Learning Objectives
Apply CxG analysis to diagnose and characterize LLM syntactic-semantic misalignment patterns
Use constructional knowledge to design more effective fine-tuning objectives and training strategies
Evaluate LLMs systematically on non-compositional constructions and idiomatic expressions
Integrate CxG insights practically into NLU pipeline design for production AI systems
Using construction grammar insights to systematically improve LLM syntax-semantics alignment.
This lesson builds on the theoretical foundations established earlier in the module and extends your understanding of how cognitive-linguistic principles apply directly to modern AI systems.
Learning Objectives
Apply CxG analysis to diagnose and characterize LLM syntactic-semantic misalignment patterns
Use constructional knowledge to design more effective fine-tuning objectives and training strategies
Evaluate LLMs systematically on non-compositional constructions and idiomatic expressions
Integrate CxG insights practically into NLU pipeline design for production AI systems
Key Concepts
Apply CxG analysis to diagnose and characterize LLM syntactic-semantic misalignment patterns
Use constructional knowledge to design more effective fine-tuning objectives and training strategies
Evaluate LLMs systematically on non-compositional constructions and idiomatic expressions
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