mlsanityData to 14 Oct 2026

Reproducibility Report: La-MAML: Look-ahead Meta Learning for Continual Learning

arXiv 2102.05824 ↗First posted 11 Feb 2021cs.LG cs.AIcited by 42

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Abstract (arXiv)

The Continual Learning (CL) problem involves performing well on a sequence of tasks under limited compute. Current algorithms in the domain are either slow, offline or sensitive to hyper-parameters. La-MAML, an optimization-based meta-learning algorithm claims to be better than other replay-based, prior-based and meta-learning based approaches. According to the MER paper [1], metrics to measure performance in the continual learning arena are Retained Accuracy (RA) and Backward Transfer-Interference (BTI). La-MAML claims to perform better in these values when compared to the SOTA in the domain. This is the main claim of the paper, which we shall be verifying in this report.

Key facts. Cited by 42 papers in the map (data through 14 Oct 2026). Builds on 5 of its 12 references that are in the map. First posted on arXiv 11 Feb 2021.

Builds on

5 of 12 references.

References · 5

  1. 2016Overcoming catastrophic forgetting in neural networkscited by 4,787
  2. 2016iCaRL: Incremental Classifier and Representation Learningcited by 2,333
  3. 2017Gradient Episodic Memory for Continual Learningcited by 1,898
  4. 2018Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interferencecited by 521
  5. 2020La-MAML: Look-ahead Meta Learning for Continual Learningcited by 52

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Cited by year

Citing papers per year: 2021: 6; 2022: 4; 2023: 14; 2024: 10; 2025: 8.

42 papers.

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  1. 2023A Comprehensive Survey of Continual Learning: Theory, Method and Applicationcited by 872
  2. 2021Co2L: Contrastive Continual Learningcited by 244
  3. 2022A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunitiescited by 163
  4. 2021An Empirical Investigation of the Role of Pre-training in Lifelong Learningcited by 134
  5. 2023Advances and Challenges in Meta-Learning: A Technical Reviewcited by 65
  6. 2023Learning to Retain while Acquiring: Combating Distribution-Shift in Adversarial Data-Free Knowledge Distillationcited by 29
  7. 2021Learngene: From Open-World to Your Learning Taskcited by 27
  8. 2024TPO: Aligning Large Language Models with Multi-branch & Multi-step Preference Treescited by 19
  9. 2021Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learningcited by 16
  10. 2023Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learningcited by 16
  11. 2021A contrastive rule for meta-learningcited by 14
  12. 2021SPeCiaL: Self-Supervised Pretraining for Continual Learningcited by 12
30 more
  1. 2023When Meta-Learning Meets Online and Continual Learning: A Surveycited by 12
  2. 2024Random Representations Outperform Online Continually Learned Representationscited by 11
  3. 2023HyperTime: Hyperparameter Optimization for Combating Temporal Distribution Shiftscited by 8
  4. 2024Learning to Continually Learn with the Bayesian Principlecited by 8
  5. 2024Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applicationscited by 8
  6. 2022On Enforcing Better Conditioned Meta-Learning for Rapid Few-Shot Adaptationcited by 7
  7. 2023Partial Hypernetworks for Continual Learningcited by 7
  8. 2024A Layer Selection Approach to Test Time Adaptationcited by 7
  9. 2024Vision-Language Navigation with Continual Learningcited by 6
  10. 2023Lookbehind-SAM: k steps back, 1 step forwardcited by 5
  11. 2023DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learningcited by 4
  12. 2023VERSE: Virtual-Gradient Aware Streaming Lifelong Learning with Anytime Inferencecited by 4
  13. 2025Dynamic Prototype Rehearsal for Continual ECG Arrhythmia Detectioncited by 4
  14. 2022Integral Continual Learning Along the Tangent Vector Field of Taskscited by 3
  15. 2023Continual HyperTransformer: A Meta-Learner for Continual Few-Shot Learningcited by 3
  16. 2023KrADagrad: Kronecker Approximation-Domination Gradient Preconditioned Stochastic Optimizationcited by 3
  17. 2023Mitigating Catastrophic Forgetting for Few-Shot Spoken Word Classification Through Meta-Learningcited by 2
  18. 2025Parabolic Continual Learningcited by 2
  19. 2025Information-Theoretic Generalization Bounds of Replay-based Continual Learningcited by 2
  20. 2024Towards Synchronous Memorizability and Generalizability with Site-Modulated Diffusion Replay for Cross-Site Continual Segmentationcited by 1
  21. 2024Continual Deep Learning on the Edge via Stochastic Local Competition among Subnetworkscited by 1
  22. 2024Learning to Learn without Forgetting using Attentioncited by 1
  23. 2025Sample Compression for Self Certified Continual Learningcited by 1
  24. 2025Meta-Continual Learning of Neural Fieldscited by 1
  25. 2025Few-Shot Generalized Category Discovery With Retrieval-Guided Decision Boundary Enhancementcited by 1
  26. 2022Task-Agnostic Learning to Accomplish New Taskscited by 0
  27. 2023Promoting Exploration in Memory-Augmented Adam using Critical Momentacited by 0
  28. 2024Sample Weight Estimation Using Meta-Updates for Online Continual Learningcited by 0
  29. 2025Meta-Learning Transformers to Improve In-Context Generalizationcited by 0
  30. 2025Wavelet Predictive Representations for Non-Stationary Reinforcement Learningcited by 0