From Intent to Improvement: Agentic Dataset Search for Better Model Training
arXiv:2610.39608v1 Announce Type: new Abstract: Finding training data in million-scale machine learning repositories is a Web search problem where text relevance is not enough. A query couples a semantic training goal with constraints such as task, license, and training stage, and the metadata that would verify them are often missing. Text retrieval ranks dataset cards by similarity but cannot enforce hard constraints or follow the relations that reach a sparsely described dataset. Free-form to…