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Continual Learning

1895 directly classified papers

Papers per year

Papers

Rational LAMOL: A Rationale-based Lifelong Learning Framework ACL 2021
Quantifying Appropriateness of Summarization Data for Curriculum Learning EACL 2021
Lifelong Knowledge-Enriched Social Event Representation Learning EACL 2021
Analyzing the Forgetting Problem in Pretrain-Finetuning of Open-domain Dialogue Response Models EACL 2021
FLAR: A Unified Prototype Framework for Few-Sample Lifelong Active Recognition ICCV 2021
Domain-Lifelong Learning for Dialogue State Tracking via Knowledge Preservation Networks EMNLP 2021
Lifelong Explainer for Lifelong Learners EMNLP 2021
Total Recall: a Customized Continual Learning Method for Neural Semantic Parsers EMNLP 2021
Continual Learning in Task-Oriented Dialogue Systems EMNLP 2021
Multi-Level Curriculum for Training a Distortion-Aware Barrel Distortion Rectification Model ICCV 2021
Unsupervised Progressive Learning and the STAM Architecture IJCAI 2021
Synthesized Feature Based Few-Shot Class-Incremental Learning on a Mixture of Subspaces ICCV 2021
Modeling financial uncertainty with multivariate temporal entropy-based curriculums UAI 2021
Hierarchical Indian buffet neural networks for Bayesian continual learning UAI 2021
Lifelong Learning with Sketched Structural Regularization ACML 2021
CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks NIPS 2021
Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning EMNLP 2021
Increasing Liquid State Machine Performance with Edge-of-Chaos Dynamics Organized by Astrocyte-modulated Plasticity NIPS 2021
Biological learning in key-value memory networks NIPS 2021
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning CVPR 2021
Learning with Selective Forgetting IJCAI 2021
Natural continual learning: success is a journey, not (just) a destination NIPS 2021
Lifelong Domain Adaptation via Consolidated Internal Distribution NIPS 2021
Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection NIPS 2021
Learning where to learn: Gradient sparsity in meta and continual learning NIPS 2021