LLM Interpretability and Sparse Autoencoders: Research from OpenAI and Anthropic
Deep Papers
Exploration of Searching for Features and Ensuring Model Safety
This chapter delves into effective methods for identifying and analyzing specific features within models, including filtering and inspecting nearest neighbor features. It also discusses multilingual and multimodal features, importance of sparsity, and the necessity of ensuring safety in models to prevent biases and harm.
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