-fsrs-c), [java binding](https://github.com/open-spaced-repetition/rs-fsrs-java), [cljc-fsrs](https://github.com/open-spaced-repetition/cljc-fsrs), [swift-fsrs](https://github.com/open-spaced-repetition/swift-fsrs), [ex_fsrs](https://github.com/open-spaced-repetition/ex_fsrs), [dart-fsrs](https://github.com/open-spaced-repetition/dart-fsrs), [rb-fsrs](https://github.com/open-spaced-repetition/rb-fsrs)
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+ - w/ optimization: [fsrs-rs](https://github.com/open-spaced-repetition/fsrs-rs), [fsrs-rs-c](https://github.com/open-spaced-repetition/fsrs-rs-c), [fsrs-rs-python](https://github.com/open-spaced-repetition/fsrs-rs-python), [fsrs-browser](https://github.com/open-spaced-repetition/fsrs-browser), [fsrs-rs-nodejs](https://github.com/open-spaced-repetition/fsrs-rs-nodejs), [fsrs-rs-dart](https://github.com/open-spaced-repetition/fsrs-rs-dart), [fsrs-rs-php](https://github.com/open-spaced-repetition/fsrs-rs-php), [py-fsrs](https://github.com/open-spaced-repetition/py-fsrs)
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  - **Scientifically-Backed**:
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+ - [A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling | Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining](https://dl.acm.org/doi/10.1145/3534678.3539081?cid=99660547150)
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+ - [Optimizing Spaced Repetition Schedule by Capturing the Dynamics of Memory | IEEE Journals & Magazine | IEEE Xplore](https://drive.google.com/file/d/1riJbkH39JB71Wj0AzESTngUM0LaeoD2l/view)
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  - [open-spaced-repetition/srs-benchmark: A benchmark for spaced repetition schedulers/algorithms (github.com)](https://github.com/open-spaced-repetition/srs-benchmark)
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  - **Plugin & Add-on**: [fsrs4anki-helper](https://github.com/open-spaced-repetition/fsrs4anki-helper), [fsrs4tw](https://github.com/open-spaced-repetition/fsrs4tw), [obsidian-spaced-repetition-recall](https://github.com/open-spaced-repetition/obsidian-spaced-repetition-recall), [fsrs4remnote](https://github.com/open-spaced-repetition/fsrs4remnote) and so on.
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+ ## Acknowledgements
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+ A special thanks to [墨墨背单词 (MaiMemo Inc.)](https://www.maimemo.com/) for their support of FSRS development by allowing its research engineer, [Jarrett Ye](https://github.com/L-M-Sherlock), to dedicate part of his working hours to this open-source project. This greatly helps in the continuous improvement and maintenance of FSRS for the benefit of the entire community.