The Structure of Relation Decoding Linear Operators in Large Language Models
PositiveArtificial Intelligence
A recent study delves into the structure of linear operators used in transformer language models, building on previous work by Hernandez et al. The research reveals that collections of relation decoders can be efficiently compressed using order-3 tensor networks, maintaining high decoding accuracy. This advancement is significant as it enhances the efficiency of language models, potentially leading to faster and more effective applications in natural language processing.
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