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AIR achieves over 18% better perplexity than previous methods while retaining 60% of the parameters, revolutionizing LLM compression efficiency.
Outer informedness in INDEQS consistently reduces forecasting error on complex graphs, outperforming traditional methods even with similar parameter counts.
Activation probes can predict future behaviors in reasoning models with up to 91% accuracy, enabling effective steering without sacrificing output quality.
