Pedram, Massoud

13 publications

IJCAI 2025 Efficient Counterexample-Guided Fairness Verification and Repair of Neural Networks Using Satisfiability Modulo Convex Programming Arya Fayyazi, Yifeng Xiao, Pierluigi Nuzzo, Massoud Pedram

ICML 2025 FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems Arya Fayyazi, Mehdi Kamal, Massoud Pedram

ICLR 2025 MambaExtend: A Training-Free Approach to Improve Long Context Extension of Mamba Seyedarmin Azizi, Souvik Kundu, Mohammad Erfan Sadeghi, Massoud Pedram

ICLRW 2025 QMambaExtend: Improving Long-Context Extension of Memory-Efficient Mamba Models Seyedarmin Azizi, Souvik Kundu, Mohammad Erfan Sadeghi, Massoud Pedram

NeurIPS 2025 Top-H Decoding: Adapting the Creativity and Coherence with Bounded Entropy in Text Generation Erfan Baghaei Potraghloo, Seyedarmin Azizi, Souvik Kundu, Massoud Pedram

ECCVW 2024 Memory-Efficient Vision Transformers: An Activation-Aware Mixed-Rank Compression Strategy Seyedarmin Azizi, Mahdi Nazemi, Massoud Pedram

ICMLW 2024 Training-Free Acceleration of ViTs with Delayed Spatial Merging Jung Hwan Heo, Seyedarmin Azizi, Arash Fayyazi, Massoud Pedram

NeurIPSW 2024 Training-Free Visual Token Compression via Delayed Spatial Merging Jung Hwan Heo, Seyedarmin Azizi, Arash Fayyazi, Massoud Pedram

WACV 2023 FLOAT: Fast Learnable Once-for-All Adversarial Training for Tunable Trade-Off Between Accuracy and Robustness Souvik Kundu, Sairam Sundaresan, Massoud Pedram, Peter A. Beerel

NeurIPS 2021 Analyzing the Confidentiality of Undistillable Teachers in Knowledge Distillation Souvik Kundu, Qirui Sun, Yao Fu, Massoud Pedram, Peter Beerel

ICCV 2021 HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise Souvik Kundu, Massoud Pedram, Peter A. Beerel

WACV 2021 Spike-Thrift: Towards Energy-Efficient Deep Spiking Neural Networks by Limiting Spiking Activity via Attention-Guided Compression Souvik Kundu, Gourav Datta, Massoud Pedram, Peter A. Beerel

AAAI 2019 A Meta-Learning Approach for Custom Model Training Amir Erfan Eshratifar, Mohammad Saeed Abrishami, David Eigen, Massoud Pedram