Recycling Failures: Salvaging Exploration in RLVR via Fine-Grained Off-Policy Guidance | ScienceToStartup | ScienceToStartup

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References (53)

[1]

Scaf-GRPO: Scaffolded Group Relative Policy Optimization for Enhancing LLM Reasoning

2025Xichen Zhang, Sitong Wu et al.

[2]

Post-training Large Language Models for Diverse High-Quality Responses

2025Yilei Chen, Souradip Chakraborty et al.

[3]

Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training

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"Develop SCOPE, a framework enhancing reinforcement learning by refining partially correct trajectories for broader exploration in complex reasoning models."

Reinforcement Learning•Score: 6•View PDF ↗

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Recycling Failures: Salvaging Exploration in RLVR via Fine-Grained Off-Policy Guidance

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References (53)

Founder's Pitch

"Develop SCOPE, a framework enhancing reinforcement learning by refining partially correct trajectories for broader exploration in complex reasoning models."

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Recycling Failures: Salvaging Exploration in RLVR via Fine-Grained Off-Policy Guidance

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References (53)

Founder's Pitch

"Develop SCOPE, a framework enhancing reinforcement learning by refining partially correct trajectories for broader exploration in complex reasoning models."

Commercial Viability Breakdown

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