Memorization
267 papers with code • 1 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Memorization
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Libraries
Use these libraries to find Memorization models and implementations
BIG-bench
DS-1000
PopQA
LM Email Address Leakage
Most implemented papers
DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills
In this article, we first frame the research problem of optimizing an adaptive and personalized spaced repetition scheduler when memorization concerns the application of underlying multiple skills.
Searching to Exploit Memorization Effect in Learning from Corrupted Labels
Sample selection approaches are popular in robust learning from noisy labels.
Learning explanations that are hard to vary
In this paper, we investigate the principle that `good explanations are hard to vary' in the context of deep learning.
Consensual Collaborative Training And Knowledge Distillation Based Facial Expression Recognition Under Noisy Annotations
1980x/CCT
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A dynamic transition mechanism is used to move from supervision loss in early learning to consistency loss for consensus of predictions among networks in the later stage.
Towards Adversarial Evaluations for Inexact Machine Unlearning
shash42/evaluating-inexact-unlearning
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Machine Learning models face increased concerns regarding the storage of personal user data and adverse impacts of corrupted data like backdoors or systematic bias.
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.
A Closer Look at Memorization in Deep Networks
We examine the role of memorization in deep learning, drawing connections to capacity, generalization, and adversarial robustness.
Rotational Unit of Memory
We evaluate our model on synthetic memorization, question answering and language modeling tasks.
Bidirectional deep-readout echo state networks
FilippoMB/Bidirectional-Deep-reservoir-Echo-State-Network
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We propose a deep architecture for the classification of multivariate time series.
Split and Rephrase: Better Evaluation and a Stronger Baseline
To aid this, we present a new train-development-test data split and neural models augmented with a copy-mechanism, outperforming the best reported baseline by 8. 68 BLEU and fostering further progress on the task.
