SOTAVerified

Memorization

Papers

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Showing 1001–1050 of 1088 papers

TitleStatusHype
MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data—0
Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning—0
Minimizing Memorization in Meta-learning: A Causal Perspective—0
Mitigating Approximate Memorization in Language Models via Dissimilarity Learned Policy—0
Mitigating Backdoor Threats to Large Language Models: Advancement and Challenges—0
Mitigating Memorization in LLMs using Activation Steering—0
Mitigating Memorization in Sample Selection for Learning with Noisy Labels—0
Mitigating Sensitive Information Leakage in LLMs4Code through Machine Unlearning—0
Mitigating Unintended Memorization in Language Models via Alternating Teaching—0
Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment—0
Mixture of Parrots: Experts improve memorization more than reasoning—0
Mixup-based Deep Metric Learning Approaches for Incomplete Supervision—0
modeLing: A Novel Dataset for Testing Linguistic Reasoning in Language Models—0
Modifying Memories in Transformer Models—0
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
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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