17 citations · 25 across the 7 of their papers we have counts for
3 papers · 2 filters
Continuous Prompts: LLM-Augmented Pipeline Processing over Unstructured Streams
Shu Chen, Deepti Raghavan, Uğur Çetintemel
Monitoring unstructured streams increasingly requires persistent, semantics-aware computation, yet today's LLM frameworks remain stateless and one-shot, limiting their usefulness f…
Making Prompts First-Class Citizens for Adaptive LLM Pipelines
Ugur Cetintemel, Shu Chen, Alexander W. Lee +3
Modern LLM pipelines increasingly resemble complex data-centric applications: they retrieve data, correct errors, call external tools, and coordinate interactions between agents. Y…
Semantic Integrity Constraints: Declarative Guardrails for AI-Augmented Data Processing Systems
Alexander W. Lee, Justin Chan, Michael Fu +4
AI-augmented data processing systems (DPSs) integrate large language models (LLMs) into query pipelines, allowing powerful semantic operations on structured and unstructured data.…