AI RESEARCH
Trained Persistent Memory for Frozen Decoder-Only LLMs
arXiv CS.AI
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ArXi:2603.22329v1 Announce Type: cross Decoder-only language models are stateless: hidden representations are discarded after every forward pass and nothing persists across sessions. Jeong (2026a) showed that trained memory adapters give a frozen encoder-decoder backbone persistent latent-space memory, building on the lateral-memory framework of Jeong (2026b,c). Here we ask whether the same principle transfers to the decoder-only setting, where no cross-attention pathway exists and memory must enter through self-attention alone.