Mark Purcell

Publications

• A Perspective on LLM Data Generation with Few-shot Examples: from Intent to Kubernetes Manifest

  • • Antonino Angi
    • Liubov Nedoshivina
    • et al.
  • 2025
  • ACL 2025

• MAD-MAX: Modular And Diverse Malicious AttackMiXtures for Automated LLM Red Teaming

  • • Stefan Schoepf
    • Muhammad Zaid Hameed
    • et al.
  • 2025
  • ICML 2025

• Granite Guardian: Comprehensive LLM Safeguarding

  • • Inkit Padhi
    • Manish Nagireddy
    • et al.
  • 2025
  • NAACL 2025

• Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI

  • • Ambrish Rawat
    • Stefan Schoepf
    • et al.
  • 2024
  • NeurIPS 2024

• MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks

  • • Giandomenico Cornacchia
    • Kieran Fraser
    • et al.
  • 2024
  • AIES 2024

• Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation

  • • Tomas Bueno Momcilovic
    • Beat Buesser
    • et al.
  • 2024
  • xAI 2024

• Pruning Federated Learning Models for Anomaly Detection in Resource-Constrained Environments

  • • Simone Magnani
    • Stefano Braghin
    • et al.
  • 2023
  • Big Data 2023

• Adaptive Aggregation For Federated Learning

  • • K. R. Kallapalayam Radhakrishnan
    • Vinod Muthusamy
    • et al.
  • 2022
  • Big Data 2022

• Machine Learning Platform for Extreme Scale Computing on Compressed IoT Data

  • • Seshu Tirupathi
    • Dhaval Salwala
    • et al.
  • 2022
  • Big Data 2022

• GOFLEX: Extracting, Aggregating and Trading Flexibility based on FlexOffers for 500+ Prosumers in 3 European cities [Operational Systems Paper]

  • • Bijay Neupane
    • Laurynas Siksnys
    • et al.
  • 2022
  • e-Energy 2022