Deep Learning
Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification Jan Schuchardt
Our tight mechanism-specific bounds outperform tight mechanism-agnostic bounds and classic group privacy results.
TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases
We evaluated adversarial robustness with CAA, an ensemble of gradient and search attacks which was recently demonstrated as the most effective attack against a tabular model.
One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection
Traditional Anomaly Detection (AD) methods have predominantly relied on unsupervised learning from extensive normal data.
Understanding Transformer Reasoning Capabilities via Graph Algorithms Clayton Sanford
Which transformer scaling regimes are able to perfectly solve different classes of algorithmic problems?
D: Supplementary Materials Table of Contents
Scores are calculated by giving a weight of 1 for applicable, 0.5 for conditionally applicable, and 0 for incorrect responses.
D: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages
D comprises 52.6k question-answer pairs from 16 countries/regions,