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Contextures: Representations from Contexts

Contextures: Representations from Contexts

2 May 2025
Runtian Zhai
Kai Yang
Che-Ping Tsai
Burak Varici
Zico Kolter
Pradeep Ravikumar
ArXiv (abs)PDFHTML

Papers citing "Contextures: Representations from Contexts"

24 / 24 papers shown
Title
Imbalance Trouble: Revisiting Neural-Collapse Geometry
Imbalance Trouble: Revisiting Neural-Collapse Geometry
Christos Thrampoulidis
Ganesh Ramachandra Kini
V. Vakilian
Tina Behnia
58
73
0
10 Aug 2022
Emergent Abilities of Large Language Models
Emergent Abilities of Large Language Models
Jason W. Wei
Yi Tay
Rishi Bommasani
Colin Raffel
Barret Zoph
...
Tatsunori Hashimoto
Oriol Vinyals
Percy Liang
J. Dean
W. Fedus
ELMReLMLRM
288
2,511
0
15 Jun 2022
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global
  and Local Spectral Embedding Methods
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods
Randall Balestriero
Yann LeCun
SSL
89
135
0
23 May 2022
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLMALM
886
13,176
0
04 Mar 2022
data2vec: A General Framework for Self-supervised Learning in Speech,
  Vision and Language
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
Alexei Baevski
Wei-Ning Hsu
Qiantong Xu
Arun Babu
Jiatao Gu
Michael Auli
SSLVLMViT
99
859
0
07 Feb 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViTTPM
477
7,819
0
11 Nov 2021
Understanding Dimensional Collapse in Contrastive Self-supervised
  Learning
Understanding Dimensional Collapse in Contrastive Self-supervised Learning
Li Jing
Pascal Vincent
Yann LeCun
Yuandong Tian
SSL
120
358
0
18 Oct 2021
Provable Guarantees for Self-Supervised Deep Learning with Spectral
  Contrastive Loss
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss
Jeff Z. HaoChen
Colin Wei
Adrien Gaidon
Tengyu Ma
SSL
77
321
0
08 Jun 2021
VICReg: Variance-Invariance-Covariance Regularization for
  Self-Supervised Learning
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
Adrien Bardes
Jean Ponce
Yann LeCun
SSLDML
153
944
0
11 May 2021
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar
Li Jing
Ishan Misra
Yann LeCun
Stéphane Deny
SSL
347
2,362
0
04 Mar 2021
Prevalence of Neural Collapse during the terminal phase of deep learning
  training
Prevalence of Neural Collapse during the terminal phase of deep learning training
Vardan Papyan
Xuemei Han
D. Donoho
205
582
0
18 Aug 2020
Bootstrap your own latent: A new approach to self-supervised Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Jean-Bastien Grill
Florian Strub
Florent Altché
Corentin Tallec
Pierre Harvey Richemond
...
M. G. Azar
Bilal Piot
Koray Kavukcuoglu
Rémi Munos
Michal Valko
SSL
398
6,837
0
13 Jun 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
387
18,866
0
13 Feb 2020
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
611
4,905
0
23 Jan 2020
Similarity of Neural Network Representations Revisited
Similarity of Neural Network Representations Revisited
Simon Kornblith
Mohammad Norouzi
Honglak Lee
Geoffrey E. Hinton
143
1,431
0
01 May 2019
Towards a Definition of Disentangled Representations
Towards a Definition of Disentangled Representations
I. Higgins
David Amos
David Pfau
S. Racanière
Loic Matthey
Danilo Jimenez Rezende
Alexander Lerchner
OCLDRL
108
480
0
05 Dec 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLMSSLSSeg
1.8K
95,175
0
11 Oct 2018
Optimal approximation of continuous functions by very deep ReLU networks
Optimal approximation of continuous functions by very deep ReLU networks
Dmitry Yarotsky
194
294
0
10 Feb 2018
Understanding deep learning requires rethinking generalization
Understanding deep learning requires rethinking generalization
Chiyuan Zhang
Samy Bengio
Moritz Hardt
Benjamin Recht
Oriol Vinyals
HAI
348
4,635
0
10 Nov 2016
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
39,595
0
01 Sep 2014
OpenML: networked science in machine learning
OpenML: networked science in machine learning
Joaquin Vanschoren
Jan N. van Rijn
B. Bischl
Luís Torgo
FedMLAI4CE
167
1,327
0
29 Jul 2014
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
314
7,316
0
20 Dec 2013
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAttSSL
595
15,904
0
12 Nov 2013
Measuring and testing dependence by correlation of distances
Measuring and testing dependence by correlation of distances
G. Székely
Maria L. Rizzo
N. K. Bakirov
279
2,602
0
28 Mar 2008
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