arXiv Computation and Language By Jiayu Hou, Lei Wang

When to Adapt: Conditional Memory Adapters for Retention-Preserving Domain Specialization

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The paper introduces Engram Adapter, a conditional memory adapter that selectively activates on in-domain inputs while suppressing out-of-domain (OOD) retrievals. It leverages multi‑channel matching over local n‑gram patterns with occupancy tracking and a learned scalar gate to inject residuals only when appropriate. Experiments on Qwen3-4B/8B with AG‑News and MedMCQA show improved in‑domain accuracy while preserving nearly all OOD performance, outperforming always‑on baselines on LegalBench.

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arXiv Computation and Language
Sep 23

LatentPort: Beyond KV Cache - Cross-Model Transfer of Recurrent Memory in Hybrid Language Models: A 4B-to-9B Hybrid-State Handoff Without Target Prefix Replay

The paper introduces LatentPort, a method that allows a language model to transfer its live memory to another model without requiring the receiver to reread the context. Experiments on a Qwen3.5 4B-to-9B sibling pair show that adding a Gated DeltaNet (GDN) persistent-state package reduces negative log‑likelihood by 0.747 nats/token and improves performance across 64 PG19 documents. The study also demonstrates that direct recurrent and convolution reuse outperforms learned GDN maps, and a 434,176‑parameter correction further narrows the performance gap to the native 9B model.

By Simon P. Villani