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Neural Variability Enhances Artificial Network Robustness

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arXiv:2606. 13801v1 Announce Type: new Abstract: Neural responses in cortex exhibit substantial trial-to-trial variability in response to repeated stimuli, while peripheral sensory neurons respond far more consistently, leading many to wonder whether stochasticity may carry meaning.

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Authors: Robin Preble, Praveen Venkatesh, Stefan Mihalas, Kameron Decker Harris
Released: 2026-06-15 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Neural Variability Enhances Artificial Network Robustness overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)", experiment "#351 follow-up: broader-vocab position-0 sweep at T=1.0 + position-1 suffix isolation". Matching terms: under, rate. Source: arxiv cs.LG (Machine Learning).
arXiv: 2606.13801

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