Proposed serialization format enhances efficiency in large language model workflows, reducing latency and preserving state.
R-State is a proposed serialization format for transferring the internal state of large language models between stages of a heterogeneous inference pipeline without detokenization and re-tokenization. It is designed to reduce latency, preserve intermediate activations and KV-cache, and enable more modular multi-model workflows through a structured packet containing metadata and tensor payloads
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Pavel Scurin (2026) studied this question.
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