From e70c45b381a6c3ea34e36ee70051dd794fc07445 Mon Sep 17 00:00:00 2001 From: bojunc <316231662@qq.com> Date: Fri, 27 Feb 2026 23:38:47 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E7=94=9F=E6=88=90=E4=B8=AD=E8=8B=B1?= =?UTF-8?q?=E6=96=87=E4=B8=A4=E4=B8=AA=E7=89=88=E6=9C=AC=E7=9A=84=E7=AE=80?= =?UTF-8?q?=E6=8A=A5?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 新增 generateMarkdownZH 和 generateMarkdownEN 函数 - 输出文件改为 YYYY-MM-DD_zh.md 和 YYYY-MM-DD_en.md - 英文版使用英文标题和分类名称 --- cache/seen_urls.json | 2 +- daily/2026-02-27_en.md | 57 +++++++++++++++++++ daily/2026-02-27_zh.md | 57 +++++++++++++++++++ skill/ai-news-collector/collect.js | 89 ++++++++++++++++++++++++++---- 4 files changed, 193 insertions(+), 12 deletions(-) create mode 100644 daily/2026-02-27_en.md create mode 100644 daily/2026-02-27_zh.md diff --git a/cache/seen_urls.json b/cache/seen_urls.json index 7fc0e1b..61aeb42 100644 --- a/cache/seen_urls.json +++ b/cache/seen_urls.json @@ -1,5 +1,5 @@ { - "lastUpdate": "2026-02-27T15:33:33.096Z", + "lastUpdate": "2026-02-27T15:38:30.698Z", "urls": [ "http://arxiv.org/abs/2602.23360v1", "http://arxiv.org/abs/2602.23359v1", diff --git a/daily/2026-02-27_en.md b/daily/2026-02-27_en.md new file mode 100644 index 0000000..beea07b --- /dev/null +++ b/daily/2026-02-27_en.md @@ -0,0 +1,57 @@ +# AI Daily Brief - 2026-02-27 + +> Collected at: 2/27/2026, 11:38:30 PM +> Total items: 131 + +## 🔥 Top 10 Highlights + +1. [sponsors/muratcankoylan](https://github.com/sponsors/muratcankoylan) - **GitHub Trending** + > A comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimi... + +2. [login?return_to=%2Fruvnet%2Fclaude-flow](https://github.com/login?return_to=%2Fruvnet%2Fclaude-flow) - **GitHub Trending** + > 🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversation... + +3. [Search More, Think Less: Rethinking Long-Horizon Agentic Search for Efficiency and Generalization](https://huggingface.co/papers/2602.22675) - **Hugging Face** + > Recent deep research agents primarily improve performance by scaling reasoning depth, but this leads to high inference cost and latency in search-inte... + +4. [AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning](https://huggingface.co/papers/2602.23258) - **Hugging Face** + > While Multi-Agent Systems (MAS) excel in complex reasoning, they suffer from the cascading impact of erroneous information generated by individual par... + +5. [Accelerating Diffusion via Hybrid Data-Pipeline Parallelism Based on Conditional Guidance Scheduling](https://huggingface.co/papers/2602.21760) - **Hugging Face** + > Diffusion models have achieved remarkable progress in high-fidelity image, video, and audio generation, yet inference remains computationally expensiv... + +6. [Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization](https://huggingface.co/papers/2602.23008) - **Hugging Face** + > Exploration remains the key bottleneck for large language model agents trained with reinforcement learning. While prior methods exploit pretrained kno... + +7. [login?return_to=%2Fruvnet%2Fwifi-densepose](https://github.com/login?return_to=%2Fruvnet%2Fwifi-densepose) - **GitHub Trending** + > Production-ready implementation of InvisPose - a revolutionary WiFi-based dense human pose estimation system that enables real-time full-body tracking... + +8. [login?return_to=%2Fbytedance%2Fdeer-flow](https://github.com/login?return_to=%2Fbytedance%2Fdeer-flow) - **GitHub Trending** + > An open-source SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skills and subagents, it handles d... + +9. [login?return_to=%2Fmoonshine-ai%2Fmoonshine](https://github.com/login?return_to=%2Fmoonshine-ai%2Fmoonshine) - **GitHub Trending** + > Fast and accurate automatic speech recognition (ASR) for edge devices + +10. [sponsors/obra](https://github.com/sponsors/obra) - **GitHub Trending** + > An agentic skills framework & software development methodology that works. + +## 📂 Categories + +### Agent Frameworks + +- [Toward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading Tasks](http://arxiv.org/abs/2602.23330v1) - arXiv +- [AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning](http://arxiv.org/abs/2602.23258v1) - arXiv + +### AI Infrastructure / Inference Optimization + +- [Bitwise Systolic Array Architecture for Runtime-Reconfigurable Multi-precision Quantized Multiplication on Hardware Accelerators](http://arxiv.org/abs/2602.23334v1) - arXiv +- [Invariant Transformation and Resampling based Epistemic-Uncertainty Reduction](http://arxiv.org/abs/2602.23315v1) - arXiv +- [Agency and Architectural Limits: Why Optimization-Based Systems Cannot Be Norm-Responsive](http://arxiv.org/abs/2602.23239v1) - arXiv +- [InnerQ: Hardware-aware Tuning-free Quantization of KV Cache for Large Language Models](http://arxiv.org/abs/2602.23200v1) - arXiv +- [Assessing Deanonymization Risks with Stylometry-Assisted LLM Agent](http://arxiv.org/abs/2602.23079v1) - arXiv +- [Rejection Mixing: Fast Semantic Propagation of Mask Tokens for Efficient DLLM Inference](http://arxiv.org/abs/2602.22868v1) - arXiv +- [Differentiable Zero-One Loss via Hypersimplex Projections](http://arxiv.org/abs/2602.23336v1) - arXiv +- [FairQuant: Fairness-Aware Mixed-Precision Quantization for Medical Image Classification](http://arxiv.org/abs/2602.23192v1) - arXiv + +--- +*Generated by AINewsCollector* diff --git a/daily/2026-02-27_zh.md b/daily/2026-02-27_zh.md new file mode 100644 index 0000000..8a8780c --- /dev/null +++ b/daily/2026-02-27_zh.md @@ -0,0 +1,57 @@ +# AI Daily Brief - 2026-02-27 + +> 采集时间: 2026/2/27 23:38:30 +> 总条目: 131 + +## 🔥 Top 10 重要消息 + +1. [sponsors/muratcankoylan](https://github.com/sponsors/muratcankoylan) - **GitHub Trending** + > A comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimi... + +2. [login?return_to=%2Fruvnet%2Fclaude-flow](https://github.com/login?return_to=%2Fruvnet%2Fclaude-flow) - **GitHub Trending** + > 🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversation... + +3. [Search More, Think Less: Rethinking Long-Horizon Agentic Search for Efficiency and Generalization](https://huggingface.co/papers/2602.22675) - **Hugging Face** + > Recent deep research agents primarily improve performance by scaling reasoning depth, but this leads to high inference cost and latency in search-inte... + +4. [AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning](https://huggingface.co/papers/2602.23258) - **Hugging Face** + > While Multi-Agent Systems (MAS) excel in complex reasoning, they suffer from the cascading impact of erroneous information generated by individual par... + +5. [Accelerating Diffusion via Hybrid Data-Pipeline Parallelism Based on Conditional Guidance Scheduling](https://huggingface.co/papers/2602.21760) - **Hugging Face** + > Diffusion models have achieved remarkable progress in high-fidelity image, video, and audio generation, yet inference remains computationally expensiv... + +6. [Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization](https://huggingface.co/papers/2602.23008) - **Hugging Face** + > Exploration remains the key bottleneck for large language model agents trained with reinforcement learning. While prior methods exploit pretrained kno... + +7. [login?return_to=%2Fruvnet%2Fwifi-densepose](https://github.com/login?return_to=%2Fruvnet%2Fwifi-densepose) - **GitHub Trending** + > Production-ready implementation of InvisPose - a revolutionary WiFi-based dense human pose estimation system that enables real-time full-body tracking... + +8. [login?return_to=%2Fbytedance%2Fdeer-flow](https://github.com/login?return_to=%2Fbytedance%2Fdeer-flow) - **GitHub Trending** + > An open-source SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skills and subagents, it handles d... + +9. [login?return_to=%2Fmoonshine-ai%2Fmoonshine](https://github.com/login?return_to=%2Fmoonshine-ai%2Fmoonshine) - **GitHub Trending** + > Fast and accurate automatic speech recognition (ASR) for edge devices + +10. [sponsors/obra](https://github.com/sponsors/obra) - **GitHub Trending** + > An agentic skills framework & software development methodology that works. + +## 📂 分类汇总 + +### Agent 框架 + +- [Toward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading Tasks](http://arxiv.org/abs/2602.23330v1) - arXiv +- [AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning](http://arxiv.org/abs/2602.23258v1) - arXiv + +### AI 基础设施 / 推理优化 + +- [Bitwise Systolic Array Architecture for Runtime-Reconfigurable Multi-precision Quantized Multiplication on Hardware Accelerators](http://arxiv.org/abs/2602.23334v1) - arXiv +- [Invariant Transformation and Resampling based Epistemic-Uncertainty Reduction](http://arxiv.org/abs/2602.23315v1) - arXiv +- [Agency and Architectural Limits: Why Optimization-Based Systems Cannot Be Norm-Responsive](http://arxiv.org/abs/2602.23239v1) - arXiv +- [InnerQ: Hardware-aware Tuning-free Quantization of KV Cache for Large Language Models](http://arxiv.org/abs/2602.23200v1) - arXiv +- [Assessing Deanonymization Risks with Stylometry-Assisted LLM Agent](http://arxiv.org/abs/2602.23079v1) - arXiv +- [Rejection Mixing: Fast Semantic Propagation of Mask Tokens for Efficient DLLM Inference](http://arxiv.org/abs/2602.22868v1) - arXiv +- [Differentiable Zero-One Loss via Hypersimplex Projections](http://arxiv.org/abs/2602.23336v1) - arXiv +- [FairQuant: Fairness-Aware Mixed-Precision Quantization for Medical Image Classification](http://arxiv.org/abs/2602.23192v1) - arXiv + +--- +*Generated by AINewsCollector* diff --git a/skill/ai-news-collector/collect.js b/skill/ai-news-collector/collect.js index 6646ea4..6510715 100644 --- a/skill/ai-news-collector/collect.js +++ b/skill/ai-news-collector/collect.js @@ -168,11 +168,7 @@ function sortItems(items, topics) { // ============ 输出模块 ============ -function generateMarkdown(items, topCount, topics) { - const date = new Date().toLocaleDateString('zh-CN', { - year: 'numeric', month: '2-digit', day: '2-digit', timeZone: 'Asia/Shanghai' - }).replace(/\//g, '-'); - +function generateMarkdownZH(items, topCount, topics, date) { const top10 = items.slice(0, topCount); let md = `# AI Daily Brief - ${date}\n\n`; @@ -206,7 +202,63 @@ function generateMarkdown(items, topCount, topics) { md += `---\n*Generated by AINewsCollector*\n`; - return { md, date }; + return md; +} + +function generateMarkdownEN(items, topCount, topics, date) { + const top10 = items.slice(0, topCount); + + let md = `# AI Daily Brief - ${date}\n\n`; + md += `> Collected at: ${new Date().toLocaleString('en-US', { timeZone: 'Asia/Shanghai' })}\n`; + md += `> Total items: ${items.length}\n\n`; + + md += `## 🔥 Top ${topCount} Highlights\n\n`; + for (let i = 0; i < top10.length; i++) { + const item = top10[i]; + md += `${i + 1}. [${item.title}](${item.url}) - **${item.source}**\n`; + if (item.summary) md += ` > ${item.summary.slice(0, 150)}${item.summary.length > 150 ? '...' : ''}\n`; + md += '\n'; + } + + md += `## 📂 Categories\n\n`; + + // 英文分类名称映射 + const topicNamesEN = { + 'AI 编程工具 / Code Agent': 'AI Coding Tools / Code Agent', + 'Agent 框架': 'Agent Frameworks', + 'AI 基础设施 / 推理优化': 'AI Infrastructure / Inference Optimization' + }; + + for (const topic of topics) { + const topicItems = items.filter(item => { + const text = `${item.title} ${item.summary}`.toLowerCase(); + return topic.keywords.some(k => text.includes(k.toLowerCase())); + }).filter(item => !top10.includes(item)); + + if (topicItems.length > 0) { + const topicNameEN = topicNamesEN[topic.name] || topic.name; + md += `### ${topicNameEN}\n\n`; + for (const item of topicItems.slice(0, 10)) { + md += `- [${item.title}](${item.url}) - ${item.source}\n`; + } + md += '\n'; + } + } + + md += `---\n*Generated by AINewsCollector*\n`; + + return md; +} + +function generateMarkdown(items, topCount, topics) { + const date = new Date().toLocaleDateString('zh-CN', { + year: 'numeric', month: '2-digit', day: '2-digit', timeZone: 'Asia/Shanghai' + }).replace(/\//g, '-'); + + const md_zh = generateMarkdownZH(items, topCount, topics, date); + const md_en = generateMarkdownEN(items, topCount, topics, date); + + return { md_zh, md_en, date }; } // ============ 主流程 ============ @@ -245,19 +297,34 @@ async function main() { allItems = sortItems(allItems, config.topics); - const { md, date } = generateMarkdown(allItems, config.output.topCount, config.topics); + const { md_zh, md_en, date } = generateMarkdown(allItems, config.output.topCount, config.topics); if (!fs.existsSync(DAILY_DIR)) fs.mkdirSync(DAILY_DIR, { recursive: true }); - const outputPath = path.join(DAILY_DIR, `${date}.md`); - fs.writeFileSync(outputPath, md); - console.log(`📝 简报已保存: ${outputPath}\n`); + + // 保存中文版 + const outputPathZH = path.join(DAILY_DIR, `${date}_zh.md`); + fs.writeFileSync(outputPathZH, md_zh); + console.log(`📝 中文简报: ${outputPathZH}\n`); + + // 保存英文版 + const outputPathEN = path.join(DAILY_DIR, `${date}_en.md`); + fs.writeFileSync(outputPathEN, md_en); + console.log(`📝 英文简报: ${outputPathEN}\n`); const cacheData = { lastUpdate: new Date().toISOString(), urls: Array.from(seenUrls).slice(-5000) }; fs.writeFileSync(CACHE_PATH, JSON.stringify(cacheData, null, 2)); console.log('✅ 采集完成!\n'); - return { success: true, outputPath, date, itemCount: allItems.length, content: md }; + return { + success: true, + outputPathZH, + outputPathEN, + date, + itemCount: allItems.length, + content_zh: md_zh, + content_en: md_en + }; } if (require.main === module) {