{
  "title": "Daily Research Brief 2026-04-19",
  "url": "/en/posts/research-brief-2026-04-19/",
  "permalink": "https://hackcv.com/en/posts/research-brief-2026-04-19/",
  "date": "2026-04-19",
  "lastmod": "2026-04-19",
  "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-2026-04-19/1200/675",
  "readingTime": 1,
  "wordCount": 120,
  "content": "\u003ch1 id=\"daily-research-brief-2026-04-19\"\u003eDaily Research Brief 2026-04-19\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\u003eTesla brought its robotaxi service to Dallas and Austin; AI chip startup Cerebras filed for 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\u003eBidirectional Cross-Modal Prompting for Event-Centric Video QA\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2604.15312\"\u003ehttps://arxiv.org/abs/2604.15312\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eLeapAlign: Post-Training Flow Matching Models for Alignment\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2604.15311\"\u003ehttps://arxiv.org/abs/2604.15311\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eGeneralization in LLM Problem Solving: The Case of Few-Shot Learning\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2604.15306\"\u003ehttps://arxiv.org/abs/2604.15306\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnosing LLM Judge Reliability: Conformal Prediction Approaches\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2604.15302\"\u003ehttps://arxiv.org/abs/2604.15302\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eMM-WebAgent: A Hierarchical Multimodal Web Agent\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2604.15309\"\u003ehttps://arxiv.org/abs/2604.15309\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eHow Do LLMs and VLMs Understand Viewpoint Rotation?\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2604.15294\"\u003ehttps://arxiv.org/abs/2604.15294\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eCoopEval: Benchmarking Cooperation-Sustaining Multi-Agent Systems\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2604.15267\"\u003ehttps://arxiv.org/abs/2604.15267\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eFrom Tokens to Steps: Verification-Aware Speculative Decoding\u003c/strong\u003e — \u003ca href=\"https://arxiv.org/abs/2604.15244\"\u003ehttps://arxiv.org/abs/2604.15244\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n",
  "summary": "Daily Research Brief 2026-04-19 📊 Token usage: estimated from retrieval and writing scale.\nCovers the latest AI research, open source and industry moves, updated daily.\nEditor\u0026rsquo;s Note Tesla brought its robotaxi service to Dallas and Austin; AI chip startup Cerebras filed for IPO.\n1. Latest arXiv Papers Bidirectional Cross-Modal Prompting for Event-Centric Video QA — https://arxiv.org/abs/2604.15312\nLeapAlign: Post-Training Flow Matching Models for Alignment — https://arxiv.org/abs/2604.15311\nGeneralization in LLM Problem Solving: The Case of Few-Shot Learning — https://arxiv.org/abs/2604.15306\n"
}