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Episodes


Stanford XCS224U: NLU I NLP Methods and Metrics, Part 3: Generation Metrics I Spring 2023

Stanford XCS224U: NLU I NLP Methods and Metrics, Part 2: Classifier Metrics I Spring 2023

Stanford XCS224U: NLU I NLP Methods and Metrics, Part 1: Overview I Spring 2023

Stanford XCS224U: Natural Language Understanding I Experiment Protocol Overview I Spring 2023

Stanford XCS224U: Analysis NLU, Part 5: Distributed Alignment Search (DAS) & Conclusion I Spring 23

Stanford XCS224U I Analysis NLU, Pt 4: Casual Abstraction & Interchange Intervention Training (IIT)

Stanford XCS224U: NLU I Analysis Methods for NLU, Part 3: Feature Attribution I Spring 2023

Stanford XCS224U: NLU I Analysis Methods for NLU, Part 2: Probing I Spring 2023

Stanford XCS224U: NLU I Analysis Methods for NLU, Part 1: Overview I Spring 2023

Stanford XCS224U: Natural Language Understanding I Lit Review Overview I Spring 2023

Stanford XCS224U: NLU I Behavioral Eval of NLU Models, Pt 7: DynaSent and Conclusion I Spring 2023

Stanford XCS224U: NLU I Behavioral Evaluation of NLU Models, Part 6: Adversarial NLI I Spring 2023

Stanford XCS224U: NLU I Behavioral Evaluation of NLU Models, Pt 5: Adversarial Testing I Spring 2023

Stanford XCS224U: NLU I Behavioral Evaluation of NLU Models, Part 4: COGS and ReCOGS I Spring 2023

Stanford XCS224U: NLU I Behavioral Evaluation of NLU Models, Part 3: Compositionality I Spring 2023

Stanford XCS224U I Behavioral Eval of NLU Models, Pt 2: Analytical Considerations I Spring 2023

Stanford XCS224U: NLU I Behavioral Evaluation of NLU Models, Part 1: Overview I Spring 2023

Stanford XCS224U: Natural Language Understanding I Homework 3 I Spring 2023

Stanford XCS224U: NLU I In-context Learning, Part 4: Techniques and Suggested Methods I Spring 2023
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