Salt and pepper noise removal for image signals. - Soheil Feizi; Sina Zahedpour; Mahdi Soltanolkotabi; Arash Amini; Farokh Marvasti (ICT, 2008)

Impulsive noise cancellation using CFAR and iterative techniques. - Sina Zahedpour; Soheil Feizi; Arash Amini; Mahmoud Ferdosizadeh Naeiny; Farokh Marvasti (ICT, 2008)

Lower and Upper Bounds for Throughput Capacity of a Cognitive Ad Hoc Network Overlaid on a Cellular Network. - Soheil Feizi-Khankandi; Farid Ashtiani (WCNC, 2008)

When do only sources need to compute? On functional compression in tree networks. - Soheil Feizi; Muriel Médard (Allerton, 2009)

Multi-Functional Compression with Side Information. - Soheil Feizi-Khankandi; Muriel Médard (GLOBECOM, 2009)

Impulsive Noise Cancellation Based on Soft Decision and Recursion. - Sina Zahedpour; Soheil Feizi; Arash Amini; Mahmoud Ferdosizadeh Naeiny; Farrokh Marvasti (IEEE Trans. Instrum. Meas., 2009)

Robust Audio Data Hiding Using Correlated Quantization With Histogram-Based Detector. - Mohammad Ali Akhaee; Mohammad Javad Saberian; Soheil Feizi; Farokh Marvasti (IEEE Trans. Multim., 2009)

Locally Adaptive Sampling. - Soheil Feizi; Vivek K. Goyal; Muriel Médard (Allerton, 2010)

Compressive sensing over networks. - Soheil Feizi; Muriel Médard; Michelle Effros (Allerton, 2010)

Cases where finding the minimum entropy coloring of a characteristic graph is a polynomial time problem. - Soheil Feizi; Muriel Médard (ISIT, 2010)

A power efficient sensing/communication scheme: Joint source-channel-network coding by using compressive sensing. - Soheil Feizi; Muriel Médard (Allerton, 2011)

Empirical rate-distortion study of compressive sensing-based joint source-channel coding. - Muriel L. Rambeloarison; Soheil Feizi; Georgios Angelopoulos; Muriel Médard (ACSCC, 2012)

Time-Stampless Adaptive Nonuniform Sampling for Stochastic Signals. - Soheil Feizi; Vivek K. Goyal; Muriel Médard (IEEE Trans. Signal Process., 2012)

Tunable sparse network coding for multicast networks. - Soheil Feizi; Daniel E. Lucani; Chres W. Sørensen; Ali Makhdoumi; Muriel Médard (NetCod, 2014)

Biclustering Usinig Message Passing. - Luke J. O'Connor; Soheil Feizi (NIPS, 2014)

On Network Functional Compression. - Soheil Feizi; Muriel Médard (IEEE Trans. Inf. Theory, 2014)

Backward Adaptation for Power Efficient Sampling. - Soheil Feizi; Georgios Angelopoulos; Vivek K. Goyal; Muriel Médard (IEEE Trans. Signal Process., 2014)

A Perspective on Future Research Directions in Information Theory. - Jeffrey G. Andrews; Alexandros G. Dimakis; Lara Dolecek; Michelle Effros; Muriel Médard; Olgica Milenkovic; Andrea Montanari; Sriram Vishwanath; Edmund M. Yeh; Randall Berry; Ken R. Duffy; Soheil Feizi; et al. (CoRR, 2015)

Integrative analysis of 111 reference human epigenomes Open. - Roadmap Epigenomics Consortium; Anshul Kundaje; Wouter Meuleman; Jason Ernst; Misha Bilenky; Angela Yen; Alireza Heravi Moussavi; Pouya Kheradpour; ZhiZhuo Zhang; Jianrong Wang; Michael J. Ziller; Viren Amin; et al. (Nat., 2015)

Spectral Alignment of Networks. - Soheil Feizi; Gerald T. Quon; Mariana Recamonde Mendoza; Muriel Médard; Manolis Kellis; Ali Jadbabaie (CoRR, 2016)

On the analysis of complex networks: fundamental limits, scalable algorithms, and applications. - Soheil Feizi-Khankandi (2016)

A memristor based binary multiplier. - Saeed Haghiri; Ali Nemati; Soheil Feizi; Amirali Amirsoleimani; Arash Ahmadi; Majid Ahmadi (CCECE, 2017)

Tensor Biclustering. - Soheil Feizi; Hamid Javadi; David Tse (NIPS, 2017)

Maximally Correlated Principal Component Analysis. - Soheil Feizi; David Tse (CoRR, 2017)

Porcupine Neural Networks: (Almost) All Local Optima are Global. - Soheil Feizi; Hamid Javadi; Jesse M. Zhang; David Tse (CoRR, 2017)

Understanding GANs: the LQG Setting. - Soheil Feizi; Changho Suh; Fei Xia 002; David Tse (CoRR, 2017)

Network Maximal Correlation. - Soheil Feizi; Ali Makhdoumi; Ken Duffy; Manolis Kellis; Muriel Médard (IEEE Trans. Netw. Sci. Eng., 2017)

Porcupine Neural Networks: Approximating Neural Network Landscapes. - Soheil Feizi; Hamid Javadi; Jesse M. Zhang; David Tse (NeurIPS, 2018)

Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation. - Yogesh Balaji; Rama Chellappa; Soheil Feizi (ICCV, 2019)

Are adversarial examples inevitable? - Ali Shafahi; W. Ronny Huang; Christoph Studer; Soheil Feizi; Tom Goldstein (ICLR (Poster), 2019)

Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs. - Yogesh Balaji; Hamed Hassani; Rama Chellappa; Soheil Feizi (ICML, 2019)

Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation. - Sahil Singla 002; Eric Wallace; Shi Feng 005; Soheil Feizi (ICML, 2019)

Quantum Wasserstein Generative Adversarial Networks. - Shouvanik Chakrabarti; Yiming Huang; Tongyang Li; Soheil Feizi; Xiaodi Wu 001 (NeurIPS, 2019)

Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks. - Aya Abdelsalam Ismail; Mohamed K. Gunady; Luiz Pessoa; Héctor Corrada Bravo; Soheil Feizi (NeurIPS, 2019)

Functional Adversarial Attacks. - Cassidy Laidlaw; Soheil Feizi (NeurIPS, 2019)

Compressing GANs using Knowledge Distillation. - Angeline Aguinaldo; Ping-Yeh Chiang; Alexander Gain; Ameya Patil; Kolten Pearson; Soheil Feizi (CoRR, 2019)

Normalized Wasserstein Distance for Mixture Distributions with Applications in Adversarial Learning and Domain Adaptation. - Yogesh Balaji; Rama Chellappa; Soheil Feizi (CoRR, 2019)

Robustness Certificates Against Adversarial Examples for ReLU Networks. - Sahil Singla 002; Soheil Feizi (CoRR, 2019)

Certifiably Robust Interpretation in Deep Learning. - Alexander Levine 001; Sahil Singla 002; Soheil Feizi (CoRR, 2019)

Interpretable Adversarial Training for Text. - Samuel Barham; Soheil Feizi (CoRR, 2019)

Strong Baseline Defenses Against Clean-Label Poisoning Attacks. - Neal Gupta; W. Ronny Huang; Liam Fowl; Chen Zhu 001; Soheil Feizi; Tom Goldstein; John P. Dickerson (CoRR, 2019)

Bounding Singular Values of Convolution Layers. - Sahil Singla 002; Soheil Feizi (CoRR, 2019)

Playing it Safe: Adversarial Robustness with an Abstain Option. - Cassidy Laidlaw; Soheil Feizi (CoRR, 2019)

Network Infusion to Infer Information Sources in Networks. - Soheil Feizi; Muriel Médard; Gerald T. Quon; Manolis Kellis; Ken Duffy (IEEE Trans. Netw. Sci. Eng., 2019)

Adversarially Robust Distillation. - Micah Goldblum; Liam Fowl; Soheil Feizi; Tom Goldstein (AAAI, 2020)

Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation. - Alexander Levine 001; Soheil Feizi (AAAI, 2020)

Maximum Likelihood Embedding of Logistic Random Dot Product Graphs. - Luke J. O'Connor; Muriel Médard; Soheil Feizi (AAAI, 2020)

Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks. - Alexander Levine 001; Soheil Feizi (AISTATS, 2020)

Adversarial Robustness of Flow-Based Generative Models. - Phillip Pope; Yogesh Balaji; Soheil Feizi (AISTATS, 2020)

Deep k-NN Defense Against Clean-Label Data Poisoning Attacks. - Neehar Peri; Neal Gupta; W. Ronny Huang; Liam Fowl; Chen Zhu 001; Soheil Feizi; Tom Goldstein; John P. Dickerson (ECCV Workshops (1), 2020)

Second-Order Provable Defenses against Adversarial Attacks. - Sahil Singla 002; Soheil Feizi (ICML, 2020)

On Second-Order Group Influence Functions for Black-Box Predictions. - Samyadeep Basu; Xuchen You; Soheil Feizi (ICML, 2020)

Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness. - Aounon Kumar; Alexander Levine 001; Tom Goldstein; Soheil Feizi (ICML, 2020)

(De)Randomized Smoothing for Certifiable Defense against Patch Attacks. - Alexander Levine 001; Soheil Feizi (NeurIPS, 2020)

Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation. - Yogesh Balaji; Rama Chellappa; Soheil Feizi (NeurIPS, 2020)

Benchmarking Deep Learning Interpretability in Time Series Predictions. - Aya Abdelsalam Ismail; Mohamed K. Gunady; Héctor Corrada Bravo; Soheil Feizi (NeurIPS, 2020)

Certifying Confidence via Randomized Smoothing. - Aounon Kumar; Alexander Levine 001; Soheil Feizi; Tom Goldstein (NeurIPS, 2020)

Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks. - Wei-An Lin; Chun Pong Lau 001; Alexander Levine 001; Rama Chellappa; Soheil Feizi (NeurIPS, 2020)

Subadditivity of Probability Divergences on Bayes-Nets with Applications to Time Series GANs. - Mucong Ding; Constantinos Daskalakis; Soheil Feizi (CoRR, 2020)

Mirrored Autoencoders with Simplex Interpolation for Unsupervised Anomaly Detection. - Yexin Wu; Yogesh Balaji; Bhanukiran Vinzamuri; Soheil Feizi (CoRR, 2020)

Deep Partition Aggregation: Provable Defense against General Poisoning Attacks. - Alexander Levine 001; Soheil Feizi (CoRR, 2020)

GANs with Variational Entropy Regularizers: Applications in Mitigating the Mode-Collapse Issue. - Pirazh Khorramshahi; Hossein Souri; Rama Chellappa; Soheil Feizi (CoRR, 2020)

Tight Second-Order Certificates for Randomized Smoothing. - Alexander Levine 001; Aounon Kumar; Thomas A. Goldstein; Soheil Feizi (CoRR, 2020)

Understanding GANs in the LQG Setting: Formulation, Generalization and Stability. - Soheil Feizi; Farzan Farnia; Tony Ginart; David Tse (IEEE J. Sel. Areas Inf. Theory, 2020)

Spectral Alignment of Graphs. - Soheil Feizi; Gerald T. Quon; Mariana Recamonde Mendoza; Muriel Médard; Manolis Kellis; Ali Jadbabaie (IEEE Trans. Netw. Sci. Eng., 2020)

Winning Lottery Tickets in Deep Generative Models. - Neha Mukund Kalibhat; Yogesh Balaji; Soheil Feizi (AAAI, 2021)

GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences. - Mucong Ding; Constantinos Daskalakis; Soheil Feizi (AISTATS, 2021)

Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. - Vedant Nanda; Samuel Dooley; Sahil Singla 002; Soheil Feizi; John P. Dickerson (FAccT, 2021)

Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings. - Mazda Moayeri; Soheil Feizi (ICCV, 2021)

Low Curvature Activations Reduce Overfitting in Adversarial Training. - Vasu Singla; Sahil Singla 002; Soheil Feizi; David Jacobs 001 (ICCV, 2021)

Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks. - Alexander Levine 001; Soheil Feizi (ICLR, 2021)

Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers. - Sahil Singla 002; Soheil Feizi (ICLR, 2021)

Understanding Over-parameterization in Generative Adversarial Networks. - Yogesh Balaji; Mohammadmahdi Sajedi; Neha Mukund Kalibhat; Mucong Ding; Dominik Stöger; Mahdi Soltanolkotabi; Soheil Feizi (ICLR, 2021)

Influence Functions in Deep Learning Are Fragile. - Samyadeep Basu; Phillip Pope; Soheil Feizi (ICLR, 2021)

Perceptual Adversarial Robustness: Defense Against Unseen Threat Models. - Cassidy Laidlaw; Sahil Singla 002; Soheil Feizi (ICLR, 2021)

Improved, Deterministic Smoothing for L1 Certified Robustness. - Alexander Levine 001; Soheil Feizi (ICML, 2021)

Skew Orthogonal Convolutions. - Sahil Singla 002; Soheil Feizi (ICML, 2021)

Improving Deep Learning Interpretability by Saliency Guided Training. - Aya Abdelsalam Ismail; Héctor Corrada Bravo; Soheil Feizi (NeurIPS, 2021)

Unsupervised anomaly detection with adversarial mirrored autoencoders. - Gowthami Somepalli; Yexin Wu; Yogesh Balaji; Bhanukiran Vinzamuri; Soheil Feizi (UAI, 2021)

Improved, Deterministic Smoothing for L1 Certified Robustness. - Alexander Levine 001; Soheil Feizi (CoRR, 2021)

Understanding Overparameterization in Generative Adversarial Networks. - Yogesh Balaji; Mohammadmahdi Sajedi; Neha Mukund Kalibhat; Mucong Ding; Dominik Stöger; Mahdi Soltanolkotabi; Soheil Feizi (CoRR, 2021)

Householder Activations for Provable Robustness against Adversarial Attacks. - Sahil Singla 002; Surbhi Singla; Soheil Feizi (CoRR, 2021)

Causal ImageNet: How to discover spurious features in Deep Learning? - Sahil Singla 002; Soheil Feizi (CoRR, 2021)

On Hard Episodes in Meta-Learning. - Samyadeep Basu; Amr Sharaf; Nicolò Fusi; Soheil Feizi (CoRR, 2021)

Provable Adversarial Robustness for Fractional Lp Threat Models. - Alexander Levine 001; Soheil Feizi (AISTATS, 2022)

Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection. - Jiang Liu 014; Alexander Levine 001; Chun Pong Lau 001; Rama Chellappa; Soheil Feizi (CVPR, 2022)

A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes. - Mazda Moayeri; Phillip Pope; Yogesh Balaji; Soheil Feizi (CVPR, 2022)

Salient ImageNet: How to discover spurious features in Deep Learning? - Sahil Singla 002; Soheil Feizi (ICLR, 2022)

Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100. - Sahil Singla 002; Surbhi Singla; Soheil Feizi (ICLR, 2022)

Policy Smoothing for Provably Robust Reinforcement Learning. - Aounon Kumar; Alexander Levine 001; Soheil Feizi (ICLR, 2022)

Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation. - Wenxiao Wang 002; Alexander Levine 001; Soheil Feizi (ICML, 2022)

FOCUS: Familiar Objects in Common and Uncommon Settings. - Priyatham Kattakinda; Soheil Feizi (ICML, 2022)

Lethal Dose Conjecture on Data Poisoning. - Wenxiao Wang 002; Alexander Levine 001; Soheil Feizi (NeurIPS, 2022)

Improved techniques for deterministic l2 robustness. - Sahil Singla 002; Soheil Feizi (NeurIPS, 2022)

Hard ImageNet: Segmentations for Objects with Strong Spurious Cues. - Mazda Moayeri; Sahil Singla 002; Soheil Feizi (NeurIPS, 2022)

Explicit Tradeoffs between Adversarial and Natural Distributional Robustness. - Mazda Moayeri; Kiarash Banihashem; Soheil Feizi (NeurIPS, 2022)

Toward Efficient Robust Training against Union of $ ell_p$ Threat Models. - Gaurang Sriramanan; Maharshi Gor; Soheil Feizi (NeurIPS, 2022)

Certifying Model Accuracy under Distribution Shifts. - Aounon Kumar; Alexander Levine 001; Tom Goldstein; Soheil Feizi (CoRR, 2022)

Understanding Failure Modes of Self-Supervised Learning. - Neha Mukund Kalibhat; Kanika Narang; Liang Tan 005; Hamed Firooz; Maziar Sanjabi; Soheil Feizi (CoRR, 2022)

Core Risk Minimization using Salient ImageNet. - Sahil Singla 002; Mazda Moayeri; Soheil Feizi (CoRR, 2022)

Interpretable Mixture of Experts for Structured Data. - Aya Abdelsalam Ismail; Sercan Ö. Arik; Jinsung Yoon; Ankur Taly; Soheil Feizi; Tomas Pfister (CoRR, 2022)

Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems. - Yanchao Sun; Ruijie Zheng; Parisa Hassanzadeh; Yongyuan Liang; Soheil Feizi; Sumitra Ganesh; Furong Huang (CoRR, 2022)

Data-Centric Debugging: mitigating model failures via targeted data collection. - Sahil Singla 002; Atoosa Malemir Chegini; Mazda Moayeri; Soheil Feizi (CoRR, 2022)

Invariant Learning via Diffusion Dreamed Distribution Shifts. - Priyatham Kattakinda; Alexander Levine 001; Soheil Feizi (CoRR, 2022)

Towards Better Input Masking for Convolutional Neural Networks. - Sriram Balasubramanian; Soheil Feizi (CoRR, 2022)

Spuriosity Rankings: Sorting Data for Spurious Correlation Robustness. - Mazda Moayeri; Wenxiao Wang 002; Sahil Singla 002; Soheil Feizi (CoRR, 2022)

Mutual Adversarial Training: Learning Together is Better Than Going Alone. - Jiang Liu 014; Chun Pong Lau 001; Hossein Souri; Soheil Feizi; Rama Chellappa (IEEE Trans. Inf. Forensics Secur., 2022)

Goal-Conditioned Q-learning as Knowledge Distillation. - Alexander Levine 001; Soheil Feizi (AAAI, 2023)

Adapting Self-Supervised Representations to Multi-Domain Setups. - Neha Mukund Kalibhat; Samuel Sharpe; Jeremy Goodsitt; C. Bayan Bruss; Soheil Feizi (BMVC, 2023)

Text2Concept: Concept Activation Vectors Directly from Text. - Mazda Moayeri; Keivan Rezaei; Maziar Sanjabi; Soheil Feizi (CVPR Workshops, 2023)

CUDA: Convolution-Based Unlearnable Datasets. - Vinu Sankar Sadasivan; Mahdi Soltanolkotabi; Soheil Feizi (CVPR, 2023)

Towards Improved Input Masking for Convolutional Neural Networks. - Sriram Balasubramanian; Soheil Feizi (ICCV, 2023)

Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult Tasks. - Samyadeep Basu; Megan Stanley; John Bronskill; Soheil Feizi; Daniela Massiceti (ICLR, 2023)

Provable Robustness against Wasserstein Distribution Shifts via Input Randomization. - Aounon Kumar; Alexander Levine 001; Tom Goldstein; Soheil Feizi (ICLR, 2023)

Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication. - Yanchao Sun; Ruijie Zheng; Parisa Hassanzadeh; Yongyuan Liang; Soheil Feizi; Sumitra Ganesh; Furong Huang (ICLR, 2023)

Identifying Interpretable Subspaces in Image Representations. - Neha Mukund Kalibhat; Shweta Bhardwaj; C. Bayan Bruss; Hamed Firooz; Maziar Sanjabi; Soheil Feizi (ICML, 2023)

Text-To-Concept (and Back) via Cross-Model Alignment. - Mazda Moayeri; Keivan Rezaei; Maziar Sanjabi; Soheil Feizi (ICML, 2023)

Run-off Election: Improved Provable Defense against Data Poisoning Attacks. - Keivan Rezaei; Kiarash Banihashem; Atoosa Malemir Chegini; Soheil Feizi (ICML, 2023)

Temporal Robustness against Data poisoning. - Wenxiao Wang 002; Soheil Feizi (NeurIPS, 2023)

Exploring Geometry of Blind Spots in Vision models. - Sriram Balasubramanian; Gaurang Sriramanan; Vinu Sankar Sadasivan; Soheil Feizi (NeurIPS, 2023)

Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases. - Mazda Moayeri; Wenxiao Wang 002; Sahil Singla 002; Soheil Feizi (NeurIPS, 2023)

Diffused Redundancy in Pre-trained Representations. - Vedant Nanda; Till Speicher; John P. Dickerson; Krishna P. Gummadi; Soheil Feizi; Adrian Weller (NeurIPS, 2023)

Can AI-Generated Text be Reliably Detected? - Vinu Sankar Sadasivan; Aounon Kumar; Sriram Balasubramanian; Wenxiao Wang 002; Soheil Feizi (CoRR, 2023)

Adversarial Robustness of Learning-based Static Malware Classifiers. - Shoumik Saha; Wenxiao Wang 002; Yigitcan Kaya; Soheil Feizi (CoRR, 2023)

Provable Robustness for Streaming Models with a Sliding Window. - Aounon Kumar; Vinu Sankar Sadasivan; Soheil Feizi (CoRR, 2023)

On Practical Aspects of Aggregation Defenses against Data Poisoning Attacks. - Wenxiao Wang 002; Soheil Feizi (CoRR, 2023)

Augmenting CLIP with Improved Visio-Linguistic Reasoning. - Samyadeep Basu; Maziar Sanjabi; Daniela Massiceti; Shell Xu Hu; Soheil Feizi (CoRR, 2023)

Identifying and Mitigating the Security Risks of Generative AI. - Clark W. Barrett; Brad Boyd; Ellie Burzstein; Nicholas Carlini; Brad Chen; Jihye Choi; Amrita Roy Chowdhury 001; Mihai Christodorescu; Anupam Datta; Soheil Feizi; Kathleen Fisher; Tatsunori Hashimoto; et al. (CoRR, 2023)

Certifying LLM Safety against Adversarial Prompting. - Aounon Kumar; Chirag Agarwal; Suraj Srinivas; Soheil Feizi; Hima Lakkaraju (CoRR, 2023)

EditVal: Benchmarking Diffusion Based Text-Guided Image Editing Methods. - Samyadeep Basu; Mehrdad Saberi; Shweta Bhardwaj; Atoosa Malemir Chegini; Daniela Massiceti; Maziar Sanjabi; Shell Xu Hu; Soheil Feizi (CoRR, 2023)

Online Advertisements with LLMs: Opportunities and Challenges. - Soheil Feizi; MohammadTaghi Hajiaghayi; Keivan Rezaei; Suho Shin 001 (CoRR, 2023)

Instruct2Attack: Language-Guided Semantic Adversarial Attacks. - Jiang Liu 014; Chen Wei; Yuxiang Guo 001; Heng Yu 005; Alan L. Yuille; Soheil Feizi; Chun Pong Lau 001; Rama Chellappa (CoRR, 2023)

Identifying and Mitigating Model Failures through Few-shot CLIP-aided Diffusion Generation. - Atoosa Malemir Chegini; Soheil Feizi (CoRR, 2023)

Identifying and Mitigating the Security Risks of Generative AI. - Clark W. Barrett; Brad Boyd; Elie Bursztein; Nicholas Carlini; Brad Chen; Jihye Choi; Amrita Roy Chowdhury 001; Mihai Christodorescu; Anupam Datta; Soheil Feizi; Kathleen Fisher; Tatsunori Hashimoto; et al. (Found. Trends Priv. Secur., 2023)

Interpretable Mixture of Experts. - Aya Abdelsalam Ismail; Sercan Ö. Arik; Jinsung Yoon; Ankur Taly; Soheil Feizi; Tomas Pfister (Trans. Mach. Learn. Res., 2023)

Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses. - Chun Pong Lau 001; Jiang Liu 014; Hossein Souri; Wei-An Lin; Soheil Feizi; Rama Chellappa (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Strong Baselines for Parameter-Efficient Few-Shot Fine-Tuning. - Samyadeep Basu; Shell Xu Hu; Daniela Massiceti; Soheil Feizi (AAAI, 2024)

Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features. - Neha Mukund Kalibhat; Kanika Narang; Hamed Firooz; Maziar Sanjabi; Soheil Feizi (AAAI, 2024)

Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP. - Samyadeep Basu; Shell Xu Hu; Maziar Sanjabi; Daniela Massiceti; Soheil Feizi (EMNLP, 2024)

IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning. - Soumya Suvra Ghosal; Samyadeep Basu; Soheil Feizi; Dinesh Manocha (EMNLP, 2024)

WorldBench: Quantifying Geographic Disparities in LLM Factual Recall. - Mazda Moayeri; Elham Tabassi; Soheil Feizi (FAccT, 2024)

Localizing and Editing Knowledge In Text-to-Image Generative Models. - Samyadeep Basu; Nanxuan Zhao; Vlad I. Morariu; Soheil Feizi; Varun Manjunatha (ICLR, 2024)

PRIME: Prioritizing Interpretability in Failure Mode Extraction. - Keivan Rezaei; Mehrdad Saberi; Mazda Moayeri; Soheil Feizi (ICLR, 2024)

Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks. - Mehrdad Saberi; Vinu Sankar Sadasivan; Keivan Rezaei; Aounon Kumar; Atoosa Malemir Chegini; Wenxiao Wang 002; Soheil Feizi (ICLR, 2024)

DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness. - Shoumik Saha; Wenxiao Wang 002; Yigitcan Kaya; Soheil Feizi; Tudor Dumitras (ICLR, 2024)

On Mechanistic Knowledge Localization in Text-to-Image Generative Models. - Samyadeep Basu; Keivan Rezaei; Priyatham Kattakinda; Vlad I. Morariu; Nanxuan Zhao; Ryan A. Rossi; Varun Manjunatha; Soheil Feizi (ICML, 2024)

Fast Adversarial Attacks on Language Models In One GPU Minute. - Vinu Sankar Sadasivan; Shoumik Saha; Gaurang Sriramanan; Priyatham Kattakinda; Atoosa Malemir Chegini; Soheil Feizi (ICML, 2024)

Decomposing and Interpreting Image Representations via Text in ViTs Beyond CLIP. - Sriram Balasubramanian; Samyadeep Basu; Soheil Feizi (NeurIPS, 2024)

Understanding Information Storage and Transfer in Multi-Modal Large Language Models. - Samyadeep Basu; Martin Grayson; Cecily Morrison; Besmira Nushi; Soheil Feizi; Daniela Massiceti (NeurIPS, 2024)

Loki: Low-rank Keys for Efficient Sparse Attention. - Prajwal Singhania; Siddharth Singh; Shwai He; Soheil Feizi; Abhinav Bhatele (NeurIPS, 2024)

LLM-Check: Investigating Detection of Hallucinations in Large Language Models. - Gaurang Sriramanan; Siddhant Bharti; Vinu Sankar Sadasivan; Shoumik Saha; Priyatham Kattakinda; Soheil Feizi (NeurIPS, 2024)

Data-Centric Debugging: mitigating model failures via targeted image retrieval. - Sahil Singla 002; Atoosa Malemir Chegini; Mazda Moayeri; Soheil Feizi (WACV, 2024)

What do we learn from inverting CLIP models? - Hamid Kazemi; Atoosa Malemir Chegini; Jonas Geiping; Soheil Feizi; Tom Goldstein (CoRR, 2024)

On Mechanistic Knowledge Localization in Text-to-Image Generative Models. - Samyadeep Basu; Keivan Rezaei; Priyatham Kattakinda; Ryan A. Rossi; Cherry Zhao; Vlad I. Morariu; Varun Manjunatha; Soheil Feizi (CoRR, 2024)

Understanding the Effect of using Semantically Meaningful Tokens for Visual Representation Learning. - Neha Mukund Kalibhat; Priyatham Kattakinda; Arman Zarei; Nikita Seleznev; Samuel Sharpe; Senthil Kumar; Soheil Feizi (CoRR, 2024)

DREW : Towards Robust Data Provenance by Leveraging Error-Controlled Watermarking. - Mehrdad Saberi; Vinu Sankar Sadasivan; Arman Zarei; Hessam Mahdavifar; Soheil Feizi (CoRR, 2024)

Understanding and Mitigating Compositional Issues in Text-to-Image Generative Models. - Arman Zarei; Keivan Rezaei; Samyadeep Basu; Mehrdad Saberi; Mazda Moayeri; Priyatham Kattakinda; Soheil Feizi (CoRR, 2024)

Endor: Hardware-Friendly Sparse Format for Offloaded LLM Inference. - Donghyeon Joo; Ramyad Hadidi; Soheil Feizi; Bahar Asgari (CoRR, 2024)

RESTOR: Knowledge Recovery through Machine Unlearning. - Keivan Rezaei; Khyathi Raghavi Chandu; Soheil Feizi; Yejin Choi 001; Faeze Brahman; Abhilasha Ravichander (CoRR, 2024)

Securing the Future of GenAI: Policy and Technology. - Mihai Christodorescu; Ryan Craven; Soheil Feizi; Neil Zhenqiang Gong; Mia Hoffmann; Somesh Jha; Zhengyuan Jiang; Mehrdad Saberi Kamarposhti; John C. Mitchell; Jessica Newman; Emelia Probasco; Yanjun Qi; et al. (IACR Cryptol. ePrint Arch., 2024)

RePanda: Pandas-powered Tabular Verification and Reasoning. - Atoosa Malemir Chegini; Keivan Rezaei; Hamid Eghbalzadeh; Soheil Feizi (ACL (1), 2025)

Almost AI, Almost Human: The Challenge of Detecting AI-Polished Writing. - Shoumik Saha; Soheil Feizi (ACL (Findings), 2025)

Understanding the Effect of using Semantically Meaningful Tokens for Visual Representation Learning. - Neha Mukund Kalibhat; Priyatham Kattakinda; Sumit Nawathe; Arman Zarei; Nikita Seleznev; Samuel Sharpe; Senthil Kumar; Soheil Feizi (CVPR Workshops, 2025)

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings. - Samuel Audia; Soheil Feizi; Matthias Zwicker; Dinesh Manocha (ICLR, 2025)

Rethinking Artistic Copyright Infringements In the Era Of Text-to-Image Generative Models. - Mazda Moayeri; Sriram Balasubramanian; Samyadeep Basu; Priyatham Kattakinda; Atoosa Malemir Chegini; Robert Brauneis; Soheil Feizi (ICLR, 2025)

Unearthing Skill-level Insights for Understanding Trade-offs of Foundation Models. - Mazda Moayeri; Vidhisha Balachandran; Varun Chandrasekaran; Safoora Yousefi; Thomas Fel; Soheil Feizi; Besmira Nushi; Neel Joshi; Vibhav Vineet (ICLR, 2025)

Mitigating Compositional Failures in Text-to-Image Models with Causal Text Embedding Refinement. - Arman Zarei; Keivan Rezaei; Samyadeep Basu; Mehrdad Saberi; Mazda Moayeri; Priyatham Kattakinda; Adrienne Raglin; Anjon Basak; Soheil Feizi (PerCom Workshops, 2025)

RESTOR: Knowledge Recovery in Machine Unlearning. - Keivan Rezaei; Khyathi Raghavi Chandu; Soheil Feizi; Yejin Choi 001; Faeze Brahman; Abhilasha Ravichander (Trans. Mach. Learn. Res., 2025)

Can AI-Generated Text be Reliably Detected? Stress Testing AI Text Detectors Under Various Attacks. - Vinu Sankar Sadasivan; Aounon Kumar; Sriram Balasubramanian; Wenxiao Wang 002; Soheil Feizi (Trans. Mach. Learn. Res., 2025)

On Mechanistic Circuits for Extractive Question-Answering. - Samyadeep Basu; Vlad I. Morariu; Zichao Wang 001; Ryan A. Rossi; Cherry Zhao; Soheil Feizi; Varun Manjunatha (CoRR, 2025)

A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models. - Zihao Lin 003; Samyadeep Basu; Mohammad Beigi; Varun Manjunatha; Ryan A. Rossi; Zichao Wang 001; Yufan Zhou 001; Sriram Balasubramanian; Arman Zarei; Keivan Rezaei; Ying Shen 006; Barry Menglong Yao; et al. (CoRR, 2025)

Seeing What's Not There: Spurious Correlation in Multimodal LLMs. - Parsa Hosseini; Sumit Nawathe; Mazda Moayeri; Sriram Balasubramanian; Soheil Feizi (CoRR, 2025)

Chain-of-Defensive-Thought: Structured Reasoning Elicits Robustness in Large Language Models against Reference Corruption. - Wenxiao Wang 002; Parsa Hosseini; Soheil Feizi (CoRR, 2025)

Gaming Tool Preferences in Agentic LLMs. - Kazem Faghih; Wenxiao Wang 002; Yize Cheng; Siddhant Bharti; Gaurang Sriramanan; Sriram Balasubramanian; Parsa Hosseini; Soheil Feizi (CoRR, 2025)

Localizing Knowledge in Diffusion Transformers. - Arman Zarei; Samyadeep Basu; Keivan Rezaei; Zihao Lin 003; Sayan Nag; Soheil Feizi (CoRR, 2025)

DyePack: Provably Flagging Test Set Contamination in LLMs Using Backdoors. - Yize Cheng; Wenxiao Wang 002; Mazda Moayeri; Soheil Feizi (CoRR, 2025)

A Closer Look at Bias and Chain-of-Thought Faithfulness of Large (Vision) Language Models. - Sriram Balasubramanian; Samyadeep Basu; Soheil Feizi (CoRR, 2025)

Adversarial Paraphrasing: A Universal Attack for Humanizing AI-Generated Text. - Yize Cheng; Vinu Sankar Sadasivan; Mehrdad Saberi; Shoumik Saha; Soheil Feizi (CoRR, 2025)

Model State Arithmetic for Machine Unlearning. - Keivan Rezaei; Mehrdad Saberi; Abhilasha Ravichander; Soheil Feizi (CoRR, 2025)

Attacker's Noise Can Manipulate Your Audio-based LLM in the Real World. - Vinu Sankar Sadasivan; Soheil Feizi; Rajiv Mathews; Lun Wang (CoRR, 2025)

IConMark: Robust Interpretable Concept-Based Watermark For AI Images. - Vinu Sankar Sadasivan; Mehrdad Saberi; Soheil Feizi (CoRR, 2025)