SOTAVerified

Memorization

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 551–575 of 1088 papers

TitleStatusHype
Thinking Tokens for Language Modeling—0
Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory—0
An Inversion-based Measure of Memorization for Diffusion ModelsCode0
To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models—0
Exploring prompts to elicit memorization in masked language model-based named entity recognition—0
Mothman at SemEval-2024 Task 9: An Iterative System for Chain-of-Thought Prompt Optimization—0
Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics—0
Post-hoc and manifold explanations analysis of facial expression data based on deep learningCode0
Quantifying Memorization and Detecting Training Data of Pre-trained Language Models using Japanese Newspaper—0
Rethinking LLM Memorization through the Lens of Adversarial Compression—0
Does Your Neural Code Completion Model Use My Code? A Membership Inference Approach—0
Reliable Model Watermarking: Defending Against Theft without Compromising on Evasion—0
The Positivity of the Neural Tangent Kernel—0
The Fault in our Stars: Quality Assessment of Code Generation Benchmarks—0
AI Knowledge and Reasoning: Emulating Expert Creativity in Scientific Research—0
GP-MoLFormer: A Foundation Model For Molecular Generation—0
Towards Better Generalization in Open-Domain Question Answering by Mitigating Context Memorization—0
What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasks—0
SoK: A Review of Differentially Private Linear Models For High-Dimensional Data—0
Towards Memorization-Free Diffusion Models—0
Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNsCode0
Protecting Copyrighted Material with Unique Identifiers in Large Language Model TrainingCode0
DP-RDM: Adapting Diffusion Models to Private Domains Without Fine-TuningCode0
Tackling Noisy Labels with Network Parameter Additive DecompositionCode0
Self-generated Replay Memories for Continual Neural Machine TranslationCode0
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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