SOTAVerified

Memorization

Papers

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Showing 301–325 of 1088 papers

TitleStatusHype
Information-Theoretic Progress Measures reveal Grokking is an Emergent Phase Transition—0
Understanding the Local Geometry of Generative Model Manifolds—0
Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMsCode1
Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization—0
Quantifying the Corpus Bias Problem in Automatic Music Transcription SystemsCode0
MaxMind: A Memory Loop Network to Enhance Software Productivity based on Large Language Models—0
Diffusion Model Meets Non-Exemplar Class-Incremental Learning and Beyond—0
Why Are My Prompts Leaked? Unraveling Prompt Extraction Threats in Customized Large Language ModelsCode0
Human foraging strategies flexibly adapt to resource distribution and time constraints—0
Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks—0
Detecting, Explaining, and Mitigating Memorization in Diffusion ModelsCode2
Adaptive Pre-training Data Detection for Large Language Models via Surprising Tokens—0
Embedding Space Selection for Detecting Memorization and Fingerprinting in Generative Models—0
Strong Copyright Protection for Language Models via Adaptive Model Fusion—0
LLMs' Understanding of Natural Language Revealed—0
Towards Clean-Label Backdoor Attacks in the Physical WorldCode0
Graph Memory Learning: Imitating Lifelong Remembering and Forgetting of Brain Networks—0
Demystifying Verbatim Memorization in Large Language ModelsCode0
Untrained neural networks can demonstrate memorization-independent abstract reasoningCode0
MemBench: Memorized Image Trigger Prompt Dataset for Diffusion ModelsCode1
Empirical Capacity Model for Self-Attention Neural Networks—0
Iterative Ensemble Training with Anti-Gradient Control for Mitigating Memorization in Diffusion ModelsCode0
Knowledge Mechanisms in Large Language Models: A Survey and Perspective—0
Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data—0
How to Engage Your Readers? Generating Guiding Questions to Promote Active ReadingCode0
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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