SOTAVerified

Memorization

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1051–1075 of 1088 papers

TitleStatusHype
On the Robustness of Monte Carlo Dropout Trained with Noisy Labels—0
On the Role of Geometry in Geo-Localization—0
On the Unintended Social Bias of Training Language Generation Models with Data from Local Media—0
On the Unintended Social Bias of Training Language Generation Models with News Articles—0
Towards Uncovering How Large Language Model Works: An Explainability Perspective—0
Optimal Memorization Capacity of Transformers—0
Optimizing Human Learning—0
OT-Filter: An Optimal Transport Filter for Learning With Noisy Labels—0
Overparameterized Neural Networks Can Implement Associative Memory—0
Parameter Compression of Recurrent Neural Networks and Degradation of Short-term Memory—0
Parsimonious Inference—0
Patch-Based Diffusion Models Beat Whole-Image Models for Mismatched Distribution Inverse Problems—0
PDFed: Privacy-Preserving and Decentralized Asynchronous Federated Learning for Diffusion Models—0
Perceptron Theory Can Predict the Accuracy of Neural Networks—0
Per-Example Gradient Regularization Improves Learning Signals from Noisy Data—0
PII-Compass: Guiding LLM training data extraction prompts towards the target PII via grounding—0
PLATO-K: Internal and External Knowledge Enhanced Dialogue Generation—0
Polling Latent Opinions: A Method for Computational Sociolinguistics Using Transformer Language Models—0
Positional Description Matters for Transformers Arithmetic—0
Positional Fragility in LLMs: How Offset Effects Reshape Our Understanding of Memorization Risks—0
Power System Event Identification based on Deep Neural Network with Information Loading—0
PreCog: Exploring the Relation between Memorization and Performance in Pre-trained Language Models—0
Predicting Grokking Long Before it Happens: A look into the loss landscape of models which grok—0
Preserving Privacy in GANs Against Membership Inference Attack—0
Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy—0
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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