Cited by: Overcoming catastrophic forgetting in neural networks

17 citation edges inside this catalog. A title match is weaker evidence than an identifier match. Zero entries does not mean no citations on the web.

• Measuring Catastrophic Forgetting in Neural Networks
  arxiv:1708.02072 · evidence: title
• AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence
  arxiv:1905.10985 · evidence: title
• Continual Backprop: Stochastic Gradient Descent with Persistent Randomness
  arxiv:2108.06325 · evidence: title
• Metalearning Continual Learning Algorithms
  arxiv:2312.00276 · evidence: title
• Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning
  arxiv:2402.13669 · evidence: title
• Continual Learning and Catastrophic Forgetting
  arxiv:2403.05175 · evidence: title
• TransformerFAM: Feedback attention is working memory
  arxiv:2404.09173 · evidence: title
• How do language models learn facts? Dynamics, curricula and hallucinations
  arxiv:2503.21676 · evidence: title
• Nested Learning: The Illusion of Deep Learning Architectures
  arxiv:2512.24695 · evidence: title
• MemRL: Self-Evolving Agents via Runtime Reinforcement Learning on Episodic Memory
  arxiv:2601.03192 · evidence: title
• Learning to Discover at Test Time
  arxiv:2601.16175 · evidence: title
• Self-Distillation Enables Continual Learning
  arxiv:2601.19897 · evidence: title
• Evolutionary Strategies lead to Catastrophic Forgetting in LLMs
  arxiv:2601.20861 · evidence: title
• Self-Improvements in Modern Agentic Systems: A Survey
  arxiv:2607.13104 · evidence: title
• Finetuning with Sampling: SFT Learns Better Than You Think
  arxiv:2610.02140 · evidence: title
• Maintaining Plasticity in Deep Continual Learning
  doi:10.1038/s41586-024-07711-7 · evidence: id
• Sleep prevents catastrophic forgetting in spiking neural networks by forming joint synaptic weight representations
  doi:10.1371/journal.pcbi.1010628 · evidence: id