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#machine learning Preprint Oct 2026

Representation Drift in Continual Learning: LoRA versus N-gram Memory

A language model that keeps learning online must not slowly erode its own base capabilities. We ask which part of a modern LLM should absorb continual updates, by measuring how each choice changes the model's internal representations. On a 48-layer mixture-of-experts model with a native pretrained N-gram memory, we tra...

Hao Wu · 0 citations
#artificial intelligence Preprint Oct 2026

Radioactive Feedback: Tracing Models Trained by Label-Only LLM Supervision

Conventional distillation transfers capability through teacher-generated demonstrations. LLM-as-a-Judge knowledge distillation offers a distinct and increasingly practical alternative. In the label-only variant studied here, the student generates every response and improves from scalar scores alone. Prior work shows th...

Yue-Jia Li, Junheng Li, Hao Wu et al. · 0 citations

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