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TRAK: Attributing Model Behavior at Scale
v1v2 (latest)

TRAK: Attributing Model Behavior at Scale

24 March 2023
Sung Min Park
Kristian Georgiev
Andrew Ilyas
Guillaume Leclerc
Aleksander Madry
    TDI
ArXiv (abs)PDFHTMLGithub (211★)

Papers citing "TRAK: Attributing Model Behavior at Scale"

49 / 49 papers shown
Title
Do Large Language Models (Really) Need Statistical Foundations?
Do Large Language Models (Really) Need Statistical Foundations?
Weijie Su
265
0
0
25 May 2025
GraSS: Scalable Influence Function with Sparse Gradient Compression
GraSS: Scalable Influence Function with Sparse Gradient Compression
Pingbang Hu
Joseph Melkonian
Weijing Tang
Han Zhao
Jiaqi W. Ma
TDI
255
0
0
25 May 2025
Meta-rater: A Multi-dimensional Data Selection Method for Pre-training Language Models
Meta-rater: A Multi-dimensional Data Selection Method for Pre-training Language Models
Xinlin Zhuang
Jiahui Peng
Ren Ma
Yucheng Wang
Tianyi Bai
Xingjian Wei
Jiantao Qiu
Chi Zhang
Ying Qian
Conghui He
116
0
0
19 Apr 2025
Data Attribution for Text-to-Image Models by Unlearning Synthesized Images
Data Attribution for Text-to-Image Models by Unlearning Synthesized Images
Sheng-Yu Wang
Aaron Hertzmann
Alexei A. Efros
Jun-Yan Zhu
Richard Zhang
TDI
191
3
0
21 Feb 2025
Most Influential Subset Selection: Challenges, Promises, and Beyond
Most Influential Subset Selection: Challenges, Promises, and Beyond
Yuzheng Hu
Pingbang Hu
Han Zhao
Jiaqi W. Ma
TDI
188
8
0
10 Jan 2025
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
Jinxu Lin
Linwei Tao
Minjing Dong
Chang Xu
TDI
76
3
0
24 Oct 2024
Identifying Sub-networks in Neural Networks via Functionally Similar Representations
Identifying Sub-networks in Neural Networks via Functionally Similar Representations
Tian Gao
Amit Dhurandhar
Karthikeyan N. Ramamurthy
Dennis L. Wei
78
0
0
21 Oct 2024
Influence Functions for Scalable Data Attribution in Diffusion Models
Influence Functions for Scalable Data Attribution in Diffusion Models
Bruno Mlodozeniec
Runa Eschenhagen
Juhan Bae
Alexander Immer
David Krueger
Richard E. Turner
DiffMTDI
121
7
0
17 Oct 2024
Data Quality Control in Federated Instruction-tuning of Large Language Models
Data Quality Control in Federated Instruction-tuning of Large Language Models
Yaxin Du
Guangyi Liu
Fengting Yuchi
W. Zhao
Jingjing Qu
Yanjie Wang
Siheng Chen
ALMFedML
104
2
0
15 Oct 2024
How Much Can We Forget about Data Contamination?
How Much Can We Forget about Data Contamination?
Sebastian Bordt
Suraj Srinivas
Valentyn Boreiko
U. V. Luxburg
109
2
0
04 Oct 2024
RandALO: Out-of-sample risk estimation in no time flat
RandALO: Out-of-sample risk estimation in no time flat
Parth Nobel
Daniel LeJeune
Emmanuel J. Candès
111
3
0
15 Sep 2024
Adversarial Attacks on Data Attribution
Adversarial Attacks on Data Attribution
Xinhe Wang
Pingbang Hu
Junwei Deng
Jiaqi W. Ma
TDI
111
0
0
09 Sep 2024
Fast Training Dataset Attribution via In-Context Learning
Fast Training Dataset Attribution via In-Context Learning
Milad Fotouhi
M. T. Bahadori
Oluwaseyi Feyisetan
P. Arabshahi
David Heckerman
86
0
0
14 Aug 2024
Data-centric Prediction Explanation via Kernelized Stein Discrepancy
Data-centric Prediction Explanation via Kernelized Stein Discrepancy
Mahtab Sarvmaili
Hassan Sajjad
Ga Wu
167
1
0
22 Mar 2024
Attributed Question Answering: Evaluation and Modeling for Attributed
  Large Language Models
Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models
Bernd Bohnet
Vinh Q. Tran
Pat Verga
Roee Aharoni
D. Andor
...
Michael Collins
Dipanjan Das
Donald Metzler
Slav Petrov
Kellie Webster
100
64
0
15 Dec 2022
Training Data Influence Analysis and Estimation: A Survey
Training Data Influence Analysis and Estimation: A Survey
Zayd Hammoudeh
Daniel Lowd
TDI
81
96
0
09 Dec 2022
ModelDiff: A Framework for Comparing Learning Algorithms
ModelDiff: A Framework for Comparing Learning Algorithms
Harshay Shah
Sung Min Park
Andrew Ilyas
Aleksander Madry
SyDa
84
29
0
22 Nov 2022
A Kernel-Based View of Language Model Fine-Tuning
A Kernel-Based View of Language Model Fine-Tuning
Sadhika Malladi
Alexander Wettig
Dingli Yu
Danqi Chen
Sanjeev Arora
VLM
122
67
0
11 Oct 2022
Understanding Influence Functions and Datamodels via Harmonic Analysis
Understanding Influence Functions and Datamodels via Harmonic Analysis
Nikunj Saunshi
Arushi Gupta
M. Braverman
Sanjeev Arora
TDI
91
18
0
03 Oct 2022
If Influence Functions are the Answer, Then What is the Question?
If Influence Functions are the Answer, Then What is the Question?
Juhan Bae
Nathan Ng
Alston Lo
Marzyeh Ghassemi
Roger C. Grosse
TDI
92
103
0
12 Sep 2022
Is a Caption Worth a Thousand Images? A Controlled Study for
  Representation Learning
Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning
Shibani Santurkar
Yann Dubois
Rohan Taori
Percy Liang
Tatsunori Hashimoto
CLIPVLM
63
41
0
15 Jul 2022
Training Compute-Optimal Large Language Models
Training Compute-Optimal Large Language Models
Jordan Hoffmann
Sebastian Borgeaud
A. Mensch
Elena Buchatskaya
Trevor Cai
...
Karen Simonyan
Erich Elsen
Jack W. Rae
Oriol Vinyals
Laurent Sifre
AI4TS
208
1,949
0
29 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error
Generalization Through The Lens Of Leave-One-Out Error
Gregor Bachmann
Thomas Hofmann
Aurelien Lucchi
125
8
0
07 Mar 2022
Quantifying Memorization Across Neural Language Models
Quantifying Memorization Across Neural Language Models
Nicholas Carlini
Daphne Ippolito
Matthew Jagielski
Katherine Lee
Florian Tramèr
Chiyuan Zhang
PILM
121
628
0
15 Feb 2022
Datamodels: Predicting Predictions from Training Data
Datamodels: Predicting Predictions from Training Data
Andrew Ilyas
Sung Min Park
Logan Engstrom
Guillaume Leclerc
Aleksander Madry
TDI
126
141
0
01 Feb 2022
LaMDA: Language Models for Dialog Applications
LaMDA: Language Models for Dialog Applications
R. Thoppilan
Daniel De Freitas
Jamie Hall
Noam M. Shazeer
Apoorv Kulshreshtha
...
Blaise Aguera-Arcas
Claire Cui
M. Croak
Ed H. Chi
Quoc Le
ALM
137
1,600
0
20 Jan 2022
Rethinking Influence Functions of Neural Networks in the
  Over-parameterized Regime
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime
Rui Zhang
Shihua Zhang
TDI
56
23
0
15 Dec 2021
Neural Networks as Kernel Learners: The Silent Alignment Effect
Neural Networks as Kernel Learners: The Silent Alignment Effect
Alexander B. Atanasov
Blake Bordelon
Cengiz Pehlevan
MLT
77
85
0
29 Oct 2021
Influence Selection for Active Learning
Influence Selection for Active Learning
Zhuoming Liu
Hao Ding
Huaping Zhong
Weijia Li
Jifeng Dai
Conghui He
TDI
67
96
0
20 Aug 2021
Deduplicating Training Data Makes Language Models Better
Deduplicating Training Data Makes Language Models Better
Katherine Lee
Daphne Ippolito
A. Nystrom
Chiyuan Zhang
Douglas Eck
Chris Callison-Burch
Nicholas Carlini
SyDa
360
634
0
14 Jul 2021
Fast Adaptation with Linearized Neural Networks
Fast Adaptation with Linearized Neural Networks
Wesley J. Maddox
Shuai Tang
Pablo G. Moreno
A. Wilson
Andreas C. Damianou
83
32
0
02 Mar 2021
A linearized framework and a new benchmark for model selection for
  fine-tuning
A linearized framework and a new benchmark for model selection for fine-tuning
Aditya Deshpande
Alessandro Achille
Avinash Ravichandran
Hao Li
Luca Zancato
Charless C. Fowlkes
Rahul Bhotika
Stefano Soatto
Pietro Perona
ALM
159
48
0
29 Jan 2021
Underspecification Presents Challenges for Credibility in Modern Machine
  Learning
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander DÁmour
Katherine A. Heller
D. Moldovan
Ben Adlam
B. Alipanahi
...
Kellie Webster
Steve Yadlowsky
T. Yun
Xiaohua Zhai
D. Sculley
OffRL
117
687
0
06 Nov 2020
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural
  Network Representations Vary with Width and Depth
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
Thao Nguyen
M. Raghu
Simon Kornblith
OOD
52
282
0
29 Oct 2020
BREEDS: Benchmarks for Subpopulation Shift
BREEDS: Benchmarks for Subpopulation Shift
Shibani Santurkar
Dimitris Tsipras
Aleksander Madry
OOD
59
175
0
11 Aug 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via
  Influence Estimation
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation
Vitaly Feldman
Chiyuan Zhang
TDI
193
464
0
09 Aug 2020
Influence Functions in Deep Learning Are Fragile
Influence Functions in Deep Learning Are Fragile
S. Basu
Phillip E. Pope
Soheil Feizi
TDI
128
235
0
25 Jun 2020
The Two Regimes of Deep Network Training
The Two Regimes of Deep Network Training
Guillaume Leclerc
Aleksander Madry
72
45
0
24 Feb 2020
Estimating Training Data Influence by Tracing Gradient Descent
Estimating Training Data Influence by Tracing Gradient Descent
G. Pruthi
Frederick Liu
Mukund Sundararajan
Satyen Kale
TDI
90
417
0
19 Feb 2020
On Second-Order Group Influence Functions for Black-Box Predictions
On Second-Order Group Influence Functions for Black-Box Predictions
S. Basu
Xuchen You
Soheil Feizi
TDI
96
71
0
01 Nov 2019
Language Models as Knowledge Bases?
Language Models as Knowledge Bases?
Fabio Petroni
Tim Rocktaschel
Patrick Lewis
A. Bakhtin
Yuxiang Wu
Alexander H. Miller
Sebastian Riedel
KELMAI4MH
576
2,673
0
03 Sep 2019
On the Accuracy of Influence Functions for Measuring Group Effects
On the Accuracy of Influence Functions for Measuring Group Effects
Pang Wei Koh
Kai-Siang Ang
H. Teo
Percy Liang
TDI
78
193
0
30 May 2019
Adversarial Examples Are Not Bugs, They Are Features
Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
Aleksander Madry
SILM
91
1,843
0
06 May 2019
Regularization Matters: Generalization and Optimization of Neural Nets
  v.s. their Induced Kernel
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel
Colin Wei
Jason D. Lee
Qiang Liu
Tengyu Ma
212
244
0
12 Oct 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
1.1K
7,182
0
20 Apr 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
Eli Shechtman
Oliver Wang
EGVM
377
11,877
0
11 Jan 2018
BadNets: Identifying Vulnerabilities in the Machine Learning Model
  Supply Chain
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
Tianyu Gu
Brendan Dolan-Gavitt
S. Garg
SILM
127
1,782
0
22 Aug 2017
Understanding Black-box Predictions via Influence Functions
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh
Percy Liang
TDI
213
2,899
0
14 Mar 2017
ImageNet Large Scale Visual Recognition Challenge
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
VLMObjD
1.7K
39,590
0
01 Sep 2014
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