ModelDiff: A Framework for Comparing Learning Algorithms

22 November 2022

Harshay Shah

Papers citing "ModelDiff: A Framework for Comparing Learning Algorithms"

24 / 24 papers shown

Title
MAGIC: Near-Optimal Data Attribution for Deep Learning Andrew Ilyas Logan Engstrom TDI 37 0 0 23 Apr 2025
ImageSet2Text: Describing Sets of Images through Text Piera Riccio F. Galati Kajetan Schweighofer Noa Garcia Nuria Oliver VLM CoGe 72 0 0 25 Mar 2025
Representational Similarity via Interpretable Visual Concepts Neehar Kondapaneni Oisin Mac Aodha Pietro Perona DRL 121 0 0 19 Mar 2025
Towards Understanding Distilled Reasoning Models: A Representational Approach David D. Baek Max Tegmark LRM 75 2 0 05 Mar 2025
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models Jinxu Lin Linwei Tao Minjing Dong Chang Xu TDI 36 2 0 24 Oct 2024
Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection Saachi Jain Kimia Hamidieh Kristian Georgiev Andrew Ilyas Marzyeh Ghassemi Aleksander Madry 35 2 0 24 Jun 2024
MD tree: a model-diagnostic tree grown on loss landscape Yefan Zhou Jianlong Chen Qinxue Cao Konstantin Schürholt Yaoqing Yang 29 2 0 24 Jun 2024
A Lightweight Measure of Classification Difficulty from Application Dataset Characteristics Bryan Bo Cao Abhinav Sharma Lawrence O'Gorman Michael J. Coss Shubham Jain 23 1 0 09 Apr 2024
The Journey, Not the Destination: How Data Guides Diffusion Models Kristian Georgiev Joshua Vendrow Hadi Salman Sung Min Park Aleksander Madry 10 20 0 11 Dec 2023
Understanding the Detrimental Class-level Effects of Data Augmentation Polina Kirichenko Mark Ibrahim Randall Balestriero Diane Bouchacourt Ramakrishna Vedantam Hamed Firooz Andrew Gordon Wilson 37 12 0 07 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 30 30 0 05 Dec 2023
Towards Measuring Representational Similarity of Large Language Models Max Klabunde Mehdi Ben Amor Michael Granitzer Florian Lemmerich 34 1 0 05 Dec 2023
DiG-IN: Diffusion Guidance for Investigating Networks -- Uncovering Classifier Differences Neuron Visualisations and Visual Counterfactual Explanations Maximilian Augustin Yannic Neuhaus Matthias Hein DiffM 29 4 0 29 Nov 2023
Perturbed examples reveal invariances shared by language models Ruchit Rawal Mariya Toneva AAML 34 0 0 07 Nov 2023
A Simple and Efficient Baseline for Data Attribution on Images Vasu Singla Pedro Sandoval-Segura Micah Goldblum Jonas Geiping Tom Goldstein FAtt 28 3 0 03 Nov 2023
FACTS: First Amplify Correlations and Then Slice to Discover Bias Sriram Yenamandra Baifeng Shi Trevor Darrell Judy Hoffman CML 23 21 0 29 Sep 2023
Understanding the Benefits of Image Augmentations Matthew Iceland Christopher Kanan 29 1 0 09 Jun 2023
Similarity of Neural Network Models: A Survey of Functional and Representational Measures Max Klabunde Tobias Schumacher M. Strohmaier Florian Lemmerich 45 64 0 10 May 2023
TRAK: Attributing Model Behavior at Scale Sung Min Park Kristian Georgiev Andrew Ilyas Guillaume Leclerc A. Madry TDI 22 127 0 24 Mar 2023
Reliability of CKA as a Similarity Measure in Deep Learning Mohammad-Javad Davari Stefan Horoi A. Natik Guillaume Lajoie Guy Wolf Eugene Belilovsky AAML 74 35 0 28 Oct 2022
When does Bias Transfer in Transfer Learning? Hadi Salman Saachi Jain Andrew Ilyas Logan Engstrom Eric Wong A. Madry 38 34 0 06 Jul 2022
Similarity Analysis of Contextual Word Representation Models John M. Wu Yonatan Belinkov Hassan Sajjad Nadir Durrani Fahim Dalvi James R. Glass 46 73 0 03 May 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,886 0 15 Sep 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 282 39,190 0 01 Sep 2014