Ruth Fong

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 34

Top Topics

Human Perceptual

Artificially Intelligent

Visual Concepts

Top Venues

Publications

Sunnie S. Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong, Andrés Monroy-Hernández
"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction. CHI (2023)
Nicole Meister, Dora Zhao, Angelina Wang, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
Gender Artifacts in Visual Datasets. ICCV (2023)
Sunnie S. Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong, Andrés Monroy-Hernández
Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application. FAccT (2023)
Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky
UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs. CoRR (2023)
Sunnie S. Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong, Andrés Monroy-Hernández
Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application. CoRR (2023)
Indu Panigrahi, Ryan Manzuk, Adam Maloof, Ruth Fong
Improving Data-Efficient Fossil Segmentation via Model Editing. CVPR Workshops (2023)
Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky
Overlooked Factors in Concept-Based Explanations: Dataset Choice, Concept Learnability, and Human Capability. CVPR (2023)
Indu Panigrahi, Ryan Manzuk, Adam Maloof, Ruth Fong
Improving Fine-Grain Segmentation via Interpretable Modifications: A Case Study in Fossil Segmentation. CoRR (2022)
Vikram V. Ramaswamy, Sunnie S. Y. Kim, Nicole Meister, Ruth Fong, Olga Russakovsky
ELUDE: Generating interpretable explanations via a decomposition into labelled and unlabelled features. CoRR (2022)
Nicole Meister, Dora Zhao, Angelina Wang, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
Gender Artifacts in Visual Datasets. CoRR (2022)
Sunnie S. Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong, Andrés Monroy-Hernández
"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction. CoRR (2022)
Sunnie S. Y. Kim, Nicole Meister, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
HIVE: Evaluating the Human Interpretability of Visual Explanations. ECCV (12) (2022)
Devon Ulrich, Ruth Fong
Interactive Visual Feature Search. CoRR (2022)
Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky
Overlooked factors in concept-based explanations: Dataset choice, concept salience, and human capability. CoRR (2022)
Mandela Patrick, Yuki Markus Asano, Polina Kuznetsova, Ruth Fong, João F. Henriques, Geoffrey Zweig, Andrea Vedaldi
On Compositions of Transformations in Contrastive Self-Supervised Learning. ICCV (2021)
Sunnie S. Y. Kim, Nicole Meister, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
HIVE: Evaluating the Human Interpretability of Visual Explanations. CoRR (2021)
Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Andrea Vedaldi
There and Back Again: Revisiting Backpropagation Saliency Methods. CoRR (2020)
Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield, Gretchen Krueger, Gillian K. Hadfield, Heidy Khlaaf, Jingying Yang, Helen Toner, Ruth Fong, Tegan Maharaj, Pang Wei Koh, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O'Keefe, Mark Koren, Théo Ryffel, J. B. Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif Khan, Yoshua Bengio, Markus Anderljung
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. CoRR (2020)
Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek
xxAI - Beyond Explainable Artificial Intelligence. xxAI@ICML (2020)
Kurtis Evan David, Qiang Liu, Ruth Fong
Debiasing Convolutional Neural Networks via Meta Orthogonalization. CoRR (2020)
Diego Marcos, Ruth Fong, Sylvain Lobry, Rémi Flamary, Nicolas Courty, Devis Tuia
Contextual Semantic Interpretability. CoRR (2020)
Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Andrea Vedaldi
There and Back Again: Revisiting Backpropagation Saliency Methods. CVPR (2020)
Iro Laina, Ruth Fong, Andrea Vedaldi
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning. NeurIPS (2020)
Mandela Patrick, Yuki Markus Asano, Ruth Fong, João F. Henriques, Geoffrey Zweig, Andrea Vedaldi
Multi-modal Self-Supervision from Generalized Data Transformations. CoRR (2020)
Diego Marcos, Ruth Fong, Sylvain Lobry, Rémi Flamary, Nicolas Courty, Devis Tuia
Contextual Semantic Interpretability. ACCV (4) (2020)
Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Hakan Bilen, Andrea Vedaldi
NormGrad: Finding the Pixels that Matter for Training. CoRR (2019)
Ruth Fong, Mandela Patrick, Andrea Vedaldi
Understanding Deep Networks via Extremal Perturbations and Smooth Masks. ICCV (2019)
Ruth Fong, Mandela Patrick, Andrea Vedaldi
Understanding Deep Networks via Extremal Perturbations and Smooth Masks. CoRR (2019)
Ruth Fong, Andrea Vedaldi
Occlusions for Effective Data Augmentation in Image Classification. CoRR (2019)
Ruth Fong
Occlusions for Effective Data Augmentation in Image Classification. ICCV Workshops (2019)
Ruth Fong, Andrea Vedaldi
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks. CoRR (2018)
Ruth Fong, Andrea Vedaldi
Net2Vec: Quantifying and Explaining How Concepts Are Encoded by Filters in Deep Neural Networks. CVPR (2018)
Ruth Fong, Walter J. Scheirer, David D. Cox
Using Human Brain Activity to Guide Machine Learning. CoRR (2017)
Ruth Fong, Andrea Vedaldi
Interpretable Explanations of Black Boxes by Meaningful Perturbation. CoRR (2017)