AIBullisharXiv – CS AI · Mar 116/10
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MSSR: Memory-Aware Adaptive Replay for Continual LLM Fine-Tuning
Researchers propose MSSR (Memory-Inspired Sampler and Scheduler Replay), a new framework for continual fine-tuning of large language models that mitigates catastrophic forgetting while maintaining adaptability. The method estimates sample-level memory strength and schedules rehearsal at adaptive intervals, showing superior performance across three backbone models and 11 sequential tasks compared to existing replay-based strategies.