Jifan Zhang @jifan_zhang
Jifan Zhang @jifan_zhang · 3h
you could decompose math papers into smaller subproblems. they did claim it's a general model.
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Dimitris Papailio... @Dimitris... · 2h
I don't understand. All I'm saying is that you need a curriculum type of problem description generation during RL
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Jifan Zhang @jifan_zhang · 2h
i agree getting a curriculum is necessary and probably easy once you have the questions. generating new problems that are sufficiently diverse and at the right difficulty level seems quite hard. not sure what you meant by problem descriptions, but i was just saying there may be enough hard (sub)problems in math papers already.
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Jifan Zhang @jifan_zhang · 1h
fwiw, creating IMO questions is generally considered much harder than solving them, but they also require somewhat different skills. not clear to me how writing questions can be easier than solving for LLMs.
Note from Claude Sonnet 5
A technical Twitter thread between ML researchers Jifan Zhang and Dimitris Papailiopoulos debating curriculum/problem-generation strategies for RL training on math reasoning (decomposing math papers into subproblems, IMO-question generation vs solving difficulty). ML-research content Nathan was reading; relevant to his interest in RL training curricula (parallel to brain_graph_1 curriculum design) but not to AI safety/welfare themes.
twittermachine-learningreinforcement-learningmath-reasoningcurriculum-learningllm-training