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Memorization

Papers

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Showing 801–850 of 1088 papers

TitleStatusHype
MoPe: Model Perturbation-based Privacy Attacks on Language Models—0
Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization—0
Mothman at SemEval-2024 Task 9: An Iterative System for Chain-of-Thought Prompt Optimization—0
MSR: Making Self-supervised learning Robust to Aggressive Augmentations—0
Multi-Sample Online Learning for Probabilistic Spiking Neural Networks—0
Navigating the Latent Space Dynamics of Neural Models—0
Network size and size of the weights in memorization with two-layers neural networks—0
Network size and weights size for memorization with two-layers neural networks—0
Neural Information Organizing and Processing -- Neural Machines—0
Neural Network Memorization Dissection—0
Neural Networks Learning and Memorization with (almost) no Over-Parameterization—0
NEVLP: Noise-Robust Framework for Efficient Vision-Language Pre-training—0
NLIP: Noise-robust Language-Image Pre-training—0
NN-grams: Unifying neural network and n-gram language models for Speech Recognition—0
Noisy Correspondence Learning with Self-Reinforcing Errors Mitigation—0
None of the Others: a General Technique to Distinguish Reasoning from Memorization in Multiple-Choice LLM Evaluation Benchmarks—0
Nonlinear random matrix theory for deep learning—0
Not All Knowledge Is Created Equal: Mutual Distillation of Confident Knowledge—0
Not-So-CLEVR: Visual Relations Strain Feedforward Neural Networks—0
Obliviate: Efficient Unmemorization for Protecting Intellectual Property in Large Language Models—0
OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models—0
Olive Oil is Made Olives, Baby Oil is Made Babies: Interpreting Noun Compounds Using Paraphrases in a Neural Model—0
On Influence Functions, Classification Influence, Relative Influence, Memorization and Generalization—0
Online Learning via Memory: Retrieval-Augmented Detector Adaptation—0
Online Memorization of Random Firing Sequences by a Recurrent Neural Network—0
On Memorization and Privacy Risks of Sharpness Aware Minimization—0
On Memorization of Large Language Models in Logical Reasoning—0
On Retrieval Augmentation and the Limitations of Language Model Training—0
On the Dichotomy Between Privacy and Traceability in _p Stochastic Convex Optimization—0
On the Generalization Mystery in Deep Learning—0
On the geometry of generalization and memorization in deep neural networks—0
On the Interpolation Effect of Score Smoothing—0
On the Memorization Properties of Contrastive Learning—0
On the Optimal Memorization Power of ReLU Neural Networks—0
On the Planning, Search, and Memorization Capabilities of Large Language Models—0
On the Reasoning Capacity of AI Models and How to Quantify It—0
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
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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