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The R1 report distinguishes R1-Zero’s RL without preliminary SFT from R1’s cold-start training. Copy claim link
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Supporting evidence: primary · 1 source
Date 2025-01-22 · publication Scope and limits Authors’ method account; no independent reproduction or earliest-invention claim.
The evidence 01 primary source Supports the claim
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning ↗ DeepSeek-AI · 2025-01-22
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Cite the original source Cite the original document, not Selekoa. Check these details against it.
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Paraphrase R1-Zero applies reinforcement learning directly; R1 begins from a checkpoint fine-tuned on cold-start examples.
Location in source §2.1 Overview; §2.2 and §2.3
Machine-checked · 2026-09-29
Source details and check notes Authors DeepSeek-AI Version Source language: English (en). arXiv:2501.12948v1; fixed first version. Canonical address Open the canonical source ↗ Accessed 2026-09-29 Language English (en) Attribution DeepSeek-AI, DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning (2025-01-22). Reuse No redistribution licence asserted for this source expression. Bibliographic metadata and brief attributed paraphrases only; model licensing is distinct from source-document reuse. Check notes English source paraphrased and checked by machine. Exploratory seed, not editorially accepted. Source reporting is not independent verification of implementation. Status and meaning Editorial status. Not reviewed by an editor . An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.
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Record ID cn-r1-rl