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DeepSeek 公開論文リスト

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

公開日：2024-1-5
url: https://arxiv.org/abs/2401.02954

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

公開日：2024-1-11
url: https://arxiv.org/abs/2401.06066

DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

公開日：2024-1-25
url: https://arxiv.org/abs/2401.14196

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

公開日：2024-2-5
url: https://arxiv.org/abs/2402.03300

DeepSeek-VL: Towards Real-World Vision-Language Understanding

公開日：2024-3-8
url: https://arxiv.org/abs/2403.05525

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

公開日：2024-5-7
url: https://arxiv.org/abs/2405.04434

DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data

公開日：2024-5-23
url: https://arxiv.org/abs/2405.14333

DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

公開日：2024-6-17
url: https://arxiv.org/abs/2406.11931

Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models

公開日：2024-7-2
url: https://arxiv.org/abs/2407.01906

DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

公開日：2024-8-15
url: https://arxiv.org/abs/2408.08152

Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation

公開日：2024-10-17
url: https://arxiv.org/abs/2410.13848

JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation

公開日：2024-11-12
url: https://arxiv.org/abs/2411.07975

DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

公開日：2024-12-13
url: https://arxiv.org/abs/2412.10302

DeepSeek-V3 Technical Report

公開日：2024-12-27
url: https://arxiv.org/abs/2412.19437

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

公開日：2025-1-22
url: https://arxiv.org/abs/2501.12948

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