Standard RAG pipelines treat documents as flat strings of text. They use "fixed-size chunking" (cutting a document every 500 ...

Once data is loaded into Excel, Copilot allows users to ask questions in natural language instead of building new formulas.

To complete the above system, the author’s main research work includes: 1) Office document automation based on python-docx. 2) Use the Django framework to develop the website.

点击上方“Deephub Imba”,关注公众号,好文章不错过 !这篇文章从头实现 LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architectures。需要说明的是，这里写的是一个简洁的最小化训练脚本，目标是了解 JEPA 的本质：对同一文本创建两个视图，预测被遮蔽片段的嵌入，用表示对齐损失来训练。本文的目标是 ...

I'm not a programmer, but I tried four vibe coding tools to see if I could build anything at all on my own. Here's what I did and did not accomplish.

I tried four vibe-coding tools, including Cursor and Replit, with no coding background. Here's what worked (and what didn't).

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Say goodbye to source maps and compilation delays. By treating types as whitespace, modern runtimes are unlocking a “no-build” TypeScript that keeps stack traces accurate and workflows clean.

自2025年初DeepSeek R1模型发布以来，强化学习（RL）在大型语言模型（LLM）的后训练范式中受到越来越多的关注，R1的突破性在于引入了可验证奖励强化学习（RLVR），通过构建数学题、代码谜题等自动验证环境，使模型在客观奖励信号的驱动下，自发地演化出与人类推理策略高度相似的思维方式。