Tag: catastrophic forgetting
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Joint Flashback Adaptation to Prevent Catastrophic Forgetting
Discover Joint Flashback Adaptation, a task-agnostic method that reduces forgetting and boosts generalization in large language models.
Layer-wise Insights for Efficient Supervised Fine-Tuning
Discover how selective layer tuning improves supervised fine-tuning, reducing forgetting and boosting model performance by 10%+ on GSM8K.
Persistent AI Identity with Multi-Anchor Memory Architecture
Discover soul.py's multi-anchor architecture that ensures resilient memory and continuous identity in AI agents, preventing catastrophic forgetting.
LifeAlign: Lifelong Alignment for Large Language Models
Discover LifeAlign, a novel framework enhancing lifelong alignment in large language models with memory-augmented preference optimization.
Dynamical Theory of Continual Learning to Prevent Forgetting
Explore the Informational Buildup Framework, a new approach to continual learning that reduces catastrophic forgetting and improves AI knowledge retention.