Author

Haodong Lei

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Jul 2026

TransMem: Transforming Hidden States into Memory for Large Language Models

TransMem is proposed, a lightweight inference-time parametric memory module that transforms sparse historical hidden states from a frozen LLM backbone into reusable memory representations and introduces evidence-conditioned self-distillation to learn transferable memory utilization rather than task-specific knowledge.

Haodong Lei, Junming Liu, Yirong Chen et al. · arXiv.org · 0 citations