diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000..ad09fc4 Binary files /dev/null and b/.DS_Store differ diff --git a/404.html b/404.html new file mode 100644 index 0000000..f8414f0 --- /dev/null +++ b/404.html @@ -0,0 +1,3 @@ + +404 Not Found +

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diff --git a/CNAME b/CNAME new file mode 100644 index 0000000..9544e71 --- /dev/null +++ b/CNAME @@ -0,0 +1 @@ +https://qingkelab.github.io/talks/ \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..40a0c66 --- /dev/null +++ b/README.md @@ -0,0 +1,31 @@ + +![](images/pdf.001.png) +### [青稞](https://qingkelab.github.io)·[知识社区](https://qingkelab.github.io/talks)直播分享 + +| 直播时间 | 主讲人 | 主题 | 直播/回放观看链接 | +| :--------: | :---------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------: | :--------------------------------------------------------------------: | +| 2024.07.30 | 香港科技大学（广州）人工智能方向博士研究生杨帅 | SEED-Story：生成长篇图文故事的多模态大型语言模型 | [https://hcqnc.xetlk.com/sl/3xzywr](https://hcqnc.xetlk.com/sl/3xzywr) | +| 2024.07.23 | 华中科技大学博士生程天恒 | YOLO-World：基于视觉语言模型的实时开放词汇物体检测 | [https://hcqnc.xetlk.com/sl/12dD2S](https://hcqnc.xetlk.com/sl/12dD2S) | +| 2024.07.15 | 清华大学自然语言处理实验室博士生余天予 | MiniCPM-V：端侧可用的 GPT-4V 级多模态大模型 | [https://hcqnc.xetlk.com/sl/30sK4y](https://hcqnc.xetlk.com/sl/30sK4y) | +| 2024.07.11 | 阿里通义实验室高级算法专家徐海洋 | Mobile-Agent：基于多模态Agent架构的手机智能体 | https://hcqnc.xetlk.com/sl/34N5vR | +| 2024.07.08 | 北京航空航天大学博士生郑耀威 | LLaMA Factory：从预训练到RLHF，大模型高效训练框架 | https://hcqnc.xetlk.com/sl/4xFmvV | +| 2024.06.27 | 浙江大学硕士研究生董玉博 | VillagerAgent：减少幻觉、提高任务分解效率的多智能协作体框架 | [https://hcqnc.xetlk.com/sl/4z6PWd](https://hcqnc.xetlk.com/sl/4z6PWd) | +| 2024.06.17 | 香港大学MMLAB在读博士吴成岳 | LLaMA Pro：扩展Transformer块优化的大型语言模型继续预训练 | https://hcqnc.xetlk.com/sl/XKqHx | +| 2024.06.13 | 北京大学在读博士孟繁续 | PiSSA：收敛快、误差小的大模型参数高效微调方法 | https://hcqnc.xetlk.com/sl/1HYPXz | +| 2024.06.06 | 上海人工智能实验室青年研究员、OpenDriveLab具身智能方向负责人曾嘉博士 | 具身多模态大模型的视觉表征预训练研究 | https://hcqnc.xetlk.com/sl/2k4HMq | +| 2024.05.29 | 南洋理工大学 MMLab 实验室在读博士姜瑜铭 | VideoBooth：文本和图像提示共同驱动的视频生成 | [https://hcqnc.xetlk.com/sl/1ogzQ4](https://hcqnc.xetlk.com/sl/1ogzQ4) | +| 2024.05.24 | 新加坡国立大学Research Fellow倪瑾杰 | Alchemy：混合评测数据集来拟合大语言模型的人类评估 | [https://hcqnc.xetlk.com/sl/gFc4](https://hcqnc.xetlk.com/sl/gFc4) | +| 2024.05.21 | 华南理工大学集合感知与智能实验室博士梁智灏 | 实时渲染 3DGS 中的反走样及逆渲染应用 | [https://hcqnc.xetlk.com/sl/3qpJ8a](https://hcqnc.xetlk.com/sl/3qpJ8a) | +| 2024.05.10 | 3D-VLA第一作者甄昊宇 | 3D-VLA：构建生成式三维具身世界模型 | https://hcqnc.xetlk.com/sl/3axJCI | +| 2024.04.24 | 香港中文大学在读博士李彦玮 | Mini-Gemini：挖掘多模态视觉语言大模型的潜力 | https://hcqnc.xetlk.com/sl/4aYFHd | +| 2024.04.19 | 加州大学洛杉矶分校在读博士洪逸宁 | 从 3D LLM 到 MultiPLY ，3D 具身基础模型的构建 | https://hcqnc.xetlk.com/sl/28OAx8 | +| 2024.04.15 | 清华大学自然语言处理实验室（THUNLP）博士后钱忱 | ChatDev——大语言模型驱动的多智能体协作与演化 | https://hcqnc.xetlk.com/sl/dsPB6 | +| 2024.04.10 | 慕尼黑工业大学视觉计算实验室博士陈振宇 | SceneTex：高质量三维室内场景纹理图生成 | https://hcqnc.xetlk.com/sl/FD3Yf | +| 2024.03.02 | DeepFaceLab(累计60,000 +⭐️)作者小黑兔
InstantID(huggingface space周榜第一)作者王浩帆
剑桥大学计算机系在读博士Andi Zhang
VBench 第一作者、南洋理工大学MMLab在读博士黄子琪 | Sora迷思，AIGC的微积分时刻? | https://hcqnc.xetlk.com/sl/3aRykI | + + +
+ 💬 合作分享 + img +
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分享嘉宾

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郑耀威，北京航空航天大学博士生。以第一作者在ACL、CVPR、AAAI、WWW等国际会议发表多篇论文，担任AAAI、EMNLP、Neural Computation等会议和期刊审稿人。曾获得华为杯数学建模全国一等奖、蓝桥杯全国一等奖、北航榜样、北航博士新生奖学金。大模型训练框架LLaMA Factory作者，GitHub开源项目获得超过2万Stars，受邀至人工智能计算大会、阿里云AI智领者峰会、中国人民大学、智谱AI作大模型主题报告。

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主题提纲

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LLaMA Factory：从预训练到RLHF，大模型高效训练框架 +
1、大模型高效训练现状 +
2、LLaMA Factory 的构建动机与组成模块 +
- 上百种大模型的全栈微调适配原理 +
- LoRA算子优化加速方法 +
- 多种微调Trick集成思路 +
3、LLaMA Factory 部署实践

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成果链接

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Abs：http://arxiv.org/abs/2403.13372 +Code：https://github.com/hiyouga/LLaMA-Factory

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直播时间

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7月8日（周一）19:00 - 20:00

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分享嘉宾

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徐海洋，阿里通义实验室高级算法专家，负责通义多模态大模型mPLUG系列工作，包括基础多模态模型mPLUG/mPLUG-2，多模态对话大模型mPLUG-Owl/Owl2，多模态文档大模型mPLUG-DocOwl，多模态智能体Mobile-Agent等，其中 mPLUG 工作在 VQA 榜单首超人类的成绩。在国际顶级期刊和会议ICML/CVPR/ICCV/ACL/EMNLP/MM/TOIS/IJCAI/AAAI等发表论文30多篇，并担任多个顶级和会议AC/PC/Reviewer。主导参与开源项目mPLUG，X-PLUG，AliceMind，DELTA。

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主题提纲

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Mobile-Agent：基于多模态Agent架构的手机智能体 +
1、多模态 Agent 的研究进展 +
2、基于视觉感知的 Mobile-Agent-V1 +
3、多 Agent 协作的多模态手机智能体 Mobile-Agent-V2 +
4、Mobile-Agent 应用实践

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成果链接

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Abs：[1]https://arxiv.org/abs/2401.16158 [2]https://arxiv.org/abs/2406.01014 +
Code：https://github.com/X-PLUG/MobileAgent

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直播时间

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7月11日（周四）19:00 - 20:00

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分享嘉宾

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余天予，清华大学自然语言处理实验室博士生，发表AAAI、CVPR 等人工智能顶会论文多篇，主要研究方向为多模态大模型。

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主题提纲

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MiniCPM-V：端侧可用的 GPT-4V 级多模态大模型 +
1、端侧多模态大模型的应用挑战 +
2、MiniCPM-V 系列模型与技术解析 +
  - 高效 Scaling Law 和 RLHF-V 等技术实现 +
  - 8B 参数量 MiniCPM-Llama3-V 2.5 +
  - 2B 参数量 MiniCPM-V 2.0 +
3、Demo 演示及 MiniCPM-V 端侧部署实践

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成果链接

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Code：https://github.com/OpenBMB/MiniCPM-V/tree/main

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直播时间

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7月15日（周一）19:00 - 20:00

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20240716125145.png

+

主讲嘉宾

+

程天恒，华中科技大学博士生；2019年获得华中科技大学（HUST）电子信息与通信专业的学士学位；研究兴趣包括计算机视觉、通用物体检测与分割以及多模态视觉模型，在人工智能与计算机视觉的顶级会议上发表学术论文11篇。

+

主题提纲

+

YOLO-World：基于视觉语言模型的实时开放词汇物体检测

+

1、迈向更通用的开放词汇物体检测
+2、YOLO-World：模型设计与大规模数据训练
+3、YOLO-World微调与应用实践
+4、多模态大模型时代的物体检测

+

成果链接

+

Paper：YOLO-World: Real-Time Open-Vocabulary Object Detection
+Abs：https://arxiv.org/abs/2401.17270 +
Code：https://github.com/AILab-CVC/YOLO-World

+

直播时间

+

7月23日（周二）19:00-20:00

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467.png

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主讲嘉宾

+

杨帅，香港科技大学（广州）人工智能方向的博士研究生，导师是陈颖聪博士。他的研究方向是高效深度学习和生成模型，相关成果已发表在ICCV，ICLR，CVPR，ECCV等国际顶级会议中。详见个人主页：https://andysonys.github.io/

+

主题提纲

+

SEED-Story：生成长篇图文故事的多模态大型语言模型

+

1、多模态内容生成的挑战 +
2、SEED-Story 架构及训练方法 +
3、大规模高分辨率数据集 StoryStream +
4、SEED-Story 微调及多模态故事生成实践

+

成果链接

+

Paper：SEED-Story: Multimodal Long Story Generation with Large Language Model +
Abs：https://arxiv.org/abs/2407.08683 +
Code：https://github.com/TencentARC/SEED-Story

+

直播时间

+

7月30日（周二）19:00-20:00

+ +
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+

主讲嘉宾

+

王文海，南京大学博士，香港中文大学博士后，上海人工智能实验室青年科学家，研究方向为视觉基础模型研究，上海人工智能实验室“书生”系列视觉基础模型核心开发者。主要成果发表在顶级期刊和会议TPAMI、CVPR、ICCV、ECCV、ICLR、NeurIPS等共43篇论文，其中19篇为一作/共一/通信。研究成果获得了总共超1.8万次引用，单篇最高引用超3000次。研究成果分别入选CVPR 2023最佳论文，世界人工智能大会青年优秀论文奖，CVMJ 2022最佳论文提名奖，两次入选ESI高被引论文（前1%）和热点论文（前0.1%），6次入选Paper Digest CVPR、ICCV、NeurIPS、ECCV年度十大最具影响力论文，一次入选Zeta Alpha 2022年百篇最高引AI论文。入选斯坦福大学2023年度全球前2%顶尖科学家，世界人工智能大会云帆奖，CSIG优博提名。担任CSIG VI编委，IJCAI 2021的高级程序委员会委员，以及TPAMI、IJCV、CVPR、ICCV、ECCV等多个顶级国际会议/期刊的程序委员会委员/审稿人。

+

主题提纲

+

InternVL 2.0：通过渐进式策略扩展开源多模态大模型的性能边界

+

1、从LLM到VLLM，多模态大模型的基本原理和技术 +
2、如何利用开源套件构建强大的多模态大模型 +
3、基于渐进式对齐训练策略实现的视觉基础模型 +
4、开源、闭源模型能力探讨及InternVL 2.0 的使用

+

成果链接

+

Code：https://github.com/OpenGVLab/InternVL

+

直播时间

+

7月30日（周二）19:00-20:00

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