Hannes Hapke discusses using sparse autoencoders to explain LLM agent decisions, providing a model-agnostic framework for understanding why agents make certain choices. The Kiji Inspector tool is introduced as a solution for explaining agent decisions, allowing for causal analysis and feature extraction.
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Hannes Hapke discusses using sparse autoencoders to explain LLM agent decisions, providing a model-agnostic framework for understanding why agents make certain choices. The Kiji Inspector tool is introduced as a solution for explaining agent decisions, allowing for causal analysis and feature extraction.
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Hannes Hapke discusses using sparse autoencoders to explain LLM agent decisions, providing a model-agnostic framework for understanding why agents make certain choices. The Kiji Inspector tool is introduced as a solution for explaining agent decisions, allowing for causal analysis and feature extraction.
Google's Gemini 4 Hydrogen improves search
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