Neural Symbolic Music Genre Transfer Insights. - Gino Brunner; Mazda Moayeri; Oliver Richter; Roger Wattenhofer; Chi Zhang (PKDD/ECML Workshops (2), 2019)

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

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

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

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

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

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

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

A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation. - Thomas Fel; Victor Boutin; Louis Béthune; Rémi Cadène; Mazda Moayeri; Léo Andéol; Mathieu Chalvidal; Thomas Serre (NeurIPS, 2023)

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

Embracing Diversity: Interpretable Zero-shot Classification Beyond One Vector Per Class. - Mazda Moayeri; Michael Rabbat; Mark Ibrahim; Diane Bouchacourt (FAccT, 2024)

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

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

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

An Introduction to Vision-Language Modeling. - Florian Bordes; Richard Yuanzhe Pang; Anurag Ajay; Alexander C. Li; Adrien Bardes; Suzanne Petryk; Oscar Mañas; Zhiqiu Lin; Anas Mahmoud 002; Bargav Jayaraman; Mark Ibrahim; Melissa Hall; et al. (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)

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)

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