Reasoning & Test-Time Compute · 2025
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Fully open-sources a large-scale RLVR system and names four techniques (decoupled clipping, dynamic sampling, token-level loss, overlong-reward shaping) that make reproducible reasoning-RL training work.
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Plain-language summary
Fully open-sources a large-scale RLVR system and names four techniques (decoupled clipping, dynamic sampling, token-level loss, overlong-reward shaping) that make reproducible reasoning-RL training work.
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Conceptual ancestorEvidence: Strongly supported
Chain-of-Thought Prompting Elicits Reasoning
Builds on the reasoning lineage in the archive
freshness sweep 2026
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Provenance
- Record ID
- P-641
- Record created
- 2026-07-13
- Last reviewed
- 2026-07-14
- Record version
- 2
- https://arxiv.org/abs/2503.14476
- arXiv:2503.14476
Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.