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<h1>DeepSeek Papers</h1>
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<h2>DeepSeek Research Contributions</h2>
<p>Below is a list of significant papers by DeepSeek detailing advancements in large language models (LLMs). Each paper includes a brief description and highlights upcoming deep dives.</p>
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<a href="#">DeepSeekLLM: Scaling Open-Source Language Models with Longer-termism</a>
<span class="coming-soon">[Deep Dive Coming Soon]</span>
<p><strong>Release Date:</strong> November 29, 2023<br>
This foundational paper explores scaling laws and the trade-offs between data and model size, establishing the groundwork for subsequent models.</p>
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<a href="#">DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model</a>
<span class="coming-soon">[Deep Dive Coming Soon]</span>
<p><strong>Release Date:</strong> May 2024<br>
This paper introduces a Mixture-of-Experts (MoE) architecture, enhancing performance while reducing training costs by 42%.</p>
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<a href="#">DeepSeek-V3 Technical Report</a>
<span class="coming-soon">[Deep Dive Coming Soon]</span>
<p><strong>Release Date:</strong> December 2024<br>
This report discusses the scaling of sparse MoE networks to 671 billion parameters, utilizing mixed precision training and HPC co-design strategies.</p>
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<a href="#">DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning</a>
<span class="coming-soon">[Deep Dive Coming Soon]</span>
<p><strong>Release Date:</strong> January 20, 2025<br>
The R1 model enhances reasoning capabilities through large-scale reinforcement learning, competing directly with leading models like OpenAI's o1.</p>
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<a href="#">DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models</a>
<span class="coming-soon">[Deep Dive Coming Soon]</span>
<p><strong>Release Date:</strong> April 2024<br>
This paper presents methods to improve mathematical reasoning in LLMs, introducing the Group Relative Policy Optimization (GRPO) algorithm.</p>
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<a href="#">DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data</a>
<span class="coming-soon">[Deep Dive Coming Soon]</span>
<p>Focuses on enhancing theorem proving capabilities in language models using synthetic data for training.</p>
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<a href="#">DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence</a>
<span class="coming-soon">[Deep Dive Coming Soon]</span>
<p>This paper details advancements in code-related tasks with an emphasis on open-source methodologies, improving upon earlier coding models.</p>
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<a href="#">DeepSeekMoE</a>
<span class="coming-soon">[Deep Dive Coming Soon]</span>
<p>Discusses the integration and benefits of the Mixture-of-Experts approach within the DeepSeek framework.</p>
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