{
  "title": "Daily Research Brief 2026-07-30",
  "url": "/en/posts/research-brief-2026-07-30/",
  "permalink": "https://hackcv.com/en/posts/research-brief-2026-07-30/",
  "date": "2026-07-30",
  "lastmod": "2026-07-30",
  "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-2026-07-30/1200/675",
  "readingTime": 1,
  "wordCount": 167,
  "content": "\u003ch1 id=\"daily-research-brief-2026-07-30\"\u003eDaily Research Brief 2026-07-30\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\u003eThe signal to watch today: \u0026lsquo;agents are evolving from tools into self-evolving systems\u0026rsquo;. On arXiv, SkillRise makes cross-task skill distillation a unified RL problem, Living-Harness lets the harness itself iterate on failure experience, and TSDS equips edge agents with \u0026rsquo;think short, defer smart\u0026rsquo; calibration.\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\u003eSkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2607.26784\"\u003ehttps://arxiv.org/abs/2607.26784\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eThink Short, Defer Smart, Act, and Repeat: Calibrated Reasoning and Uncertainty-Aware Deferral for Edge LLM Agents\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2607.26865\"\u003ehttps://arxiv.org/abs/2607.26865\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eEmbodied Agents Take Control: Minimal-Interface Zero-Shot Agents Rival Industrial-Scale Policies in Vision-and-Language Navigation\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2607.26148\"\u003ehttps://arxiv.org/abs/2607.26148\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eLiving-Harness Is an Interactive-Agent Evolver\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2607.26598\"\u003ehttps://arxiv.org/abs/2607.26598\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eMitigating Compounding Error via Video Representation Regularization\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2607.27036\"\u003ehttps://arxiv.org/abs/2607.27036\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eFreqForcing: Autoregressive Long Video Generation via Spectral Self-Anchoring\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2607.27110\"\u003ehttps://arxiv.org/abs/2607.27110\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eSwapping the Optimizer Boosts RL Agent Training Efficiency by Up to ~88%\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2607.16169\"\u003ehttps://arxiv.org/abs/2607.16169\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eScaling GUI Agents with Visual State Transitions\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2607.24112\"\u003ehttps://arxiv.org/abs/2607.24112\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n",
  "summary": "Daily Research Brief 2026-07-30 📊 Token usage: estimated from retrieval and writing scale.\nCovers the latest AI research, open source and industry moves, updated daily.\nEditor\u0026rsquo;s Note The signal to watch today: \u0026lsquo;agents are evolving from tools into self-evolving systems\u0026rsquo;. On arXiv, SkillRise makes cross-task skill distillation a unified RL problem, Living-Harness lets the harness itself iterate on failure experience, and TSDS equips edge agents with \u0026rsquo;think short, defer smart\u0026rsquo; calibration.\n"
}