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      <title>Don’t stop early: Case-folding source code at memory speed</title>
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      <pubDate>Sat, 01 Aug 2026 00:00:00 +0800</pubDate>
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      <description>How a branch-free loop and byte-space arithmetic let GitHub case-fold every byte of code search at &gt;45 GiB/s on a single core. The post Don’t stop early: Case-folding source code at memory speed appeared first on The Git｜来源：GitHub Blog</description>
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      <title>Ten advances in mathematics and theoretical computer science</title>
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      <pubDate>Sat, 01 Aug 2026 08:00:00 +0800</pubDate>
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      <description>OpenAI shares new results on long-standing open problems in mathematics and theoretical computer science, including advances in geometry, cryptography, and complexity.｜来源：OpenAI News</description>
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      <title>Scaling Kubernetes pods with KEDA based on Amazon SQS queue depth</title>
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      <description>In event-driven Kubernetes architectures, CPU and memory utilization often fail to reflect real system pressure. A worker pod may sit idle from a CPU perspective while thousands of messages pile up in an Amazon SQS queue｜来源：CNCF Blog</description>
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      <title>TokTier: Exact Stateful Tokenization for Agentic LLM Serving</title>
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      <description>LLM serving systems cache prompt KV state, yet most front ends still re-tokenize the full request text on every call. The cost lands on coding agents, which resubmit a long transcript after each small tool result, and re｜来源：arXiv AI / ML / NLP</description>
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      <title>Advancing responsible AI across Europe</title>
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      <pubDate>Fri, 31 Jul 2026 23:00:00 +0800</pubDate>
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      <description>OpenAI shares how its safety, security, transparency, and provenance practices support responsible AI governance in Europe. The work will continue as the EU AI Act advances.｜来源：OpenAI News</description>
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      <title>ExtractBench: A Benchmark for Schema-Guided Enterprise Document Extraction</title>
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      <pubDate>Sat, 01 Aug 2026 01:55:58 +0800</pubDate>
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      <description>Enterprise workflows increasingly rely on agents for \emph{schema-guided extraction}: given a document and a user-defined schema, the agent faithfully follows the schema to produce the correct output with source evidence｜来源：arXiv AI / ML / NLP</description>
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      <title>Building abundant intelligence</title>
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      <pubDate>Fri, 31 Jul 2026 23:00:00 +0800</pubDate>
      <category>AI 模型</category>
      <description>A full-stack approach to making advanced AI more capable, more affordable, and more widely useful.｜来源：OpenAI News</description>
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      <title>Differentially Private Nonparametric Modal Learning with Applications to Regression and Clustering</title>
      <link>https://arxiv.org/abs/2607.29675v1</link>
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      <pubDate>Sat, 01 Aug 2026 01:55:02 +0800</pubDate>
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      <description>Density modes provide a localized and interpretable summary of multimodal distributions, but their estimation under rigorous differential privacy constraints remains largely unexplored. We study differentially private re｜来源：arXiv AI / ML / NLP</description>
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