RFC R-State — Resumable State Transfer Format for Heterogeneous LLM Pipeline Architectures

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

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-01
DOI
https://doi.org/10.5281/zenodo.19951913
Citations
2
Primary Topic
Machine Learning and Algorithms
Type
article
Field-Weighted Citation Impact
65.68
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article

RFC R-State — Resumable State Transfer Format for Heterogeneous LLM Pipeline Architectures

Pavel Scurin
2 citations
Zenodo (CERN European Organization for Nuclear Research)
Machine Learning and Algorithms
65.68
article

RFC R-State — Resumable State Transfer Format for Heterogeneous LLM Pipeline Architectures

Pavel Scurin
article en
2 citations

Abstract

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

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 0%
Machine Learning and Algorithms
65.68
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RFC R-State — Resumable State Transfer Format for Heterogeneous LLM Pipeline Architectures — Pavel Scurin · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS