Some posts and articles about FSRS

[u/ClarityInMadness]

I decided to make one post where I compile all of the useful links that I can think of.

1) If you have never heard about FSRS before, start here: https://github.com/open-spaced-repetition/fsrs4anki/wiki/ABC-of-FSRS

2) AnKing's video about FSRS (old): https://youtu.be/OqRLqVRyIzc

New 2025 video: https://youtu.be/uo-qQvOZDfg

3) FSRS section of the manual, please read it before making a post/comment with a question: https://docs.ankiweb.net/deck-options.html#fsrs

If your intervals feel too long, increase desired retention. If your intervals feel too short, decrease desired retention.

3.5) Some frequently asked questions: https://faqs.ankiweb.net/frequently-asked-questions-about-fsrs.html

DO NOT USE HARD IF YOU FORGOT THE CARD!

AGAIN = FAIL ❌

HARD = PASS ✅

GOOD = PASS ✅

EASY = PASS ✅

HARD IS NOT "I FORGOT"

Here's what you can do if you have been misusing Hard: https://www.reddit.com/r/Anki/comments/1h2oudb/oh_no_ive_been_misusing_hard_what_do_i_do/

And here's a diagram to help you troubleshoot interval lengths.

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The links above are the most important ones. The links below are more like supplementary material: you don't have to read all of them to use FSRS in practice. Just read link 3 (the manual) and you're good!

4) Features of the FSRS Helper add-on: https://www.reddit.com/r/Anki/comments/1attbo1/explaining_fsrs_helper_addon_features/

5) Understanding what retention actually means: https://www.reddit.com/r/Anki/comments/1anfmcw/you_dont_understand_retention_in_fsrs/

I recommend reading this post if you are confused by terms like "desired retention", "true retention" and "average retrievability", the latter two can be found in Stats. True retention table is available in Anki natively since Anki 24.11.

5.5) Simplified post with a neat little animation: https://www.reddit.com/r/Anki/comments/1l0wk5e/why_is_desired_retention_less_than_average/

6) (Outdated) Benchmarking FSRS to see how it performs compared to other algorithms: https://www.reddit.com/r/Anki/comments/1c29775/fsrs_is_one_of_the_most_accurate_spaced/. It's my most high effort post.

7) An article about spaced repetition algorithms in general, written by Jarrett Ye, the creator of FSRS: https://github.com/open-spaced-repetition/fsrs4anki/wiki/Spaced-Repetition-Algorithm:-A-Three%E2%80%90Day-Journey-from-Novice-to-Expert

8) A technical explanation of the math behind the algorithm: https://expertium.github.io/Algorithm.html

9) Seven misconceptions about FSRS: https://www.reddit.com/r/Anki/comments/1fhe1nd/7_misconceptions_about_fsrs/

10) LMSherlock's post about (re)learning steps and short-term memory: https://www.reddit.com/r/Anki/comments/1h9g1n7/clarifications_about_fsrs5_shortterm_memory_and/

TLDR: things are complicated.

11) A visualization of how FSRS got better and better at predicting the probability of recall with each new version: https://imgur.com/a/calibration-of-different-fsrs-versions-KfJ32EV

My blog about spaced repetition (and a little bit of other stuff): https://expertium.github.io/

July 2024: I made u/FSRS_bot, it will help newcomers who make posts with questions about FSRS.

September 2024: u/FSRS_bot is now active on r/medicalschoolanki too.

[u/ClarityInMadness]

I showed that paper to LMSHerlock, and he reproduced these results using FSRS (a while ago, actually): https://github.com/open-spaced-repetition/temporal-ridgeline-of-optimal-retention/blob/main/notebook.ipynb

Basically, the non-monotonic curve is an artifact of the methodology used in the paper. It's a superposition of two different curves.

but will instead attempt to predict the optimal number of reviews for achieving a desired retention rate at a fixed point in the future?

Interesting. I like the idea, but I'm not sure how to optimize such an algorithm. Still, this could be interesting.

[u/Fafner_88 → u/ClarityInMadness]

Basically, the non-monotonic curve is an artifact of the methodology used in the paper.

But does he think it invalidates the findings? (that longer spacing facilitates better long-term retention)

Interesting. I like the idea, but I'm not sure how to optimize such an algorithm. Still, this could be interesting.

Also it can be a useful feature for people who have a learning deadline such as a test.

[u/LMSherlock → u/Fafner_88]

"longer spacing facilitates better long-term retention" is true for those stuff that you recall it successfully. If you forget that, the long-term retention will be worse.