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FINN-Tro: Exploiting Verification Gaps in Dataflow Inference Accelerators
The growing adoption of dataflow accelerators for neural network inference introduces new attack surfaces that existing verification methodologies fail to address. Inference ac- celeration frameworks such as FINN, which transform quantized neural networks into FPGA-deployable dataflow architectures,
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