arXiv
arxiv.org › abs › 2501.12948
[2501.12948] DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
January 22, 2025 - View a PDF of the paper titled DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning, by DeepSeek-AI and 199 other authors View PDF HTML (experimental)
GitHub
github.com › deepseek-ai › DeepSeek-R1 › blob › main › DeepSeek_R1.pdf
DeepSeek-R1/DeepSeek_R1.pdf at main · deepseek-ai/DeepSeek-R1
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Videos
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DeepSeek R1 Theory Overview | GRPO + RL + SFT - YouTube
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DeepSeek R1 Explained to your grandma - YouTube
DeepSeek-R1 Paper Explained - A New RL LLMs Era in AI?
DeepSeek-R1 Crash Course
Building a fully local "deep researcher" with DeepSeek-R1
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Paper: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs ...
arXiv
arxiv.org › pdf › 2501.12948 pdf
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via
In this paper, we take the first step toward improving language model reasoning capabilities · using pure reinforcement learning (RL). Our goal is to explore the potential of LLMs to develop · reasoning capabilities without any supervised data, focusing on their self-evolution through · a pure RL process. Specifically, we use DeepSeek-V3-Base as the base model and employ
DeepSeek
api-docs.deepseek.com › deepseek-r1 release 2025/01/20
DeepSeek-R1 Release | DeepSeek API Docs
📄 More details: https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf · 🌐 API Access & Pricing · ⚙️ Use DeepSeek-R1 by setting model=deepseek-reasoner · 💰 $0.14 / million input tokens (cache hit) 💰 $0.55 / million input tokens (cache miss) 💰 $2.19 / million output tokens ·
Hugging Face
huggingface.co › papers › 2501.12948
Paper page - DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
To support the research community, we open-source DeepSeek-R1-Zero, DeepSeek-R1, and six dense models (1.5B, 7B, 8B, 14B, 32B, 70B) distilled from DeepSeek-R1 based on Qwen and Llama. View arXiv page View PDF GitHub 91.6k Add to collection ... This is an automated message from the Librarian Bot. I found the following papers similar to this paper.
Reddit
reddit.com › r/singularity › a summary of deepseek-r1's paper by deepseek-r1
r/singularity on Reddit: A summary of DeepSeek-R1's paper by DeepSeek-R1
November 29, 2024 -
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Aha moments emerged naturally in RL: Self-correction behaviors like "Wait, let’s reevaluate..." arose without SFT.
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Cold-start SFT fixed readability: ~1k structured examples resolved language mixing.
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GRPO cut RL costs by 30%: Group-wise reward normalization outperformed PPO.
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RL increased CoT length autonomously: Reasoning steps grew from 100→1k tokens without penalties.
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Distillation beat direct RL in small models: SFT on R1 data outperformed RL-trained base models.
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Process rewards failed; outcome rewards worked better: Rule-based final-answer checks stabilized training.
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XML tags reduced hallucinations 15%: Structured <think>/<answer> improved reward clarity.
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Language mixing fixed via consistency rewards: Penalized code-switching in multilingual outputs.
I find it funny that ive seen multiple AI youtubers explain papers and they just go to another AI to help them in the video but hey it does a good job
https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf
Top answer 1 of 2
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DeepSeek-R1 is roughly 4.41x cheaper than o1 which means for the same price as a singular o1 query give or take you could run a consensus voting tree-of-agents system with 4 separate instances of R1 which could outperform o1 for the same price if not still cheaper
2 of 2
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The new benchmarks for R1 zero are INSANE!!!
ResearchGate
researchgate.net › publication › 388484582_Technical_Report_Analyzing_DeepSeek-R1's_Impact_on_AI_Development
(PDF) Technical Report: Analyzing DeepSeek-R1's Impact on AI Development
January 20, 2025 - PDF | The paper "DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning" introduces DeepSeek-R1-Zero and DeepSeek-R1, two... | Find, read and cite all the research you need on ResearchGate
AI Papers Academy
aipapersacademy.com › home › deepseek-r1 paper explained – a new rl llms era in ai?
DeepSeek-R1 Paper Explained – A New RL LLMs Era in AI? - AI Papers Academy
July 3, 2025 - The paper, titled “DeepSeek-R1: ... Learning”, presents a state-of-the-art, open-source reasoning model and a detailed recipe for training such models using large-scale reinforcement learning techniques....
ResearchGate
researchgate.net › publication › 389004776_DeepSeek_R1_What_Sets_It_Apart
(PDF) DeepSeek R1: What Sets It Apart?
February 14, 2025 - PDF | DeepSeek R1: The AI Powerhouse Redefining Efficiency and Innovation Breaking the mold of proprietary AI, DeepSeek R1 emerges as a game-changer... | Find, read and cite all the research you need on ResearchGate
GitHub
github.com › deepseek-ai › DeepSeek-R1
GitHub - deepseek-ai/DeepSeek-R1
DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks. To support the research community, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six dense models distilled from DeepSeek-R1 based on ...
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Tenorshare
tenorshare.com › home › tenorshare pdnob › deepseek r1 pdf explained: features, api, and more
DeepSeek R1 PDF Guide: Download, Installation, and Setup
February 6, 2025 - The DeepSeek R1 PDF provides in-depth insights into its design, training methodology, and performance benchmarks. Now, we’ll guide you on how to access these documents and highlight the key areas to focus on when reviewing them.
arXiv
arxiv.org › abs › 2502.02523
[2502.02523] Brief analysis of DeepSeek R1 and its implications for Generative AI
February 7, 2025 - View a PDF of the paper titled Brief analysis of DeepSeek R1 and its implications for Generative AI, by Sarah Mercer and 2 other authors View PDF HTML (experimental)
ResearchGate
researchgate.net › publication › 388856323_Highlighting_DeepSeek-R1_Architecture_Features_and_Future_Implications
(PDF) Highlighting DeepSeek-R1: Architecture, Features and Future Implications
February 11, 2025 - DeepSeek-R1 emphasizes unique training processes devoid of supervised fine-tuning and utilizes rule-based reinforcement learning by means of group relative policy optimization. The paper will identify the major features of DeepSeek-R1 and their ...
SSRN
papers.ssrn.com › sol3 › Delivery.cfm › 5107732.pdf
The Mathematics of DeepSeek-R1: Theoretical Foundations and ...
March 24, 2025 - Noguer I Alonso, Miquel, The Mathematics of DeepSeek-R1: Theoretical Foundations and Comparative Analysis (January 22, 2025). Available at SSRN: https://ssrn.com/abstract=5107732 or http://dx.doi.org/10.2139/ssrn.5107732 · New York United States ...
ResearchGate
researchgate.net › publication › 388231214_DeepSeek_Revolutionizing_AI_with_Open-Source_Reasoning_Models_-Advancing_Innovation_Accessibility_and_Competition_with_OpenAI_and_Gemini_20
(PDF) DeepSeek: Revolutionizing AI with Open-Source Reasoning Models -Advancing Innovation, Accessibility, and Competition with OpenAI and Gemini 2.0
January 22, 2025 - DeepSeek's AI models have emerged ... DeepSeek's success is DeepSeek-R1, a reasoning-focused model leveraging reinforcement learning (RL) through Group Relative Policy Optimization (GRPO)....
Hugging Face
huggingface.co › deepseek-ai › DeepSeek-R1-Zero
deepseek-ai/DeepSeek-R1-Zero · Hugging Face
DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks. To support the research community, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six dense models distilled from DeepSeek-R1 based on ...
ResearchGate
researchgate.net › publication › 390043387_Brief_analysis_of_DeepSeek_R1_and_its_implications_for_Generative_AI
(PDF) Brief analysis of DeepSeek R1 and its implications for Generative AI
March 5, 2025 - PDF | In late January 2025, DeepSeek released their new reasoning model (DeepSeek R1); which was developed at a fraction of the cost yet remains... | Find, read and cite all the research you need on ResearchGate
Nature
nature.com › articles › article
DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning | Nature
September 17, 2025 - To address these challenges, we introduce DeepSeek-R1, a model trained through a multistage learning framework that integrates rejection sampling, RL and supervised fine-tuning, detailed in the ‘DeepSeek-R1’ section.
X
x.com › HatforceSec › status › 1881377291080778063
Arthur Gervais on X: "Here's the full paper: https://t.co/k9GCDbH9PY" / X
DeepSeek-R1/DeepSeek_R1.pdf at main · deepseek-ai/DeepSeek-R1 · From github.com · 11:24 AM · Jan 20, 2025 · · · 170 Views · 1 · Sign up now to get your own personalized timeline! Sign up with GoogleSign up with Google. Opens in new tab · Sign up with Apple ·