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豆包·视觉理解模型
具备非常强的内容识别能力,同时,拥有出色的理解推理和细腻的视觉描述表现。
研究成果
Computer Vision
SeedEdit: Align Image Re-Generation to Image Editing
Yichun Shi, Peng Wang, Weilin Huang

2024-11-11

System Research

ByteCheckpoint: A Unified Checkpointing System for LLM Development

Borui Wan, Mingji Han, Yiyao Sheng, Zhichao Lai, Mofan Zhang, Junda Zhang, Yanghua Peng, Haibin Lin, Xin Liu, Chuan Wu

2024-07-29

Speech&Audio

SD-Eval: A Benchmark Dataset for Spoken Dialogue Understanding Beyond Words

Junyi Ao, Yuancheng Wang, Xiaohai Tian, Dekun Chen, Jun Zhang, Lu Lu, Yuxuan Wang, Haizhou Li, Zhizheng Wu

2024-06-19

NLP

Let the Code LLM Edit Itself When You Edit the Code

Zhenyu He, Jun Zhang, Shengjie Luo, Jingjing Xu, Zhi Zhang, Di He

2024-07-03

LLM

How Far is Video Generation from World Model: A Physical Law Perspective

Bingyi Kang, Yang Yue, Rui Lu, Zhijie Lin, Yang Zhao, Kaixin Wang, Gao Huang, Jiashi Feng

2024-11-04

LLM

Why Does the Effective Context Length of LLMs Fall Short?

Chenxin An, Jun Zhang, Ming Zhong, Lei Li, Shansan Gong, Yao Luo, Jingjing Xu, Lingpeng Kong

2024-10-24

Computer Vision

Depth Anything V2

Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao

2024-06-13

模型家族
豆包通用模型 Pro
支持128K长文本,全系列可精调,具备更强的理解、生成、逻辑等综合能力
豆包通用模型 Lite
轻量版模型,对比专业版提供更低token成本、更低延迟
豆包·角色扮演模型
个性化的角色创作能力,更强的上下文感知和剧情推动能力
技术落地
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