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Building a\nneural network for such a problem presents a number of interesting challenges\nthat have not occurred in tasks such as image processing or NLP. In particular,\nwe note that detection from raw bytes presents a sequence problem with over two\nmillion time steps and a problem where batch normalization appear to hinder the\nlearning process. We present our initial work in building a solution to tackle\nthis problem, which has linear complexity dependence on the sequence length,\nand allows for interpretable sub-regions of the binary to be identified. 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