{
  "title": "Daily Research Brief 2026-05-27",
  "url": "/en/posts/research-brief-2026-05-27/",
  "permalink": "https://hackcv.com/en/posts/research-brief-2026-05-27/",
  "date": "2026-05-27",
  "lastmod": "2026-05-27",
  "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-2026-05-27/1200/675",
  "readingTime": 1,
  "wordCount": 152,
  "content": "\u003ch1 id=\"daily-research-brief-2026-05-27\"\u003eDaily Research Brief 2026-05-27\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 paper thread today: AI safety as effective controllability, in-context continual unlearning (ICCU), scaling the harness rather than the model for long-horizon agents, and fine-grained credit assignment for LLM training.\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\u003ePosition: AI Safety Requires Effective Controllability\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2605.27117\"\u003ehttps://arxiv.org/abs/2605.27117\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eICCU: In-Context Continual Unlearning via Pattern-Induced Forgetting\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2605.27138\"\u003ehttps://arxiv.org/abs/2605.27138\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eAdvancing Mathematics Research with AI-Driven Formal Proof Assistance\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2605.22763\"\u003ehttps://arxiv.org/abs/2605.22763\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eFrom Model Scaling to System Scaling: Scaling the Harness for Long-Horizon Agents\u003c/strong\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eMobileGym: A Verifiable and Highly Parallel Simulation Environment for Mobile Agents\u003c/strong\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eSafeDiffusion-R1: A Continual Learning Framework for Safe Diffusion Models\u003c/strong\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eSkillEvolver: Self-Evolving Skill System for AI Agents\u003c/strong\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eFine-Grained Credit Assignment for LLM Training\u003c/strong\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eLingBot-VA: A Causal World Model for Robot Simulation and Manipulation\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2601.21998\"\u003ehttps://arxiv.org/abs/2601.21998\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eSqueezing Capacity from Multimodal Large Language Models\u003c/strong\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n",
  "summary": "Daily Research Brief 2026-05-27 📊 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 paper thread today: AI safety as effective controllability, in-context continual unlearning (ICCU), scaling the harness rather than the model for long-horizon agents, and fine-grained credit assignment for LLM training.\n1. Latest arXiv Papers Position: AI Safety Requires Effective Controllability — https://arxiv.org/abs/2605.27117\nICCU: In-Context Continual Unlearning via Pattern-Induced Forgetting — https://arxiv.org/abs/2605.27138\n"
}