Domino: Discovering Systematic Errors with Cross-Modal Embeddings

24 March 2022

Sabri Eyuboglu

M. Varma

Khaled Kamal Saab

Jean-Benoit Delbrouck

Christopher Lee-Messer

Papers citing "Domino: Discovering Systematic Errors with Cross-Modal Embeddings"

26 / 26 papers shown

Title
Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Quentin Guimard Moreno DÍncà Massimiliano Mancini Elisa Ricci SSL 72 0 0 29 Apr 2025
Detecting Systematic Weaknesses in Vision Models along Predefined Human-Understandable Dimensions Sujan Sai Gannamaneni Rohil Prakash Rao Michael Mock Maram Akila Stefan Wrobel AAML 139 0 0 17 Feb 2025
GIFT: A Framework for Global Interpretable Faithful Textual Explanations of Vision Classifiers Éloi Zablocki Valentin Gerard Amaia Cardiel Eric Gaussier Matthieu Cord Eduardo Valle 79 0 0 23 Nov 2024
Distributionally robust self-supervised learning for tabular data Shantanu Ghosh Tiankang Xie Mikhail Kuznetsov OOD 19 1 0 11 Oct 2024
Multicalibration for Confidence Scoring in LLMs Gianluca Detommaso Martín Bertrán Riccardo Fogliato Aaron Roth 24 12 0 06 Apr 2024
Better, Not Just More: Data-Centric Machine Learning for Earth Observation R. Roscher M. Rußwurm Caroline Gevaert Michael C. Kampffmeyer J. A. dos Santos ... Ronny Hansch Stine Hansen Keiller Nogueira Jonathan Prexl D. Tuia 32 10 0 08 Dec 2023
Describing Differences in Image Sets with Natural Language Lisa Dunlap Yuhui Zhang Xiaohan Wang Ruiqi Zhong Trevor Darrell Jacob Steinhardt Joseph E. Gonzalez Serena Yeung-Levy CoGe VLM 32 30 0 05 Dec 2023
Beyond Testers' Biases: Guiding Model Testing with Knowledge Bases using LLMs Chenyang Yang Rishabh Rustogi Rachel A. Brower-Sinning Grace A. Lewis Christian Kastner Tongshuang Wu KELM 30 11 0 14 Oct 2023
Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning Yu Yang Besmira Nushi Hamid Palangi Baharan Mirzasoleiman 36 36 0 08 Apr 2023
Goal Driven Discovery of Distributional Differences via Language Descriptions Ruiqi Zhong Peter Zhang Steve Li Jinwoo Ahn Dan Klein Jacob Steinhardt 39 48 0 28 Feb 2023
Discovering and Mitigating Visual Biases through Keyword Explanation Younghyun Kim Sangwoo Mo Minkyu Kim Kyungmin Lee Jaeho Lee Jinwoo Shin 40 30 0 26 Jan 2023
Task Discovery: Finding the Tasks that Neural Networks Generalize on Andrei Atanov Andrei Filatov Teresa Yeo Ajay Sohmshetty Amir Zamir OOD 40 10 0 01 Dec 2022
ModelDiff: A Framework for Comparing Learning Algorithms Harshay Shah Sung Min Park Andrew Ilyas A. Madry SyDa 51 26 0 22 Nov 2022
DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems Nabeel Seedat F. Imrie M. Schaar 27 12 0 09 Nov 2022
Discovering Bugs in Vision Models using Off-the-shelf Image Generation and Captioning Olivia Wiles Isabela Albuquerque Sven Gowal VLM 30 46 0 18 Aug 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 51 71 0 19 Jul 2022
GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language Zhiying Zhu Weixin Liang James Y. Zou 32 9 0 30 Jun 2022
Distilling Model Failures as Directions in Latent Space Saachi Jain Hannah Lawrence Ankur Moitra A. Madry 18 89 0 29 Jun 2022
When does dough become a bagel? Analyzing the remaining mistakes on ImageNet Vijay Vasudevan Benjamin Caine Raphael Gontijo-Lopes Sara Fridovich-Keil Rebecca Roelofs VLM UQCV 35 57 0 09 May 2022
ConceptExplainer: Interactive Explanation for Deep Neural Networks from a Concept Perspective Jinbin Huang Aditi Mishra Bum Chul Kwon Chris Bryan FAtt HAI 38 31 0 04 Apr 2022
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts Weixin Liang James Y. Zou OOD 35 81 0 14 Feb 2022
Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text M. Varma Laurel J. Orr Sen Wu Megan Leszczynski Xiao Ling Christopher Ré 39 27 0 15 Oct 2021
The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models G. dÉon Jason dÉon J. R. Wright Kevin Leyton-Brown 20 74 0 01 Jul 2021
Robustness Gym: Unifying the NLP Evaluation Landscape Karan Goel Nazneen Rajani Jesse Vig Samson Tan Jason M. Wu Stephan Zheng Caiming Xiong Mohit Bansal Christopher Ré AAML OffRL OOD 146 136 0 13 Jan 2021
Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation Laurel J. Orr Megan Leszczynski Simran Arora Sen Wu Neel Guha Xiao Ling Christopher Ré 132 48 0 20 Oct 2020
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan Ö. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 122 297 0 17 Oct 2019