While LLM quantization's impact on utility has been extensively explored, this work for the first time studies its adverse effects from a security perspective.

InMTL, there areDdifferent labeled domains where data are related and the goal is to improve the predictive power of all domains altogether.

Neural Information Processing Systems http://nips.cc/

Xiaoqian Wu Shanghai Jiao Tong University enlighten@sjtu.edu.cn In Tab. 1, we conclude the notations in this work for clarity.Notation Definition r A rule. The size of the premise symbols set M . S is the symbol set, and R is the rule set. A \ B The set difference of A and B. D A very large-scale activity images database.

Human reasoning can be understood as a cooperation between the intuitive, associative "System-1" and the deliberative, logical "System-2".

Recently,there has been agrowing interest in developing saliencymethods that providevisualexplanations ofnetworkpredictions. Still,theusability ofexisting methods is limited to image classification models. To overcome this limitation, we extend the existing approaches to generategrid saliencies, which provide spatially coherent visualexplanations for(pixel-level)denseprediction networks.

Filteringx-noiseusing W noise. Inspired weutilizex-noise.

We first examine how H -consistency bounds vary across surrogates based on the number of classes.