The paper proposes using modified Complementary Cumulative Distribution Function (mCCDF) plots to visualize and communicate results of cumulative-link ordinal regression models for ordinal data.

This study provides a longitudinal analysis of dark web content, revealing that cybercrime discussions are dominated by a few persistent core topics rather than rapidly shifting themes.

This paper introduces Distributional Random Forests, which replace mean-based CART splitting with criteria that compare full conditional response distributions in candidate children. The authors syste…

This paper introduces a component-centric framework and a novel detector, Connor, to understand and detect sophisticated, multi-component attacks targeting the Model Context Protocol (MCP) servers.

The paper introduces causal density functions, which are local density ratios that allow for the pointwise estimation and scoring of directed causal influence by comparing interventional and observati…

MACReD introduces a hierarchical multi-agent framework that achieves state-of-the-art performance in parsing complex chemical reaction diagrams by coordinating specialized agents for perception and gl…

This paper introduces a new R package for Non-negative Matrix Factorization (NMF) and compares its performance systematically with two other R packages using real-world data.

The paper proposes MVRAF, a data-driven framework that quantifies vulnerability risk in large-scale cloud infrastructure by integrating multiple attack attributes and analyzing cumulative risk distrib…

SWORD is a novel online regime detection method for dynamic networks that significantly improves change point detection accuracy by comparing the mean of spectral moments between adjacent time windows…

The paper proposes PCDM, a diffusion-based framework that enables highly stealthy and effective data poisoning attacks against Federated Learning systems, significantly degrading global performance wh…

This paper derives multivariate generating functions to refine the enumeration of Fibonacci polyominoes.

The paper introduces MCP Pitfall Lab, a comprehensive security testing framework that rigorously assesses and validates developer pitfalls in Model Context Protocol (MCP) tool servers under realistic…