Montague, Paul

16 publications

NeurIPS 2025 3D-Prover: Diversity Driven Theorem Proving with Determinantal Point Processes Sean Lamont, Christian Walder, Amir Dezfouli, Paul Montague, Michael Norrish

ICLR 2025 Fantastic Targets for Concept Erasure in Diffusion Models and Where to Find Them Anh Tuan Bui, Thuy-Trang Vu, Long Tung Vuong, Trung Le, Paul Montague, Tamas Abraham, Junae Kim, Dinh Phung

ICLRW 2025 Hiding and Recovering Knowledge in Text-to-Image Diffusion Models via Learnable Prompts Anh Tuan Bui, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Phung

ICLR 2025 Multi-Level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning Shijie Liu, Andrew Craig Cullen, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein

ICML 2025 Position: Certified Robustness Does Not (Yet) Imply Model Security Andrew Craig Cullen, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein

AAAI 2024 BAIT: Benchmarking (Embedding) Architectures for Interactive Theorem-Proving Sean Lamont, Michael Norrish, Amir Dezfouli, Christian Walder, Paul Montague

NeurIPS 2024 Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation Anh Bui, Long Vuong, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Phung

ICML 2024 Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples Andrew Craig Cullen, Shijie Liu, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein

AAAI 2023 Enhancing the Antidote: Improved Pointwise Certifications Against Poisoning Attacks Shijie Liu, Andrew C. Cullen, Paul Montague, Sarah M. Erfani, Benjamin I. P. Rubinstein

AAAI 2023 Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness Bao Gia Doan, Shuiqiao Yang, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Seyit Camtepe, Salil S. Kanhere, Ehsan Abbasnejad, Damith C. Ranasinghe

TMLR 2023 Generating Adversarial Examples with Task Oriented Multi-Objective Optimization Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Phung

AISTATS 2022 On Global-View Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds Trung Le, Anh Tuan Bui, Le Minh Tri Tue, He Zhao, Paul Montague, Quan Tran, Dinh Phung

NeurIPS 2022 Double Bubble, Toil and Trouble: Enhancing Certified Robustness Through Transitivity Andrew Cullen, Paul Montague, Shijie Liu, Sarah Erfani, Benjamin I. Rubinstein

AAAI 2021 Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung

ECCV 2020 Improving Adversarial Robustness by Enforcing Local and Global Compactness Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier deVel, Tamas Abraham, Dinh Phung

ICLR 2019 Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection Tue Le, Tuan Nguyen, Trung Le, Dinh Phung, Paul Montague, Olivier De Vel, Lizhen Qu