AI RESEARCH
A Domain-Specific Language for LLM-Driven Trigger Generation in Multimodal Data Collection
arXiv CS.LG
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ArXi:2604.13046v1 Announce Type: cross Data-driven systems depend on task-relevant data, yet data collection pipelines remain passive and indiscriminate. Continuous logging of multimodal sensor streams incurs high storage costs and captures irrelevant data. This paper proposes a declarative framework for intent-driven, on-device data collection that enables selective collection of multimodal sensor data based on high-level user requests. The framework combines natural language interaction with a formally specified domain-specific language.