SOTAVerified

Memorization

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1001–1050 of 1088 papers

TitleStatusHype
Deep ReLU Networks Have Surprisingly Few Activation Patterns—0
DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of SkillsCode0
Downsampling leads to Image Memorization in Convolutional Autoencoders—0
Better Generalization with On-the-fly Dataset Denoising—0
Investigating CNNs' Learning Representation under label noise—0
Long-Term Vehicle Localization by Recursive Knowledge Distillation—0
The Information Complexity of Learning Tasks, their Structure and their Distance—0
Understanding Feature Selection and Feature Memorization in Recurrent Neural Networks—0
RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose EstimationCode0
Learning to Infer Program SketchesCode0
Identity Crisis: Memorization and Generalization under Extreme Overparameterization—0
Optimal Kronecker-Sum Approximation of Real Time Recurrent LearningCode0
Do We Train on Test Data? Purging CIFAR of Near-Duplicates—0
Revisiting Sample Selection Approach to Positive-Unlabeled Learning: Turning Unlabeled Data into Positive rather than Negative—0
State-Regularized Recurrent Neural Networks—0
How does Disagreement Help Generalization against Label Corruption?Code0
Detecting Overfitting of Deep Generative Networks via Latent RecoveryCode0
VideoMem: Constructing, Analyzing, Predicting Short-term and Long-term Video Memorability—0
Limited Gradient Descent: Learning With Noisy Labels—0
Leveraging Random Label Memorization for Unsupervised Pre-Training—0
Auditing Data Provenance in Text-Generation ModelsCode0
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity—0
Memorization in Overparameterized Autoencoders—0
Are You Sure YouWant To Do That? Classification with Interpretable Queries—0
Detecting Memorization in ReLU Networks—0
Wide and Deep Learning for Peer-to-Peer Lending—0
A Practical Approach to Sizing Neural Networks—0
SIGUA: Forgetting May Make Learning with Noisy Labels More RobustCode0
State-Regularized Recurrent Networks—0
Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels—0
Déjà Vu: an empirical evaluation of the memorization properties of ConvNets—0
Closed-Book Training to Improve Summarization Encoder Memory—0
Are You Sure You Want To Do That? Classification with Verification—0
VideoMatch: Matching based Video Object Segmentation—0
Airline Passenger Name Record Generation using Generative Adversarial Networks—0
MediaEval 2018: Predicting Media Memorability Task—0
Learning and Memorization—0
A Spline Theory of Deep Learning—0
Split and Rephrase: Better Evaluation and Stronger BaselinesCode0
Olive Oil is Made Olives, Baby Oil is Made Babies: Interpreting Noun Compounds Using Paraphrases in a Neural Model—0
LSTMs Exploit Linguistic Attributes of Data—0
Approximating Real-Time Recurrent Learning with Random Kronecker Factors—0
Refining Source Representations with Relation Networks for Neural Machine Translation—0
Mad Max: Affine Spline Insights into Deep Learning—0
DNN or k-NN: That is the Generalize vs. Memorize Question—0
Split and Rephrase: Better Evaluation and a Stronger BaselineCode0
ALIGNet: Partial-Shape Agnostic Alignment via Unsupervised LearningCode0
MemGEN: Memory is All You Need—0
Fast Parametric Learning with Activation Memorization—0
Olive Oil is Made of Olives, Baby Oil is Made for Babies: Interpreting Noun Compounds using Paraphrases in a Neural ModelCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PaLM-540B (few-shot, k=5)Accuracy95.4—Unverified
2Gopher-280B (few-shot, k=5)Accuracy80—Unverified
3PaLM-62B (few-shot, k=5)Accuracy77.7—Unverified