SOTAVerified

Memorization

Papers

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Showing 476–500 of 1088 papers

TitleStatusHype
Imputation with Inter-Series Information from Prototypes for Irregular Sampled Time SeriesCode0
Erasing Undesirable Influence in Diffusion ModelsCode1
A Good Score Does not Lead to A Good Generative ModelCode0
Learning with Structural Labels for Learning with Noisy Labels—0
Infinite dSprites for Disentangled Continual Learning: Separating Memory Edits from GeneralizationCode0
Noisy Correspondence Learning with Self-Reinforcing Errors Mitigation—0
RoleEval: A Bilingual Role Evaluation Benchmark for Large Language ModelsCode1
BloomVQA: Assessing Hierarchical Multi-modal Comprehension—0
FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy LabelsCode0
Social Learning: Towards Collaborative Learning with Large Language Models—0
Lifted RDT based capacity analysis of the 1-hidden layer treelike sign perceptrons neural networks—0
Negative Pre-aware for Noisy Cross-modal MatchingCode1
Preserving Privacy Through Dememorization: An Unlearning Technique For Mitigating Memorization Risks In Language ModelsCode0
SoK: Unintended Interactions among Machine Learning Defenses and RisksCode0
Understanding (Un)Intended Memorization in Text-to-Image Generative Models—0
Memory Triggers: Unveiling Memorization in Text-To-Image Generative Models through Word-Level Duplication—0
Scalable Extraction of Training Data from (Production) Language Models—0
Continual Referring Expression Comprehension via Dual Modular MemorizationCode0
Positional Description Matters for Transformers Arithmetic—0
CSGNN: Conquering Noisy Node labels via Dynamic Class-wise Selection—0
Sparse Low-rank Adaptation of Pre-trained Language ModelsCode1
Negotiated Representations for Machine Mearning ApplicationCode0
On Retrieval Augmentation and the Limitations of Language Model Training—0
Does Pre-trained Language Model Actually Infer Unseen Links in Knowledge Graph Completion?—0
Fuse to Forget: Bias Reduction and Selective Memorization through Model FusionCode0
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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