Dennis Hofmann - Publications

MAADBench: The Refreshable Paradigm for Anomaly Detection in Multi-Agent Systems.
Lei Ma, Dennis M. Hofmann, Haowen Xu, Joshua DeOliveira, Peter M. VanNostrand, Lei Cao, Elke A. Rundensteiner
Preprint on arXiv 2026

Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation.
Lei Ma, Suhani Chaudhary, Ethan Shanbaum, Athanasios Tassiadamis, Peter M. VanNostrand, Dennis M. Hofmann, Haowen Xu, Elke A. Rundensteiner
IEEE International Conference on Data Mining (ICDM 2026) Demonstration

MAS-CORE: A Representative-Based Ensemble for Multi-Agent System Anomaly Detection
Ojal Prasad, Deeya Rawat, Corey Verkouteren, Dennis M. Hofmann, Lei Ma, Elke A. Rundensteiner
IEEE URTC 2026

Options Without Agency: Diversity as a Requirement for Fair Actionable Recourse
Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, Elke A. Rundensteiner
Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency (FAccT 2026)

KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction
Lei Ma, Jinyang Liu, Tieying Zhang, Peter M. VanNostrand, Dennis M. Hofmann, Lei Cao, Elke A. Rundensteiner, Jianjun Chen
Proceedings of the IEEE International Conference on Data Engineering (ICDE 2026)

Agree to Disagree: Robust Anomaly Detection with Noisy Labels
Dennis M. Hofmann, Peter M. VanNostrand, Lei Ma, Huayi Zhang, Joshua C. DeOliveira, Lei Cao, Elke Rundensteiner
Proceedings of the ACM on Management of Data (SIGMOD 2025)

Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data
Lei Ma, Lei Cao, Peter M. VanNostrand, Dennis M. Hofmann, Su Yao, Elke Rundensteiner
Proceedings of the ACM on Management of Data (SIGMOD 2025)

Counterfactual Explanation Analytics: Empowering Lay Users to Take Action Against Consequential Automated Decisions
Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, Belisha Genin, Randy Huang, Elke Rundensteiner
Proceedings of the VLDB Endowment (VLDB 2024) Demonstration

Actionable Recourse for Automated Decisions: Examining the Effects of Counterfactual Explanation Type and Presentation on Lay User Understanding
Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, Elke Rundensteiner
The ACM Conference on Fairness, Accountability, and Transparency (FAccT 2024)

FACET: Robust Counterfactual Explanation Analytics
Peter M. VanNostrand, Huayi Zhang, Dennis M. Hofmann, Elke Rundensteiner
Proceedings of the ACM on Management of Data (SIGMOD 2023)

A Demonstration of AutoOD: A Self-Tuning Anomaly Detection System
Dennis M. Hofmann, Peter M. VanNostrand, Huayi Zhang, Yizhou Yan, Lei Cao, Samuel Madden, Elke Rundensteiner
Proceedings of the VLDB Endowment 2022 (VLDB 2022) Demonstration