[nomadpenguin]

Poor generalization (overtraining on prompts) and loss of context over time are the biggest issues I've found with them. Slow card creation workflows and needing to rate your own reviews are merely UX issues -- losing context and losing generalization make SRS actively harmful when used for some topics.

There's 2 solutions I've thought of but haven't tried implementing:

1. A free-recall based approach. Free recall allows you to operate at a higher level of organization and connect concepts at lower levels. However, how you would schedule SRS with free recall is not clear.

2. Have an LLM generate questions on-the-fly so that you don't overtrain on prompts. You might also instruct the LLM to create questions that connect multiple concepts together. The problem with this approach is that LLMs are still not so good at creating good test questions.

[barrell]

I implemented free recall into FSRS pretty easily. Granted, it’s only for language learning, and I have it set up to work in a free recall friendly way (you don’t learn cards, you learn actual words and morphemes) but it’s been working for a few weeks now. I’m working on a product video atm, but once that’s done my next task (sometime this week) is to clean up the UI and merge it to master.

I almost never see someone talk about free recall so I was too excited to see it mentioned not to comment

[nomadpenguin]

How are you handling scheduling with FSRS? The challenge that I quickly saw was that it was difficult to figure out when you should advance a segment of information. If you get 80% of the info right, should it be advanced? What happens to the 20% you missed? How do you prevent yourself from missing the same 20% every time it comes around?