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Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips research paper by NVIDIA, 2026

NVIDIA · Apr 16, 2026 · Reasoning · 4 citations · 57 upvotes · unverified

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What it shows

Deep neural networks exhibit catastrophic vulnerability to minimal parameter bit flips across multiple domains, which can be identified and mitigated through targeted protection strategies.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Ido Galil, Moshe Kimhi, Ran El-Yaniv
arXiv
2502.07408 · PDF
Venue
Trans. Mach. Learn. Res.
Citations
4, 0 influential · Semantic Scholar
Upvotes
57 · Hugging Face
Code
github.com/IdoGalil/maximal-brain-damage
Lab
NVIDIA · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 4Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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