Loten Noy

Explores applying SHAP for token-level attribution to interpret large language model outputs, covering experiments on sentiment, hate speech, and toxicity classification and describing use cases for prompt engineering, debugging, and dataset augmentation.

Discusses designing ML infrastructure that balances quick POC development and production-readiness, including principles for POC tooling, storage service examples, and migrating exploratory code to production.