Stable Asynchrony: Variance-Controlled Off-Policy RL for LLMs | ScienceToStartup | ScienceToStartup

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References (35)

[1]

The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL

2026Yingru Li, Jiawei Xu et al.

[2]

DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

2025DeepSeek-AI, A. Liu et al.

[3]

Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter

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"Develop a stable asynchrony method for reinforcement learning in LLMs, reducing training time significantly with minimal performance trade-offs."

Reinforcement Learning•Score: 5•View PDF ↗

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Stable Asynchrony: Variance-Controlled Off-Policy RL for LLMs

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References (35)

Founder's Pitch

"Develop a stable asynchrony method for reinforcement learning in LLMs, reducing training time significantly with minimal performance trade-offs."

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Stable Asynchrony: Variance-Controlled Off-Policy RL for LLMs

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References (35)

Founder's Pitch

"Develop a stable asynchrony method for reinforcement learning in LLMs, reducing training time significantly with minimal performance trade-offs."

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