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cs.CV2025
Sampling Matters in Explanations: Towards Trustworthy Attribution Analysis Building Block in Visual Models through Maximizing Explanation Certainty
Róisín Luo, James McDermott, Colm O'Riordan
Image attribution analysis seeks to highlight the feature representations learned by visual models such that the highlighted feature maps can reflect the pixel-wise importance of i…
cs.CV2024
Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization
Róisín Luo, Alexandru Drimbarean, James McDermott +1
This paper explores a novel paradigm in low-bit (i.e. 4-bits or lower) quantization, differing from existing state-of-the-art methods, by framing optimal quantization as an archite…