New Method For Algebra-Preserving Koopman Learning
Researchers have developed a new method for deep active learning in LLMs, focusing on in-context sample selection. This approach utilizes recent insights into LLM behavior. This technique aims to simplify nonlinear dynamics into a linear spectral problem for computation.
Topics
Developing
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Sources · 7 independent
Modernity/arxiv
“Activation-Based Active Learning for In-Context Learning: Challenges and Insights. Authors: Yaseen M. Osman, Geoff V. Merrett, Stuart E. Middleton Abstract: Deep active learning has previously been explored for LLM in-context sample selection, but not with methods that utilise rece...”
Modernity/arxiv
“Deep Embedded Multiplicative DMD for Algebra-Preserving Koopman Learning. Authors: Kelan Gray, Finlay Brown, Nicolas Boullé, Matthew J. Colbrook Abstract: Koopman theory turns nonlinear dynamics into a linear spectral problem. In computation, however, everything depends on...”
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