SOTAVerified

Memorization

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 501–525 of 1088 papers

TitleStatusHype
Minimum Description Length Hopfield NetworksCode0
Data Contamination Quiz: A Tool to Detect and Estimate Contamination in Large Language ModelsCode1
Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt CalibrationCode2
Data Factors for Better Compositional GeneralizationCode0
Preserving Privacy in GANs Against Membership Inference Attack—0
From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion ModelsCode0
DEPN: Detecting and Editing Privacy Neurons in Pretrained Language ModelsCode1
Bridging Lottery Ticket and Grokking: Understanding Grokking from Inner Structure of NetworksCode0
The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability—0
Grokking in Linear Estimators -- A Solvable Model that Groks without Understanding—0
SoK: Memorization in General-Purpose Large Language Models—0
MoPe: Model Perturbation-based Privacy Attacks on Language Models—0
Implications of Annotation Artifacts in Edge Probing Test DatasetsCode0
Copyright Violations and Large Language ModelsCode0
To grok or not to grok: Disentangling generalization and memorization on corrupted algorithmic datasetsCode1
AgentTuning: Enabling Generalized Agent Abilities for LLMsCode3
Training Dynamics of Deep Network Linear Regions—0
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine LearningCode1
ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks—0
Unintended Memorization in Large ASR Models, and How to Mitigate It—0
Generation or Replication: Auscultating Audio Latent Diffusion Models—0
Combating Label Noise With A General Surrogate Model For Sample Selection—0
On the Over-Memorization During Natural, Robust and Catastrophic OverfittingCode0
Why Train More? Effective and Efficient Membership Inference via Memorization—0
Beyond Memorization: Violating Privacy Via Inference with Large Language ModelsCode1
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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