2025.03.21 | 蒸馏提升超分辨率效率,优化推理减少计算负担。

2025.03.21 | 蒸馏提升超分辨率效率,优化推理减少计算负担。

11分钟 ·
播放数134
·
评论数0

本期的 15 篇论文如下:

00:23 🖼 One-Step Residual Shifting Diffusion for Image Super-Resolution via Distillation(基于蒸馏的单步残差转移扩散超分辨率)

01:01 🤔 Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models(停止过度思考:大型语言模型高效推理综述)

01:38 🚀 Unleashing Vecset Diffusion Model for Fast Shape Generation(释放Vecset扩散模型以实现快速形状生成)

02:18 🤖 Survey on Evaluation of LLM-based Agents(基于大型语言模型(LLM)的智能体评估方法综述)

02:56 🎨 DiffMoE: Dynamic Token Selection for Scalable Diffusion Transformers(DiffMoE:用于可扩展扩散Transformer的动态Token选择)

03:33 🤖 Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning(Cosmos-Reason1:从物理常识到具身推理)

04:14 🖼 Scale-wise Distillation of Diffusion Models(扩散模型的尺度wise蒸馏)

04:54 🗜 Plug-and-Play 1.x-Bit KV Cache Quantization for Video Large Language Models(面向视频大语言模型的即插即用1.x-Bit KV缓存量化)

05:36 🧮 MathFusion: Enhancing Mathematic Problem-solving of LLM through Instruction Fusion(MathFusion:通过指令融合增强大型语言模型解决数学问题的能力)

06:17 🖼 InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity(无限的你:在保留身份的同时进行灵活的照片重塑)

06:56 🎮 JARVIS-VLA: Post-Training Large-Scale Vision Language Models to Play Visual Games with Keyboards and Mouse(JARVIS-VLA:通过后训练大规模视觉语言模型,使用键盘和鼠标玩视觉游戏)

07:41 🧠 CaKE: Circuit-aware Editing Enables Generalizable Knowledge Learners(CaKE:电路感知编辑实现通用知识学习器)

08:26 🖼 Ultra-Resolution Adaptation with Ease(简易的超分辨率自适应)

09:04 🎨 Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts(专家竞赛:一种灵活的路由策略,用于扩展具有混合专家模型的扩散Transformer)

09:48 🎬 MagicMotion: Controllable Video Generation with Dense-to-Sparse Trajectory Guidance(MagicMotion:基于稠密到稀疏轨迹引导的可控视频生成)

【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