Google DeepMind paper reportedly proposes 'Virtual Logic Depth' to boost LLM reasoning without adding parameters
A post says the approach loops data through existing layers, claiming reasoning gains for small local models without added parameters.
TLDR
A post claims Google DeepMind published a paper proposing 'Virtual Logic Depth' as a fourth scaling dimension. As described in the post, the approach runs data through the same layers repeatedly rather than adding parameters. Its author argues this could help small, cheap local models reason better and reduce reliance on expensive enterprise APIs.
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