NLP Challenges
Sameer highlights the unique challenges of interpretability in NLP due to discrete inputs and the difficulty in defining valid input combinations. Nathan discusses the complexities of explanation methods in linear models, raising questions on the relevance of input text weighting.In this clip
From this podcast
NLP Highlights
117 - Interpreting NLP Model Predictions, with Sameer Singh
Related Questions
What is the challenge around explainability in AI as discussed in the episode 117 - Interpreting NLP Model Predictions, with Sameer Singh and the clip Feature Attribution Methods?
What challenges are faced in training large language models (LLMs) as discussed in the episode Ishan Misra: Self-Supervised Deep Learning in Computer Vision | Lex Fridman Podcast #206 and the clip NLP vs. Computer Vision?