Vikram V. Ramaswamy

17 papers A* 5Journal 9Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Attention IoU: Examining Biases in CelebA using Attention Maps. CVPR Aaron Serianni, Tyler Zhu, Olga Russakovsky, Vikram V. Ramaswamy
2025	J	`jnl`	Attention IoU: Examining Biases in CelebA using Attention Maps. CoRR Aaron Serianni, Tyler Zhu, Olga Russakovsky, Vikram V. Ramaswamy
2023	J	`jnl`	Beyond web-scraping: Crowd-sourcing a geographically diverse image dataset. CoRR Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron B. Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky
2023	A*	`conf`	Gender Artifacts in Visual Datasets. ICCV Nicole Meister, Dora Zhao, Angelina Wang, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
2023	A*	`conf`	GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition. NeurIPS Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky
2023	A*	`conf`	Overlooked Factors in Concept-Based Explanations: Dataset Choice, Concept Learnability, and Human Capability. CVPR Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky
2023	—	`—`	Tackling Bias within Computer Vision Models Vikram V. Ramaswamy
2023	J	`jnl`	UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs. CoRR Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky
2022	J	`jnl`	ELUDE: Generating interpretable explanations via a decomposition into labelled and unlabelled features. CoRR Vikram V. Ramaswamy, Sunnie S. Y. Kim, Nicole Meister, Ruth Fong, Olga Russakovsky
2022	J	`jnl`	Gender Artifacts in Visual Datasets. CoRR Nicole Meister, Dora Zhao, Angelina Wang, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
2022	—	`conf`	HIVE: Evaluating the Human Interpretability of Visual Explanations. ECCV (12) Sunnie S. Y. Kim, Nicole Meister, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
2022	J	`jnl`	Overlooked factors in concept-based explanations: Dataset choice, concept salience, and human capability. CoRR Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky
2022	—	`conf`	Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation. FAccT Angelina Wang, Vikram V. Ramaswamy, Olga Russakovsky
2022	J	`jnl`	Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation. CoRR Angelina Wang, Vikram V. Ramaswamy, Olga Russakovsky
2021	A*	`conf`	Fair Attribute Classification Through Latent Space De-Biasing. CVPR Vikram V. Ramaswamy, Sunnie S. Y. Kim, Olga Russakovsky
2021	J	`jnl`	HIVE: Evaluating the Human Interpretability of Visual Explanations. CoRR Sunnie S. Y. Kim, Nicole Meister, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
2020	J	`jnl`	Fair Attribute Classification through Latent Space De-biasing. CoRR Vikram V. Ramaswamy, Sunnie S. Y. Kim, Olga Russakovsky