PiERN proposes token-level routing of physically-isolated experts to embed high-precision computation directly into LLMs, reporting higher accuracy and lower latency, token count, and energy use than fine-tuning or multi-agent baselines.
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Triadic Suffix Tokenization groups digits into triads with fixed magnitude suffixes to make order-of-magnitude relationships explicit at the token level for LLMs.
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PiERN: Token-Level Routing for Integrating High-Precision Computation and Reasoning
PiERN proposes token-level routing of physically-isolated experts to embed high-precision computation directly into LLMs, reporting higher accuracy and lower latency, token count, and energy use than fine-tuning or multi-agent baselines.
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A Triadic Suffix Tokenization Scheme for Numerical Reasoning
Triadic Suffix Tokenization groups digits into triads with fixed magnitude suffixes to make order-of-magnitude relationships explicit at the token level for LLMs.