SOTAVerified

Memorization

Papers

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Showing 451–475 of 1088 papers

TitleStatusHype
Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language ModelsCode0
Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?Code0
Amplifying Training Data Exposure through Fine-Tuning with Pseudo-Labeled MembershipsCode0
Towards Uncovering How Large Language Model Works: An Explainability Perspective—0
Neural Information Organizing and Processing -- Neural Machines—0
The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward PassesCode1
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization—0
Copyright Traps for Large Language ModelsCode1
Social Evolution of Published Text and The Emergence of Artificial Intelligence Through Large Language Models and The Problem of Toxicity and Bias—0
Future Prediction Can be a Strong Evidence of Good History Representation in Partially Observable Environments—0
Wasserstein proximal operators describe score-based generative models and resolve memorization—0
Revisiting Early-Learning Regularization When Federated Learning Meets Noisy Labels—0
Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models—0
Analyzing the Neural Tangent Kernel of Periodically Activated Coordinate Networks—0
Amortized Planning with Large-Scale Transformers: A Case Study on ChessCode4
EMN: Brain-inspired Elastic Memory Network for Quick Domain Adaptive Feature Mapping—0
Déjà Vu Memorization in Vision-Language Models—0
Human-Centered Privacy Research in the Age of Large Language Models—0
Unconditional Latent Diffusion Models Memorize Patient Imaging Data: Implications for Openly Sharing Synthetic DataCode0
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial TrainingCode0
Expressive Power of ReLU and Step Networks under Floating-Point Operations—0
Do LLMs Dream of Ontologies?Code0
Memorization in Self-Supervised Learning Improves Downstream GeneralizationCode0
Critical Data Size of Language Models from a Grokking Perspective—0
Understanding Learning through the Lens of Dynamical Invariants—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