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Stanford CS224V Lecture 11: Translate Trial Criteria into SMT Instead of Asking an LLM to Decide

The lecture parses patient records and trial criteria into SMT, retrieves candidates through a weaker propositional projection, and runs a solver on the reduced set. Reasoning is inspectable, but NL-to-SMT remains the main error boundary.

Stanford CS224V Lecture 6: Why Database Agents Begin with Semantic Parsing

Reliable database agents map language to executable queries, resolve schemas and enumerated values, and evaluate execution separately from answer generation; hybrid questions additionally require explicit source routing.

Stanford CS224V Lecture 7: SUQL Unifies SQL and Free-Text Retrieval

SUQL adds answer and summary functions over text to SQL. A semantic parser emits one hybrid query, while an optimizing compiler applies predicate pushdown, top-k pruning, and lazy evaluation.

Stanford CS224V Lecture 3: Building Task-Oriented Agents with Genie Worksheets

Genie Worksheets declare task capability as a form-like specification. A contextual semantic parser updates formal dialogue state while the runtime controls queries, actions, and responses.