{
  "title": "Daily Research Brief 2026-06-13",
  "url": "/en/posts/research-brief-2026-06-13/",
  "permalink": "https://hackcv.com/en/posts/research-brief-2026-06-13/",
  "date": "2026-06-13",
  "lastmod": "2026-06-13",
  "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-2026-06-13/1200/675",
  "readingTime": 1,
  "wordCount": 149,
  "content": "\u003ch1 id=\"daily-research-brief-2026-06-13\"\u003eDaily Research Brief 2026-06-13\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\u003eThe paper thread today: MemRefine compresses long-term agent memory, MaxProof scales math proof via generative-verifier RL, epiphenomenal CoT probing, and OpenMedReason for medical VLMs.\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\u003eCross-Modal Masked Compositional Concept Modeling for Enhancing Visio-Linguistic Compositionality\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2606.13288\"\u003ehttps://arxiv.org/abs/2606.13288\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eMemRefine: LLM-Guided Compression for Long-Term Agent Memory\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2606.13177\"\u003ehttps://arxiv.org/abs/2606.13177\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eBeyond the Commitment Boundary: Probing Epiphenomenal Chain-of-Thought in Large Reasoning Models\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2606.13603\"\u003ehttps://arxiv.org/abs/2606.13603\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eReSET: Accurate Latency-Critical NVFP4 Reasoning via Step-Aware Temperature Scaling\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2606.13233\"\u003ehttps://arxiv.org/abs/2606.13233\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eSkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2606.13647\"\u003ehttps://arxiv.org/abs/2606.13647\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eMaxProof: Scaling Mathematical Proof with Generative-Verifier RL and Population-Level Test-Time Scaling\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2606.13473\"\u003ehttps://arxiv.org/abs/2606.13473\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eOpenMedReason: Scientific Reasoning Supervision for Medical Vision-Language Models\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2606.12169\"\u003ehttps://arxiv.org/abs/2606.12169\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eFrom Prompts to Tokens: Internalizing Causal Supervision in Vision-Language Model for Multi-Image Causal Reasoning\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2606.11745\"\u003ehttps://arxiv.org/abs/2606.11745\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n",
  "summary": "Daily Research Brief 2026-06-13 📊 Token usage: estimated from retrieval and writing scale.\nCovers the latest AI research, open source and industry moves, updated daily.\nEditor\u0026rsquo;s Note The paper thread today: MemRefine compresses long-term agent memory, MaxProof scales math proof via generative-verifier RL, epiphenomenal CoT probing, and OpenMedReason for medical VLMs.\n1. Latest arXiv Papers Cross-Modal Masked Compositional Concept Modeling for Enhancing Visio-Linguistic Compositionality — https://arxiv.org/abs/2606.13288\nMemRefine: LLM-Guided Compression for Long-Term Agent Memory — https://arxiv.org/abs/2606.13177\n"
}