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2026-09-03
日期、来源、摘要、可信度和合规说明均来自通过完整审核门禁与哈希校验的每日公开快照；周报发布后由同期完整发布包接管。
RSS 公开元数据：Fine-tuning a 350M Model for Better Structured Outputs in 100 GRPO Steps。Update on GitHub:last-child]:mb-0"> This guide is a fully public, inexpensive recipe for making a small model substantially better at structured-output compliance. We fine-tune LFM2.5-350M with Group Relative Policy Optimization (GRPO) using the TRL library and evaluate it on the IFStruct benchmark. The full run takes around 500 samples and 100 training steps, small enough for a free-tier Colab or Kaggle GPU, and is available on GitHub. The results show that even a light fine-tuning procedure improves performance from 22.6% to 29.7% on the IFStruct benchmark. Structured output is one of the most common real-w... 来源：RSSHub。RSSHub public RSS metadata only; no full article body stored. Trafilatura public URL extraction; stored short extract only, no full article body, cookies, or headers.
打开公开来源RSS 公开元数据：Training a coding model to paint watercolours with TRL and OpenEnv。Update on GitHub:last-child]:mb-0"> On 23 August, Surya Narreddi posted a beautiful video of watercolours painted by a language model. The model writes JavaScript through p5.brush, a library that "adds natural drawing tools to p5.js". The video went viral fast, over 1.5M views at the time of writing. The video came with a blog post explaining the training behind an earlier and narrower stage of the project, close-up flowers rather than the full compositions in the video, sadly without open artifacts yet. His site says a full technical report is coming, so ensure you follow him. The original idea is his, coming from... 来源：RSSHub。RSSHub public RSS metadata only; no full article body stored. Trafilatura public URL extraction; stored short extract only, no full article body, cookies, or headers.
打开公开来源RSS 公开元数据：NeoMME: an efficient Multimodal-native and Multilingual Encoder。:last-child]:mb-0"> TL;DR We introduce NeoMME, a family of 260M and 800M multilingual multimodal encoders. Unlike many generative visual language models, NeoMME does not use a separate pretrained vision tower or a causal language model. A single bidirectional Transformer processes both text tokens and raw image patches, and we train the entire model from scratch with a masked discrete-diffusion objective. We fine-tuned NeoMME for visual document retrieval using ColPali's page-image approach. NeoMME -Retriever returns dense and late-interaction embeddings in one forward pass. Both model sizes lie on the ViDoRe v3 Paret... 来源：RSSHub。RSSHub public RSS metadata only; no full article body stored. Trafilatura public URL extraction; stored short extract only, no full article body, cookies, or headers.
打开公开来源RSS 公开元数据：Safety overview: GPT-6 Astra。Loading… Share Today, we are releasing GPT‑6 Astra, the most capable model we have ever broadly deployed. Astra is our first model to reach the Critical level of cybersecurity capability under our Preparedness Framework. The most important things to know about the safety of this launch are as follows: GPT‑6 Astra is a significant step up in cyber capabilities and meets our Critical threshold. This means that, with the right tools and access, GPT‑6 Astra can find previously unknown security flaws and develop new ways to exploit them across many well-protected systems without a person guiding each step. Accordingly, we significantly strengthened our prot... 来源：RSSHub。RSSHub public RSS metadata only; no full article body stored.
打开公开来源RSS 公开元数据：Give Your Coding Agents a Memory You Own。Update on GitHub:last-child]:mb-0"> I work across several machines, and I switch coding agents depending on the task. Every one of them meets my projects as a stranger. The reasoning from “last Tuesday” disappears when the session ends. Each new agent, on each new host, starts from zero. Earlier this year, Software Forgets: Agent Traces Are the Memory made the case that coding agents already produce the record we keep losing. As they search a codebase, try approaches, hit errors, read documentation, and change direction, they leave behind a dense account of not just what changed, but why. While the diagnosis is correct, traces are only pote... 来源：RSSHub。RSSHub public RSS metadata only; no full article body stored. Trafilatura public URL extraction; stored short extract only, no full article body, cookies, or headers.
打开公开来源RSS 公开元数据：Daybreak for Frontline Defenders: $1B to protect essential services。Loading… Share $1 billion for frontline defenders $1 billion for frontline defenders Expanded access to frontier AI and hands-on support for defenders New partnerships with defenders Work with us $1 billion for frontline defenders Expanded access to frontier AI and hands-on support for defenders New partnerships with defenders Work with us Today OpenAI is introducing Daybreak for Frontline Defenders, a new global initiative to help frontline defenders use frontier AI cyber capabilities to protect essential services in the United States and around the world. The initiative includes: A $1 billion global commitment t... 来源：RSSHub。RSSHub public RSS metadata only; no full article body stored.
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