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Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning
PODS decouples reinforcement learning phases by parallelizing rollouts and selectively updating, using max-variance down-sampling to enhance performance on the GSM8K benchmark compared to standard GRPO.
https://arxiv.org/abs//2504.13818
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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By Igor Melnyk
5
33 ratings
PODS decouples reinforcement learning phases by parallelizing rollouts and selectively updating, using max-variance down-sampling to enhance performance on the GSM8K benchmark compared to standard GRPO.
https://arxiv.org/abs//2504.13818
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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