SOTAVerified

Memorization

Papers

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Showing 351–400 of 1088 papers

TitleStatusHype
Extreme Image Transformations Facilitate Robust Latent Object Representations—0
Extracting Unlearned Information from LLMs with Activation Steering—0
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity—0
FLM-101B: An Open LLM and How to Train It with $100K Budget—0
Composing Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets—0
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation—0
Integrating Functionalities To A System Via Autoencoder Hippocampus Network—0
Extracting Training Data from Unconditional Diffusion Models—0
Extracting Training Data from Document-Based VQA Models—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers—0
Attention Beats Concatenation for Conditioning Neural Fields—0
Investigating CNNs' Learning Representation under label noise—0
Extracting memorized pieces of (copyrighted) books from open-weight language models—0
FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning—0
Future Prediction Can be a Strong Evidence of Good History Representation in Partially Observable Environments—0
Generalizability of Memorization Neural Networks—0
FINED: Feed Instance-Wise Information Need with Essential and Disentangled Parametric Knowledge from the Past—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers—0
Assessing Generalization in TD methods for Deep Reinforcement Learning—0
Expressive Power of ReLU and Step Networks under Floating-Point Operations—0
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning—0
Combating Label Noise With A General Surrogate Model For Sample Selection—0
Generalization vs. Memorization in the Presence of Statistical Biases in Transformers—0
Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data—0
Exploring the Hidden Reasoning Process of Large Language Models by Misleading Them—0
Generation or Replication: Auscultating Audio Latent Diffusion Models—0
Co-matching: Combating Noisy Labels by Augmentation Anchoring—0
Generative AI Training and Copyright Law—0
Generative artificial intelligence in ophthalmology: multimodal retinal images for the diagnosis of Alzheimer's disease with convolutional neural networks—0
A Spline Theory of Deep Learning—0
Exploring prompts to elicit memorization in masked language model-based named entity recognition—0
Collectionless Artificial Intelligence—0
Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization—0
A Multi-Perspective Analysis of Memorization in Large Language Models—0
A Simple Model of Inference Scaling Laws—0
GP-MoLFormer: A Foundation Model For Molecular Generation—0
Exploring Memorization in Fine-tuned Language Models—0
Collaborative Learning in General Graphs with Limited Memorization: Complexity, Learnability, and Reliability—0
Context-Aware Membership Inference Attacks against Pre-trained Large Language Models—0
Graph Neural Networks Provably Benefit from Structural Information: A Feature Learning Perspective—0
Exploring Memorization and Copyright Violation in Frontier LLMs: A Study of the New York Times v. OpenAI 2023 Lawsuit—0
Grokking as Compression: A Nonlinear Complexity Perspective—0
Cross-Domain Generalization Through Memorization: A Study of Nearest Neighbors in Neural Duplicate Question Detection—0
Exploring Local Memorization in Diffusion Models via Bright Ending Attention—0
Coherence and Diversity through Noise: Self-Supervised Paraphrase Generation via Structure-Aware Denoising—0
Grokking in the Wild: Data Augmentation for Real-World Multi-Hop Reasoning with Transformers—0
Exploring Fact Memorization and Style Imitation in LLMs Using QLoRA: An Experimental Study and Quality Assessment Methods—0
Weak and Strong Gradient Directions: Explaining Memorization, Generalization, and Hardness of Examples at Scale—0
Codex Hacks HackerRank: Memorization Issues and a Framework for Code Synthesis Evaluation—0
A Simple Approach to the Noisy Label Problem Through the Gambler's Loss—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