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Distilling Model Failures as Directions in Latent Space

29 June 2022

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Papers citing "Distilling Model Failures as Directions in Latent Space"

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Title
Fine-Grained Bias Exploration and Mitigation for Group-Robust Classification Miaoyun Zhao Qiang Zhang C. Li 97 0 0 11 May 2025
Severing Spurious Correlations with Data Pruning Varun Mulchandani Jung-Eun Kim 451 1 0 24 Mar 2025
Interpreting CLIP with Hierarchical Sparse Autoencoders Vladimir Zaigrajew Hubert Baniecki P. Biecek 254 1 0 27 Feb 2025
Controlled Training Data Generation with Diffusion Models Teresa Yeo Andrei Atanov Harold Benoit Aleksandr Alekseev Ruchira Ray Pooya Esmaeil Akhoondi Amir Zamir 97 6 0 22 Mar 2024
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding Chitwan Saharia William Chan Saurabh Saxena Lala Li Jay Whang ... Raphael Gontijo-Lopes Tim Salimans Jonathan Ho David J Fleet Mohammad Norouzi VLM 466 6,077 0 23 May 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 76 59 0 09 May 2022
Learning to Split for Automatic Bias Detection Yujia Bao Regina Barzilay 60 21 0 28 Apr 2022
Hierarchical Text-Conditional Image Generation with CLIP Latents Aditya A. Ramesh Prafulla Dhariwal Alex Nichol Casey Chu Mark Chen VLM DiffM 413 6,916 0 13 Apr 2022
Domino: Discovering Systematic Errors with Cross-Modal Embeddings Sabri Eyuboglu M. Varma Khaled Kamal Saab Jean-Benoit Delbrouck Christopher Lee-Messer Jared A. Dunnmon James Zou Christopher Ré 89 148 0 24 Mar 2022
Datamodels: Predicting Predictions from Training Data Andrew Ilyas Sung Min Park Logan Engstrom Guillaume Leclerc Aleksander Madry TDI 133 142 0 01 Feb 2022
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 502 15,788 0 20 Dec 2021
Just Train Twice: Improving Group Robustness without Training Group Information Emmy Liu Behzad Haghgoo Annie S. Chen Aditi Raghunathan Pang Wei Koh Shiori Sagawa Percy Liang Chelsea Finn OOD 107 563 0 19 Jul 2021
Meaningfully Debugging Model Mistakes using Conceptual Counterfactual Explanations Abubakar Abid Mert Yuksekgonul James Zou CML 87 64 0 24 Jun 2021
Leveraging Sparse Linear Layers for Debuggable Deep Networks Eric Wong Shibani Santurkar Aleksander Madry FAtt 60 92 0 11 May 2021
Discover the Unknown Biased Attribute of an Image Classifier Zhiheng Li Chenliang Xu 73 50 0 29 Apr 2021
Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks Curtis G. Northcutt Anish Athalye Jonas W. Mueller 92 537 0 26 Mar 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 999 29,926 0 26 Feb 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 235 1,449 0 14 Dec 2020
Understanding Failures of Deep Networks via Robust Feature Extraction Sahil Singla Besmira Nushi S. Shah Ece Kamar Eric Horvitz FAtt 73 84 0 03 Dec 2020
Learning from others' mistakes: Avoiding dataset biases without modeling them Victor Sanh Thomas Wolf Yonatan Belinkov Alexander M. Rush 74 116 0 02 Dec 2020
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems N. Sohoni Jared A. Dunnmon Geoffrey Angus Albert Gu Christopher Ré 87 252 0 25 Nov 2020
Towards Debiasing NLU Models from Unknown Biases Prasetya Ajie Utama N. Moosavi Iryna Gurevych 87 155 0 25 Sep 2020
Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts Sarah Jabbour David Fouhey Ella Kazerooni Michael Sjoding Jenna Wiens OOD 52 49 0 21 Sep 2020
BREEDS: Benchmarks for Subpopulation Shift Shibani Santurkar Dimitris Tsipras Aleksander Madry OOD 63 175 0 11 Aug 2020
Robustness to Spurious Correlations via Human Annotations Megha Srivastava Tatsunori Hashimoto Percy Liang CML OOD 51 90 0 13 Jul 2020
Learning from Failure: Training Debiased Classifier from Biased Classifier J. Nam Hyuntak Cha SungSoo Ahn Jaeho Lee Jinwoo Shin 84 150 0 06 Jul 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Dan Hendrycks Steven Basart Norman Mu Saurav Kadavath Frank Wang ... Samyak Parajuli Mike Guo Basel Alomair Jacob Steinhardt Justin Gilmer OOD 363 1,757 0 29 Jun 2020
Noise or Signal: The Role of Image Backgrounds in Object Recognition Kai Y. Xiao Logan Engstrom Andrew Ilyas Aleksander Madry 148 387 0 17 Jun 2020
Are we done with ImageNet? Lucas Beyer Olivier J. Hénaff Alexander Kolesnikov Xiaohua Zhai Aaron van den Oord VLM 134 407 0 12 Jun 2020
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks Dimitris Tsipras Shibani Santurkar Logan Engstrom Andrew Ilyas Aleksander Madry 77 135 0 22 May 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 221 2,061 0 16 Apr 2020
Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy Kaiyu Yang Klint Qinami Li Fei-Fei Jia Deng Olga Russakovsky 126 323 0 16 Dec 2019
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 108 1,249 0 20 Nov 2019
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan O. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 289 307 0 17 Oct 2019
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases Christopher Clark Mark Yatskar Luke Zettlemoyer OOD 88 467 0 09 Sep 2019
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual He He Sheng Zha Haohan Wang 70 199 0 28 Aug 2019
Fairness in Deep Learning: A Computational Perspective Mengnan Du Fan Yang Na Zou Helen Zhou FaML FedML 51 234 0 23 Aug 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 571 4,391 0 23 Aug 2019
Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference Yonatan Belinkov Adam Poliak Stuart M. Shieber Benjamin Van Durme Alexander M. Rush 63 95 0 09 Jul 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 198 2,246 0 05 Jul 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 142 502 0 12 Jun 2019
Counterfactual Visual Explanations Yash Goyal Ziyan Wu Jan Ernst Dhruv Batra Devi Parikh Stefan Lee CML 80 512 0 16 Apr 2019
Data Shapley: Equitable Valuation of Data for Machine Learning Amirata Ghorbani James Zou TDI FedML 85 791 0 05 Apr 2019
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness Robert Geirhos Patricia Rubisch Claudio Michaelis Matthias Bethge Felix Wichmann Wieland Brendel 139 2,674 0 29 Nov 2018
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 68 371 0 29 Oct 2018
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 152 1,970 0 08 Oct 2018
Grounding Visual Explanations Lisa Anne Hendricks Ronghang Hu Trevor Darrell Zeynep Akata FAtt 59 230 0 25 Jul 2018
Explaining Image Classifiers by Counterfactual Generation C. Chang Elliot Creager Anna Goldenberg David Duvenaud VLM 78 265 0 20 Jul 2018
Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations Dan Hendrycks Thomas G. Dietterich OOD 84 202 0 04 Jul 2018
Fairness Without Demographics in Repeated Loss Minimization Tatsunori B. Hashimoto Megha Srivastava Hongseok Namkoong Percy Liang FaML 117 585 0 20 Jun 2018