Contextures: The Mechanism of Representation Learning | Paper Citation Record

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This paper cites Gpt- 4 technical report.

Contextures: The Mechanism of Representation Learning Gpt- 4 technical report

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This paper cites Emergence of inv ariance and disentangle- ment in deep representations.

Contextures: The Mechanism of Representation Learning Emergence of inv ariance and disentangle- ment in deep representations

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This paper cites \alpha-req : Assessing representation quality in self-sup ervised learning by mea- suring eigenspectrum decay.

Contextures: The Mechanism of Representation Learning \alpha-req : Assessing representation quality in self-sup ervised learning by mea- suring eigenspectrum decay

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Contextures: The Mechanism of Representation Learning S carf: Self-supervised contrastive learning using random feature corruption

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Contextures: The Mechanism of Representation Learning Contrastive and non -contrastive self- supervised learning recover global and local spectral embe dding methods

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This paper cites VICReg: Varia nce-invariance- covariance regularization for self-supervised learning.

Contextures: The Mechanism of Representation Learning VICReg: Varia nce-invariance- covariance regularization for self-supervised learning

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This paper cites Generalized discrimin ant analysis using a ker- nel approach.

Contextures: The Mechanism of Representation Learning Generalized discrimin ant analysis using a ker- nel approach

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This paper cites Laplacian eigenmaps f or dimensionality re- duction and data representation.

Contextures: The Mechanism of Representation Learning Laplacian eigenmaps f or dimensionality re- duction and data representation

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This paper cites Rep resentation learning: A review and new perspectives.

Contextures: The Mechanism of Representation Learning Rep resentation learning: A review and new perspectives

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This paper cites Learning eigenfunctions links spectral embedding and kernel pca.

Contextures: The Mechanism of Representation Learning Learning eigenfunctions links spectral embedding and kernel pca

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Contextures: The Mechanism of Representation Learning Mixmatch: A holistic approach to s emi-supervised learning

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Contextures: The Mechanism of Representation Learning D iscriminative learning for diﬀering training and test distributions

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Contextures: The Mechanism of Representation Learning Statistical properties of kernel principal component analysis

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This paper cites Demo graphic dialectal vari- ation in social media: A case study of African-American Engl ish.

Contextures: The Mechanism of Representation Learning Demo graphic dialectal vari- ation in social media: A case study of African-American Engl ish

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This paper cites On the Opportunities and Risks of Foundation Models.

Contextures: The Mechanism of Representation Learning On the Opportunities and Risks of Foundation Models

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This paper cites Nuanced metrics for measuring unintended bias with rea l data for text clas- siﬁcation.

Contextures: The Mechanism of Representation Learning Nuanced metrics for measuring unintended bias with rea l data for text clas- siﬁcation

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Contextures: The Mechanism of Representation Learning Unresolved cited work

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This paper cites Functional analysis, Sobolev spaces and partial diﬀerenti al equations.

Contextures: The Mechanism of Representation Learning Functional analysis, Sobolev spaces and partial diﬀerenti al equations

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Contextures: The Mechanism of Representation Learning Unresolved cited work

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Contextures: The Mechanism of Representation Learning The SSL interplay: Augmentations, inductive bias, an d generalization

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This paper cites Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads.

Contextures: The Mechanism of Representation Learning Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

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Contextures: The Mechanism of Representation Learning Xgboost: A scalable tr ee boosting system

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Contextures: The Mechanism of Representation Learning A sim- ple framework for contrastive learning of visual represent ations

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Contextures: The Mechanism of Representation Learning Exploring simple siamese re presentation learning

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Contextures: The Mechanism of Representation Learning De constructing denois- ing diﬀusion models for self-supervised learning

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Contextures: The Mechanism of Representation Learning Spectral graph theory , volume 92

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Contextures: The Mechanism of Representation Learning Le, and Christopher D

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Contextures: The Mechanism of Representation Learning Gra- dient descent on neural networks typically occurs at the edg e of stability

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Contextures: The Mechanism of Representation Learning Diﬀusion maps

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Contextures: The Mechanism of Representation Learning Multinomial goodness -of-ﬁt tests

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Contextures: The Mechanism of Representation Learning A kernel theory of modern data augmentation

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Contextures: The Mechanism of Representation Learning Fast line ar algebra is stable

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Contextures: The Mechanism of Representation Learning Neuralef: Deconst ructing kernels by deep neural networks

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Contextures: The Mechanism of Representation Learning BERT: Pre- training of deep bidirectional transformers for language u nderstanding

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Contextures: The Mechanism of Representation Learning Improved Regularization of Convolutional Neural Networks with Cutout

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Contextures: The Mechanism of Representation Learning An image is worth 16x16 words: Transformers for image recognition at scale

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Contextures: The Mechanism of Representation Learning The Llama 3 Herd of Models

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Contextures: The Mechanism of Representation Learning Learning Models with Uniform Performance via Distributionally Robust Optimization

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Contextures: The Mechanism of Representation Learning T owards revealing the mystery behind chain of thought: A theoretical perspective

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Contextures: The Mechanism of Representation Learning Unresolved cited work

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Contextures: The Mechanism of Representation Learning Sobolev norm learnin g rates for regularized least-squares algorithms

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Contextures: The Mechanism of Representation Learning A decision-theoreti c generalization of on-line learning and an application to boosting

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Contextures: The Mechanism of Representation Learning Latent functional maps: a spectral framew ork for represen- tation alignment

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Contextures: The Mechanism of Representation Learning Scaling laws for reward model overop- timization

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Contextures: The Mechanism of Representation Learning Gemini: A Family of Highly Capable Multimodal Models

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Contextures: The Mechanism of Representation Learning Un supervised representa- tion learning by predicting image rotations

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Contextures: The Mechanism of Representation Learning Multiple kernel learn ing algorithms

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Contextures: The Mechanism of Representation Learning Generat ive adversarial nets

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Contextures: The Mechanism of Representation Learning Revisit- ing deep learning models for tabular data

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Contextures: The Mechanism of Representation Learning Bootstrap your own latent - a new approach t o self-supervised learning

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Contextures: The Mechanism of Representation Learning In search of lost domain generalization

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Contextures: The Mechanism of Representation Learning Characteriz- ing implicit bias in terms of optimization geometry

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Contextures: The Mechanism of Representation Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

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Contextures: The Mechanism of Representation Learning Statistical intervals: a guide for practitioners , volume 92

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Contextures: The Mechanism of Representation Learning Graph representation learning

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Contextures: The Mechanism of Representation Learning A Theoretical Study of Inductive Biases in Contrastive Learning

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Contextures: The Mechanism of Representation Learning P rovable guarantees for self-supervised deep learning with spectral contrastive loss

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Contextures: The Mechanism of Representation Learning HaoChen, Colin Wei, Ananya Kumar, and Tengyu Ma

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Contextures: The Mechanism of Representation Learning Fairness without demographics in repeated loss minimization

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Contextures: The Mechanism of Representation Learning Masked autoencoders are scalable vision learners

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Contextures: The Mechanism of Representation Learning D eep residual learning for image recognition

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Contextures: The Mechanism of Representation Learning Hearst, S.T

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Contextures: The Mechanism of Representation Learning Distilling the Knowledge in a Neural Network

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Contextures: The Mechanism of Representation Learning Denoising di ﬀusion probabilistic mod- els

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Contextures: The Mechanism of Representation Learning Wilds: A benchmark of in-the-wild distribution shifts

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Contextures: The Mechanism of Representation Learning Representational similarity analysis-connecting the branches of systems ne uroscience

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Contextures: The Mechanism of Representation Learning Learning multi ple layers of features from tiny images, 2009

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Contextures: The Mechanism of Representation Learning Imagenet classiﬁcation with deep convolutional neural networks

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Contextures: The Mechanism of Representation Learning Temporal ensembling for sem i-supervised learning

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Contextures: The Mechanism of Representation Learning How we analyzed the compas recidivism algorithm

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Contextures: The Mechanism of Representation Learning Gradient-based learning applied to document recognition

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Contextures: The Mechanism of Representation Learning P redicting what you already know helps: Provable self-supervised learning

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Contextures: The Mechanism of Representation Learning Chain of thought empow- 146 ers transformers to solve inherently serial problems

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Contextures: The Mechanism of Representation Learning Foundations of Multisensory Artificial Intelligence

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Contextures: The Mechanism of Representation Learning Masked pre- diction tasks: a parameter identiﬁability view

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Contextures: The Mechanism of Representation Learning HaoChen, Adrien Gaidon, and Tengyu Ma

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