Principal Component Analysis Visualization

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Principal components analysis (PCA)method0.834
  Statistical method used to analyze neural activity data.
• Feature Visualizationmethod0.816
  Method of optimizing input to cause a neuron to fire maximally, used to characterize what a neuron detects; establishes causal link
• PCA visualizations of LLaMA-2-13B and 70B representations of curated datasets show clear linear structure, with true statements separating from false ones in the top two principal componentsfinding0.751
  Primary visual evidence for linear truth representations in large LLMs
• Interactive Circuit Visualizationmethod0.742
  Interactive tool for visualizing and inspecting learned binary logic circuits using modified DigitalJS library
• Value-Weighted Attention Pattern Visualizationmethod0.742
  Visualizing attention patterns weighted by the norm of value vectors to better show how much information is moved from each position
• Mind's eye visualizationmethod0.741
  Technique of building a fluid, three-dimensional vision by closing one's eyes, relying on words and feeling to avoid arbitrary graphical over-specification.
• Contrastive analysismethod0.741
  Method comparing brain activity in conscious vs. unconscious conditions.
• Combining visualization and analysis is useful to arrive at a deeper understanding of the Fifteen Properties.hypothesis0.740
  Authors' central hypothesis tested and supported through their illustration and correspondence analysis methodology.