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probeshift-activation-cache – Dataset by Beicicc | AlphaNeural AI
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probeshift-activation-cache
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feature-extraction
mit
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linear-probes
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ProbeShift Activation Cache
Residual-stream activations backing the ProbeShift benchmark — a label-free study of linear-probe direction stability under label-preserving semantic shift. Ships so the benchmark's numbers reproduce in minutes (no re-extraction needed).
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cache_seed{0..4}/
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/ acts.npy float16 [N, L+1, H] masked-mean-pooled residual stream (L+1 = embeddings + L layers) labels.npy int64 [N]… See the full description on the dataset page:
https://huggingface.co/datasets/Beicicc/probeshift-activation-cache
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