This paper introduces ZipLine, a system for integrative analysis of multivariate graphs through a unified predicate language and learning algorithm.

The paper proposes two methods for predicting tennis match outcomes using topological data analysis and graph theory. The first method uses lower-star filtration and persistent homology, achieving 66.…

The paper introduces EduMPI, a learning support tool for simplifying cluster usage and performance analysis of MPI parallel programs for students.

LEAF is a dynamic analysis framework for Rust that captures MIR-level semantic information and delivers it as an event stream through Dynamic MIR.

The paper introduces LongDS, a new benchmark for long-horizon, multi-turn data analysis, demonstrating that current AI agents struggle significantly with maintaining and updating complex analytical st…

This paper investigates ways to transform a theory-based methodology for optimizing visual analytics workflows from theory to practice using case studies.

The paper introduces Hyperparam, a set of lightweight JavaScript libraries designed to enable direct, model-aware querying of unstructured data (like agent traces) within client-side AI applications.

This paper presents a pipeline for transforming historical sources into structured data using machine learning tools and the GRAM-framework, enabling automated, skeletal graphing of actions.

An industrial evaluation of an AI-enabled decision-support tool for crime linkage analysis was conducted, showing analysts selectively used AI predictions and valued model features.

This paper proposes statistical procedures to identify coordinates responsible for change-points in multivariate time series data.

The paper introduces FinVerBench, a comprehensive benchmark for financial statement verification, concluding that successful verification requires calibrated judgment under realistic observational con…

The paper introduces BusinessCaseBench, a benchmark for measuring AI performance on analytical knowledge work using business cases and grading rubrics.

This paper extends gradient boosting to functions of vector inputs using a simple algorithm with histogram-based decision trees.

The paper proposes a generic memory framework for advanced static program analysis, supporting various memory behaviors from different programming languages using Abstract Interpretation theory.

This study investigated the stability and prompt-responsiveness of AI tools in classifying the cognitive demand of math tasks, finding that few-shot prompting was a more reliable performance booster t…

Authors of 44 meta-analyses preferred a single pass by a frontier model over two multi-agent debate tools for improving their papers, despite the tools spending roughly thirty times the tokens.