arXiv:2604.04990v1 Announce Type: cross
Abstract: AI coding agents select frameworks, scaffold infrastructure, and wire integrations, often in seconds. These are architectural decisions, yet almost no one reviews them as such. We identify five mechanisms by which agents make implicit architectural choices and propose six prompt-architecture coupling patterns that map natural-language prompt features to the infrastructure they require. The patterns range from contingent couplings (structured output validation) that may weaken as models improve to fundamental ones (tool-call orchestration) that persist regardless of model capability. An illustrative demonstration confirms that prompt wording alone produces structurally different systems for the same task. We term the phenomenon vibe architecting, architecture shaped by prompts rather than deliberate design, and outline review practices, decision records, and tooling to bring these hidden decisions under governance.
TR-EduVSum: A Turkish-Focused Dataset and Consensus Framework for Educational Video Summarization
arXiv:2604.07553v1 Announce Type: cross Abstract: This study presents a framework for generating the gold-standard summary fully automatically and reproducibly based on multiple human summaries of


