Towards Evolving Context Parameterization for Large Language Models
This work proposed PLUME, a training-free method that constructs a global update representation, activates memory evidence to form a local parameter view, and adaptively integrates their predictions during decoding, which demonstrated its effectiveness in sequential evolution settings.
Xiao Shi, Zhe-Rui Li, Yi-Ming Jiang et al.
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