Gated KalmaNet: A Fading Memory Layer Through Test-Time Ridge Regression
Published:Nov 26, 2025 03:26
•1 min read
•ArXiv
Analysis
This article introduces Gated KalmaNet, a novel approach for improving memory in language models. The core idea revolves around using test-time ridge regression to create a fading memory layer. The research likely explores the benefits of this approach in terms of performance and efficiency compared to existing memory mechanisms within LLMs. The use of 'Gated' suggests a control mechanism for the memory, potentially allowing for selective retention or forgetting of information. The source, ArXiv, indicates this is a pre-print, suggesting the work is recent and undergoing peer review.
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