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Trivial or impossible -- dichotomous data difficulty masks model
  differences (on ImageNet and beyond)
v1v2v3 (latest)

Trivial or impossible -- dichotomous data difficulty masks model differences (on ImageNet and beyond)

International Conference on Learning Representations (ICLR), 2021
12 October 2021
Kristof Meding
Luca M. Schulze Buschoff
Robert Geirhos
Felix Wichmann
ArXiv (abs)PDFHTML

Papers citing "Trivial or impossible -- dichotomous data difficulty masks model differences (on ImageNet and beyond)"

21 / 21 papers shown
Data Pruning by Information Maximization
Data Pruning by Information MaximizationInternational Conference on Learning Representations (ICLR), 2025
Haoru Tan
Sitong Wu
Wei Huang
Shizhen Zhao
Xiaojuan Qi
321
8
0
02 Jun 2025
Bridging Distribution Shift and AI Safety: Conceptual and Methodological Synergies
Bridging Distribution Shift and AI Safety: Conceptual and Methodological Synergies
Chenruo Liu
Kenan Tang
Yao Qin
Qi Lei
248
1
0
28 May 2025
PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity
PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity
Mustafa Burak Gurbuz
Xingyu Zheng
C. Dovrolis
OOD
637
0
0
07 Apr 2025
Not All Samples Should Be Utilized Equally: Towards Understanding and Improving Dataset Distillation
Not All Samples Should Be Utilized Equally: Towards Understanding and Improving Dataset Distillation
Shaobo Wang
Yantai Yang
Qilong Wang
Kaixin Li
Linfeng Zhang
Junchi Yan
DD
400
11
0
22 Aug 2024
A Lightweight Measure of Classification Difficulty from Application
  Dataset Characteristics
A Lightweight Measure of Classification Difficulty from Application Dataset Characteristics
Bryan Bo Cao
Abhinav Sharma
Lawrence O'Gorman
Michael J. Coss
Shubham Jain
298
3
0
09 Apr 2024
Distilling the Knowledge in Data Pruning
Distilling the Knowledge in Data Pruning
Emanuel Ben-Baruch
Adam Botach
Igor Kviatkovsky
Manoj Aggarwal
Gérard Medioni
224
2
0
12 Mar 2024
Your Vision-Language Model Itself Is a Strong Filter: Towards
  High-Quality Instruction Tuning with Data Selection
Your Vision-Language Model Itself Is a Strong Filter: Towards High-Quality Instruction Tuning with Data Selection
Ruibo Chen
Yihan Wu
Lichang Chen
Guodong Liu
Qi He
Tianyi Xiong
Chenxi Liu
Junfeng Guo
Heng-Chiao Huang
VLM
196
36
0
19 Feb 2024
How to Train Data-Efficient LLMs
How to Train Data-Efficient LLMs
Noveen Sachdeva
Benjamin Coleman
Wang-Cheng Kang
Jianmo Ni
Lichan Hong
Ed H. Chi
James Caverlee
Julian McAuley
D. Cheng
267
90
0
15 Feb 2024
Data Optimization in Deep Learning: A Survey
Data Optimization in Deep Learning: A SurveyIEEE Transactions on Knowledge and Data Engineering (TKDE), 2023
Ou Wu
Rujing Yao
330
6
0
25 Oct 2023
You Only Condense Once: Two Rules for Pruning Condensed Datasets
You Only Condense Once: Two Rules for Pruning Condensed DatasetsNeural Information Processing Systems (NeurIPS), 2023
Yang He
Lingao Xiao
Qiufeng Wang
227
23
0
21 Oct 2023
Functional trustworthiness of AI systems by statistically valid testing
Functional trustworthiness of AI systems by statistically valid testing
Bernhard Nessler
Thomas Doms
Sepp Hochreiter
131
0
0
04 Oct 2023
D4: Improving LLM Pretraining via Document De-Duplication and
  Diversification
D4: Improving LLM Pretraining via Document De-Duplication and DiversificationNeural Information Processing Systems (NeurIPS), 2023
Kushal Tirumala
Daniel Simig
Armen Aghajanyan
Ari S. Morcos
SyDa
192
151
0
23 Aug 2023
Are Deep Neural Networks Adequate Behavioural Models of Human Visual
  Perception?
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?Annual Review of Vision Science (ARVS), 2023
Felix Wichmann
Robert Geirhos
248
39
0
26 May 2023
SemDeDup: Data-efficient learning at web-scale through semantic
  deduplication
SemDeDup: Data-efficient learning at web-scale through semantic deduplication
Amro Abbas
Kushal Tirumala
Daniel Simig
Surya Ganguli
Ari S. Morcos
304
243
0
16 Mar 2023
ModelDiff: A Framework for Comparing Learning Algorithms
ModelDiff: A Framework for Comparing Learning AlgorithmsInternational Conference on Machine Learning (ICML), 2022
Harshay Shah
Sung Min Park
Andrew Ilyas
Aleksander Madry
SyDa
203
34
0
22 Nov 2022
Similarity of Neural Architectures using Adversarial Attack
  Transferability
Similarity of Neural Architectures using Adversarial Attack TransferabilityEuropean Conference on Computer Vision (ECCV), 2022
Ian Ryu
Dongyoon Han
Byeongho Heo
Song Park
Sanghyuk Chun
Jong-Seok Lee
AAML
543
3
0
20 Oct 2022
Random initialisations performing above chance and how to find them
Random initialisations performing above chance and how to find them
Frederik Benzing
Simon Schug
Robert Meier
J. Oswald
Yassir Akram
Nicolas Zucchet
Laurence Aitchison
Angelika Steger
ODL
423
28
0
15 Sep 2022
On the Strong Correlation Between Model Invariance and Generalization
On the Strong Correlation Between Model Invariance and GeneralizationNeural Information Processing Systems (NeurIPS), 2022
Weijian Deng
Stephen Gould
Liang Zheng
OOD
223
25
0
14 Jul 2022
Beyond neural scaling laws: beating power law scaling via data pruning
Beyond neural scaling laws: beating power law scaling via data pruningNeural Information Processing Systems (NeurIPS), 2022
Ben Sorscher
Robert Geirhos
Shashank Shekhar
Surya Ganguli
Ari S. Morcos
1.7K
552
0
29 Jun 2022
A Tour of Visualization Techniques for Computer Vision Datasets
A Tour of Visualization Techniques for Computer Vision Datasets
B. Alsallakh
P. Bhattacharya
V. Feng
Narine Kokhlikyan
Orion Reblitz-Richardson
Rahul Rajan
David Yan
131
4
0
19 Apr 2022
Partial success in closing the gap between human and machine vision
Partial success in closing the gap between human and machine visionNeural Information Processing Systems (NeurIPS), 2021
Robert Geirhos
Kantharaju Narayanappa
Benjamin Mitzkus
Tizian Thieringer
Matthias Bethge
Felix Wichmann
Wieland Brendel
VLMAAML
325
267
0
14 Jun 2021
1
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