{
  "title": "Daily Research Brief 2026-05-13",
  "url": "/en/posts/research-brief-2026-05-13/",
  "permalink": "https://hackcv.com/en/posts/research-brief-2026-05-13/",
  "date": "2026-05-13",
  "lastmod": "2026-05-13",
  "author": "",
  "description": "Daily research brief — AI / LLM / Agent / Computer Vision / Audio-Video / Engineering",
  "categories": ["Research Brief"],
  "tags": ["AI","LLM","Agent","Computer Vision","Audio-Video","Engineering","Daily Brief"],
  "cover": "https://picsum.photos/seed/daily-research-brief-2026-05-13/1200/675",
  "readingTime": 1,
  "wordCount": 140,
  "content": "\u003ch1 id=\"daily-research-brief-2026-05-13\"\u003eDaily Research Brief 2026-05-13\u003c/h1\u003e\n\u003cp\u003e📊 Token usage: estimated from retrieval and writing scale.\u003c/p\u003e\n\u003cp\u003eCovers the latest AI research, open source and industry moves, updated daily.\u003c/p\u003e\n\u003chr\u003e\n\u003ch2 id=\"editors-note\"\u003eEditor\u0026rsquo;s Note\u003c/h2\u003e\n\u003cp\u003eA 26M-parameter model achieved on-device function calling; AI \u0026lsquo;self-replication\u0026rsquo; success jumped 13x to 81%; three ministries issued top-level agent policy; DeepSeek V4 broke the million-token context window; Anthropic crossed $900B valuation, eyeing an October IPO.\u003c/p\u003e\n\u003ch2 id=\"1-latest-arxiv-papers\"\u003e1. Latest arXiv Papers\u003c/h2\u003e\n\u003col\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eTBA: Decoupling LLM RL Training — 50x Speedup\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2503.18929\"\u003ehttps://arxiv.org/abs/2503.18929\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eIntentGrasp: The First Comprehensive \u0026lsquo;Intent Understanding\u0026rsquo; Benchmark\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2605.06832\"\u003ehttps://arxiv.org/abs/2605.06832\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003ePRISM: A Three-Stage Multimodal Model Training Framework\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2604.28123\"\u003ehttps://arxiv.org/abs/2604.28123\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eOPUS: Theory-Guided Pretraining Data Selection for LLMs\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2602.05400\"\u003ehttps://arxiv.org/abs/2602.05400\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eLLaVA-CKD: Cascaded Knowledge Distillation for Vision-Language Models\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2605.10641\"\u003ehttps://arxiv.org/abs/2605.10641\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eContinual Factual Knowledge Acquisition in Language Models\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2605.10640\"\u003ehttps://arxiv.org/abs/2605.10640\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eConfidence-Guided Diffusion Augmentation for Low-Resource Settings\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2605.10916\"\u003ehttps://arxiv.org/abs/2605.10916\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eFast Rates for Offline Contextual Bandits with Function Approximation\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2605.10639\"\u003ehttps://arxiv.org/abs/2605.10639\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n",
  "summary": "Daily Research Brief 2026-05-13 📊 Token usage: estimated from retrieval and writing scale.\nCovers the latest AI research, open source and industry moves, updated daily.\nEditor\u0026rsquo;s Note A 26M-parameter model achieved on-device function calling; AI \u0026lsquo;self-replication\u0026rsquo; success jumped 13x to 81%; three ministries issued top-level agent policy; DeepSeek V4 broke the million-token context window; Anthropic crossed $900B valuation, eyeing an October IPO.\n1. Latest arXiv Papers TBA: Decoupling LLM RL Training — 50x Speedup — https://arxiv.org/abs/2503.18929\n"
}