AIBullisharXiv – CS AI · 14h ago7/10
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Overcoming Forgetting in LLM Fine-Tuning with Evolution Strategies
Researchers demonstrate that Evolution Strategies (ES) can effectively fine-tune large language models without catastrophic forgetting of prior tasks, contrary to recent concerns. By introducing Anchored Weight Decay (AWD), a regularization technique that constrains optimization toward initial parameters, the work shows ES-based continual learning is viable and computationally efficient compared to reinforcement learning approaches.