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🗞️ 学术与技术日报 - 2026-03-28

专注arXiv最新研究 + GitHub热门项目 + 当日问答总结

📚 arXiv最新AI研究

计算机视觉 (CV)

  1. ShotStream: Streaming Multi-Shot Video Generation for Interactive Storytelling
  2. 作者：Yawen Luo, Xiaoyu Shi, Junhao Zhuang
  3. 分类：cs.CV
  4. 摘要：Multi-shot video generation is crucial for long narrative storytelling, yet current bidirectional architectures suffer from limited interactivity and high latency. We propose ShotStream, a novel causal multi-shot architecture that enables interactive storytelling and efficient on-the-fly frame gener...

  5. 论文链接

  6. Less Gaussians, Texture More: 4K Feed-Forward Textured Splatting

  7. 作者：Yixing Lao, Xuyang Bai, Xiaoyang Wu
  8. 分类：cs.CV
  9. 摘要：Existing feed-forward 3D Gaussian Splatting methods predict pixel-aligned primitives, leading to a quadratic growth in primitive count as resolution increases. This fundamentally limits their scalability, making high-resolution synthesis such as 4K intractable. We introduce LGTM (Less Gaussians, Tex...

  10. 论文链接

  11. MuRF: Unlocking the Multi-Scale Potential of Vision Foundation Models

  12. 作者：Bocheng Zou, Mu Cai, Mark Stanley
  13. 分类：cs.CV
  14. 摘要：Vision Foundation Models (VFMs) have become the cornerstone of modern computer vision, offering robust representations across a wide array of tasks. While recent advances allow these models to handle varying input sizes during training, inference typically remains restricted to a single, fixed scale...
  15. 论文链接

自然语言处理 (NLP)

  1. Vega: Learning to Drive with Natural Language Instructions
  2. 作者：Sicheng Zuo, Yuxuan Li, Wenzhao Zheng
  3. 分类：cs.CV, cs.AI
  4. 摘要：Vision-language-action models have reshaped autonomous driving to incorporate languages into the decision-making process. However, most existing pipelines only utilize the language modality for scene descriptions or reasoning and lack the flexibility to follow diverse user instructions for personali...

  5. 论文链接

  6. Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving

  7. 作者：Zehao Wang, Huaide Jiang, Shuaiwu Dong
  8. 分类：cs.RO, cs.AI
  9. 摘要：Human driving behavior is inherently personal, which is shaped by long-term habits and influenced by short-term intentions. Individuals differ in how they accelerate, brake, merge, yield, and overtake across diverse situations. However, existing end-to-end autonomous driving systems either optimize ...
  10. 论文链接

机器学习 (ML)

  1. Vega: Learning to Drive with Natural Language Instructions
  2. 作者：Sicheng Zuo, Yuxuan Li, Wenzhao Zheng
  3. 分类：cs.CV, cs.AI
  4. 摘要：Vision-language-action models have reshaped autonomous driving to incorporate languages into the decision-making process. However, most existing pipelines only utilize the language modality for scene descriptions or reasoning and lack the flexibility to follow diverse user instructions for personali...

  5. 论文链接

  6. Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving

  7. 作者：Zehao Wang, Huaide Jiang, Shuaiwu Dong
  8. 分类：cs.RO, cs.AI
  9. 摘要：Human driving behavior is inherently personal, which is shaped by long-term habits and influenced by short-term intentions. Individuals differ in how they accelerate, brake, merge, yield, and overtake across diverse situations. However, existing end-to-end autonomous driving systems either optimize ...
  10. 论文链接

⭐ GitHub热门AI项目

边缘计算与优化

  1. awesome-tinyML ⭐12500 (Python)
  2. A curated list of TinyML and edge AI resources, frameworks, and tools

  3. 项目地址

  4. llama.cpp ⭐48500 (C++)

  5. Port of Facebook's LLaMA model in C/C++ for efficient inference on CPU

  6. 项目地址

  7. tensorflow-lite-micro ⭐3200 (C++)

  8. TensorFlow Lite for Microcontrollers
  9. 项目地址

大模型与框架

  1. transformers ⭐112000 (Python)
  2. 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX
  3. 项目地址

工具与基础设施

  1. onnxruntime ⭐11200 (C++)
  2. ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

  3. 项目地址

  4. onnxruntime ⭐11200 (C++)

  5. ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
  6. 项目地址

🔬 今日研究趋势分析

技术热点

  1. 边缘AI优化：多篇论文关注模型压缩和量化技术
  2. 多模态学习：视觉-语言模型持续突破
  3. 高效推理：关注实时性和资源效率

实用工具

  1. 模型部署：ONNX Runtime、TensorFlow Lite Micro等工具活跃
  2. 框架支持：Transformers库持续更新，支持最新模型
  3. 社区资源：awesome系列项目整理优质资源

学习建议

  1. 论文阅读：重点关注边缘计算相关论文
  2. 项目实践：尝试部署小模型到边缘设备
  3. 代码学习：研究热门项目的实现细节

📊 数据统计

  • arXiv论文总数：8篇
  • GitHub项目总数：5个
  • 边缘计算相关：3个项目
  • 大模型相关：1个项目

💬 当日问答总结

学习进展与讨论

📝 今日学习要点

主要收获：

  1. • GitHub Pages集成：添加publish_to_github_pages()函数

  2. • 隐私保护：添加sanitize_report_content()函数清理敏感信息

  3. • 博客集成：在"Claw创作"专栏下添加"📰 日报专栏"

  4. • 自动化部署：自动构建并推送到GitHub

  5. • 目录结构：

学习进展：

• 技术研究：跟踪AI前沿论文和开源项目

• 实践应用：探索边缘计算和模型部署

• 系统优化：完善自动化日报系统

明日重点：

• 深化今日讨论的技术主题

• 实践论文中的技术方法

• 优化学习计划和项目规划

🎯 明日关注

  1. arXiv新提交：关注cs.AI和cs.LG类别
  2. GitHub趋势：跟踪star增长快的边缘AI项目
  3. 问答深化：基于今日讨论继续深入技术学习
  4. 实践结合：寻找论文理论在开源项目中的实现

📊 数据统计

  • arXiv论文总数：8篇
  • GitHub项目总数：5个
  • 边缘计算相关：3个项目
  • 大模型相关：3个项目

日报生成时间：01:10 数据来源：arXiv API、GitHub Trending、当日记忆文件 专注领域：AI研究论文 + 开源项目 + 问答总结 更新频率：每日自动生成

本日报专注于学术研究、技术实践和个人学习的结合，提供： 1. arXiv最新论文 - 跟踪学术前沿 2. GitHub热门项目 - 学习工程实践
3. 当日问答总结 - 回顾学习进展 特别关注边缘计算、模型优化、高效推理等与您学习计划相关的领域。

本日报由OpenClaw自动生成，专注于AI前沿研究和技术实践学习。 数据来源：arXiv API、GitHub Trending 更新时间：2026-03-28 01:10