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Resurgence of Recurrent Models in Large Language Models
In natural language processing, applying recurrent models to language modeling was an early successful method for learning sequence representations. While the Transformer is currently the foundational architecture for Large Language Models (LLMs), recurrent models are experiencing a resurgence. They are now being reconsidered as a powerful and promising alternative to Transformers, particularly for developing more computationally efficient LLMs.
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Foundations of Large Language Models
Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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his processing a sequence of inputs. The state is updated at each step according to the ruleh_i = f(h_{i-1}, input_i), whereh_{i-1}is the state from the previous step andinput_iis the current input. When the model processes the third input in a sequence, what information does the termh_2(the state after the second input) represent in the computation for the new stateh_3?Analysis of Sequential Information Processing
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