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本期的 8 篇论文如下:
[00:30] 🧠 HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs(华佗GPT-o1:迈向医学复杂推理的大语言模型)
[01:16] 🧭 Orient Anything: Learning Robust Object Orientation Estimation from Rendering 3D Models(定向万物:从渲染3D模型中学习鲁棒的物体方向估计)
[02:03] 🔍 Task Preference Optimization: Improving Multimodal Large Language Models with Vision Task Alignment(任务偏好优化:通过视觉任务对齐提升多模态大语言模型)
[02:50] 🧬 The Superposition of Diffusion Models Using the Itô Density Estimator(使用Itô密度估计器进行扩散模型的叠加)
[03:33] 🎨 From Elements to Design: A Layered Approach for Automatic Graphic Design Composition(从元素到设计:一种分层的自动图形设计构图方法)
[04:16] 🛡 Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging(通过预调优和后调优模型合并保护微调的大型语言模型)
[04:56] 📊 SBS Figures: Pre-training Figure QA from Stage-by-Stage Synthesized Images(SBS图表:从分阶段合成图像预训练图表问答)
[05:47] 🎥 VideoMaker: Zero-shot Customized Video Generation with the Inherent Force of Video Diffusion Models(VideoMaker:利用视频扩散模型的内在力量实现零样本定制视频生成)
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您还可以在以下平台找到我们,获得播客内容以外更多信息
小红书: AI速递
本期的 8 篇论文如下:
[00:30] 🧠 HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs(华佗GPT-o1:迈向医学复杂推理的大语言模型)
[01:16] 🧭 Orient Anything: Learning Robust Object Orientation Estimation from Rendering 3D Models(定向万物:从渲染3D模型中学习鲁棒的物体方向估计)
[02:03] 🔍 Task Preference Optimization: Improving Multimodal Large Language Models with Vision Task Alignment(任务偏好优化:通过视觉任务对齐提升多模态大语言模型)
[02:50] 🧬 The Superposition of Diffusion Models Using the Itô Density Estimator(使用Itô密度估计器进行扩散模型的叠加)
[03:33] 🎨 From Elements to Design: A Layered Approach for Automatic Graphic Design Composition(从元素到设计:一种分层的自动图形设计构图方法)
[04:16] 🛡 Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging(通过预调优和后调优模型合并保护微调的大型语言模型)
[04:56] 📊 SBS Figures: Pre-training Figure QA from Stage-by-Stage Synthesized Images(SBS图表:从分阶段合成图像预训练图表问答)
[05:47] 🎥 VideoMaker: Zero-shot Customized Video Generation with the Inherent Force of Video Diffusion Models(VideoMaker:利用视频扩散模型的内在力量实现零样本定制视频生成)
【关注我们】
您还可以在以下平台找到我们,获得播客内容以外更多信息
小红书: AI速递