mlsanityData to 7 Oct 2026

Metalearning with Hebbian Fast Weights

arXiv 1807.05076 ↗First posted 12 Jul 2018cs.NE cs.AI cs.LGcited by 15

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Abstract (arXiv)

We unify recent neural approaches to one-shot learning with older ideas of associative memory in a model for metalearning. Our model learns jointly to represent data and to bind class labels to representations in a single shot. It builds representations via slow weights, learned across tasks through SGD, while fast weights constructed by a Hebbian learning rule implement one-shot binding for each new task. On the Omniglot, Mini-ImageNet, and Penn Treebank one-shot learning benchmarks, our model achieves state-of-the-art results.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Jul 2018.

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Citing papers per year: 2021: 3; 2022: 3; 2023: 3; 2024: 0; 2025: 3; 2026: 3.

15 papers.

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  1. 2021Linear Transformers Are Secretly Fast Weight Programmerscited by 471
  2. 2025Kimi Linear: An Expressive, Efficient Attention Architecturecited by 169
  3. 2022A Modern Self-Referential Weight Matrix That Learns to Modify Itselfcited by 40
  4. 2023Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Surveycited by 8
  5. 2023Metalearning Continual Learning Algorithmscited by 6
  6. 2025Fast weight programming and linear transformers: from machine learning to neurobiologycited by 6
  7. 2021Towards Zero-shot Language Modelingcited by 3
  8. 2026Where to Bind Matters: Hebbian Fast Weights in Vision Transformers for Few-Shot Character Recognitioncited by 3
  9. 2023EMO: Episodic Memory Optimization for Few-Shot Meta-Learningcited by 2
  10. 2026Adaptive Hebbian Memory Routing in Vision Transformers for Few-Shot Learningcited by 2
  11. 2022Memory-enriched computation and learning in spiking neural networks through Hebbian plasticitycited by 1
  12. 2022Learning to Control Rapidly Changing Synaptic Connections: An Alternative Type of Memory in Sequence Processing Artificial Neural Networkscited by 1
3 more
  1. 2026Where Should Experience Live? Hierarchical Hebbian Memory for Continual Vision Transformerscited by 1
  2. 2021Representation Memorization for Fast Learning New Knowledge without Forgettingcited by 0
  3. 2025Multi-Plasticity Synergy with Adaptive Mechanism Assignment for Training Spiking Neural Networkscited by 0