4 accepted papers
Large Language Models face fundamental deployment challenges due to the computational demands of auto-regressive token-by-token generation. While speculative decoding has emerged as a promising acceleration technique through its draft-then-verify framework, current implementations suffer from two cr
Music deepfake detection is aimed at identifying whether songs are generated by AI. Current methods usually separate vocals from background music for detection, but this could leave residual forgery information in the background. Our study demonstrates for the first time that incorporating backgroun…
Deep Equilibrium (DEQ) models hold great promise for expanding the capabilities of neural networks and showcasing competitive performances with less memory cost. However, the backward propagation steps in their training process typically involve expensive Jacobian-inverse calculations, resulting in…
Graph Transformers (GTs) have emerged as powerful tools for handling graph-structured data through global attention mechanisms. While GTs can effectively capture long-range dependencies, they introduce difficulties in optimization due to their complex, non-differentiable operators, which cannot be d