884 citations · 892 across the 2 of their papers we have counts for
5 papers · 1 filter
DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding
Zhiyu Wu, Xiaokang Chen, Zizheng Pan +24
We present DeepSeek-VL2, an advanced series of large Mixture-of-Experts (MoE) Vision-Language Models that significantly improves upon its predecessor, DeepSeek-VL, through two key…
Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation
Chengyue Wu, Xiaokang Chen, Zhiyu Wu +8
In this paper, we introduce Janus, an autoregressive framework that unifies multimodal understanding and generation. Prior research often relies on a single visual encoder for both…
DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search
Huajian Xin, Z. Z. Ren, Junxiao Song +14
We introduce DeepSeek-Prover-V1.5, an open-source language model designed for theorem proving in Lean 4, which enhances DeepSeek-Prover-V1 by optimizing both training and inference…
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
DeepSeek-AI, Qihao Zhu, Daya Guo +37
We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks. Specifically, D…
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Huajian Xin, Daya Guo, Zhihong Shao +6
Proof assistants like Lean have revolutionized mathematical proof verification, ensuring high accuracy and reliability. Although large language models (LLMs) show promise in mathem…