RePo: Empowering Language Models to Reorganize Context
SakanaAILabs · x · 2026-07-04
The RePo method proposed by Sakana AI will be showcased at ICML 2026. Standard language models process information as rigid, linear sequences and rely solely on fixed token indices to infer structure, wasting limited capacity when critical facts are drowned in noise.
RePo breaks this bottleneck by allowing the model to actively reorganize its context rather than relying on fixed indices, thereby concentrating its capacity on deep reasoning.
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