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t55

892 カルマ登録 3 年前
ML researcher

投稿

RL Speedrun

github.com
2 ポイント·投稿者 t55·25 日前·0 コメント

Target Policy Optimization

arxiv.org
1 ポイント·投稿者 t55·3 か月前·0 コメント

Show HN: Kilroy – Knowledge base for teams using Claude Code

github.com
5 ポイント·投稿者 t55·3 か月前·0 コメント

Procedural Reasoning Datasets

github.com
1 ポイント·投稿者 t55·11 か月前·0 コメント

In Defence of Gary Marcus

reubenadams.substack.com
3 ポイント·投稿者 t55·12 か月前·0 コメント

Reasoning Gym – Procedural RL reasoning datasets

github.com
1 ポイント·投稿者 t55·12 か月前·0 コメント

ChatGPT Agent [video]

youtube.com
3 ポイント·投稿者 t55·12 か月前·0 コメント

ReasoningGym: Reasoning Environments for RL with Verifiable Rewards

arxiv.org
105 ポイント·投稿者 t55·昨年·28 コメント

コメント

t55
·7 日前·議論
what timelines do you have in mind
t55
·6 か月前·議論
[flagged]
t55
·12 か月前·議論
that's a standard feature in cursor, windsurf, etc.
t55
·昨年·議論
this is what deepmind did 10 years ago lol
t55
·昨年·議論
yeah, RLVR is still nascent and hence there's lots of noise.

> How can these spurious rewards possibly work? Can we get similar gains on other models with broken rewards?

it's because in those cases, RLVR merely elicits the reasoning strategies already contained in the model through pre-training

this paper, which uses Reasoning gym, shows that you need to train for way longer than those papers you mentioned to actually uncover novel reasoning strategies: https://arxiv.org/abs/2505.24864
t55
·昨年·議論
so you think it's fake news? another example of a paper with strong claims without much evidence?
t55
·昨年·議論
agree, the RG evals feel like a fresh breeze
t55
·昨年·議論
> prolonged RL training can uncover novel reasoning strategies that are inaccessible to base models, even under extensive sampling

does this mean that previous RL papers claiming the opposite were possibly bottlenecked by small datasets?
t55
·昨年·議論
> I personally think that Gemini 2.5 Pro's superiority comes from having hundreds or thousands RL tasks (without any proof whatsoever, so rather a feeling).

Given that GDM pioneered RL, that's a reasonable assumption
t55
·昨年·議論
[flagged]
t55
·昨年·議論
Anthropic doubling down on code makes sense, that has been their strong suit compared to all other models

Curious how their Devin competitor will pan out given Devin's challenges