Tag: model interpretability
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Activation Steering in AI: From Attribution to Action
Explore how activation steering transforms AI explainability from insight to actionable intervention for better model interpretability and debugging.
NeuronLens: Enhancing LLMs with Range-Based Neuron Attribution
Discover NeuronLens, a novel framework improving LLM interpretability by analyzing neuron activation ranges to overcome polysemanticity challenges.
Why Reasoning Models Misrepresent Their Thought Process
Discover why Large Reasoning Models sometimes mislead about their reasoning and how this impacts AI trust and transparency.
Scalable Interpretability & Control for Large Language Models
Discover scalable methods for interpreting and controlling large multi-GPU language models, boosting performance and steering outputs effectively.
Spectral Edge Dynamics Unveil Key Learning Modes
Discover how spectral edge dynamics reveal low-dimensional functional modes in machine learning, enhancing model interpretability and learning efficiency.