SOTAVerified

Memorization

Papers

Showing 76100 of 1088 papers

TitleStatusHype
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic ForgettingCode1
ByGPT5: End-to-End Style-conditioned Poetry Generation with Token-free Language ModelsCode1
Dissecting Generation Modes for Abstractive Summarization Models via Ablation and AttributionCode1
Arithmetic Without Algorithms: Language Models Solve Math With a Bag of HeuristicsCode1
Can Forward Gradient Match Backpropagation?Code1
AlleNoise: large-scale text classification benchmark dataset with real-world label noiseCode1
Capabilities of GPT-4 on Medical Challenge ProblemsCode1
DISC: Learning From Noisy Labels via Dynamic Instance-Specific Selection and CorrectionCode1
Early-Learning Regularization Prevents Memorization of Noisy LabelsCode1
Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language ModelsCode1
Elephants Never Forget: Testing Language Models for Memorization of Tabular DataCode1
A comparison of LSTM and GRU networks for learning symbolic sequencesCode1
Do Language Models Plagiarize?Code1
CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?Code1
Towards Adversarial Evaluations for Inexact Machine UnlearningCode1
Mitigating Memorization of Noisy Labels via Regularization between RepresentationsCode1
State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesisCode1
A Unified Framework for Model EditingCode1
Consensual Collaborative Training And Knowledge Distillation Based Facial Expression Recognition Under Noisy AnnotationsCode1
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy LabelsCode1
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy LabelsCode1
AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZCode1
Continual Variational Autoencoder Learning via Online Cooperative MemorizationCode1
Bot or Human? Detecting ChatGPT Imposters with A Single QuestionCode1
DEPN: Detecting and Editing Privacy Neurons in Pretrained Language ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PaLM-540B (few-shot, k=5)Accuracy95.4Unverified
2Gopher-280B (few-shot, k=5)Accuracy80Unverified
3PaLM-62B (few-shot, k=5)Accuracy77.7Unverified