ReplaySSM: Cache SSM Inputs, Not State

9 Oct 2026Reported by arXiv21

Source: arXiv

Summary

The story centres on vLLM. Reported by arXiv.

Key points

First reported by arXiv on 9 Oct 2026.
Reported so far by arXiv alone — worth checking the original before relying on it.
Names vLLM.
Filed under AI Models.

Summary assembled automatically by BharatHunt from the headline and the coverage listed below — not AI-generated, and not a reproduction of the article. The original reporting is the source of truth.

Companies, models and people in this story

vLLMtool

Reported by arXiv

First seen 9 oct 2026

arXivReplaySSM: Cache SSM Inputs, Not State9 Oct 2026Ze-Wei Liou

AI Models38

Push-based KV transfer to improve TTFT and TPOT for disaggregated inference in vLLM

It centres on Inference, and also names vLLM and Benchmarks. Reported by AWS.

Source: AWSYesterdayRead original

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What’s Trending in AI?

ReplaySSM: Cache SSM Inputs, Not State

Summary

Key points

Companies, models and people in this story

Reported by arXiv

Push-based KV transfer to improve TTFT and TPOT for disaggregated inference in vLLM

More on BharatHunt

Improve TTFT for multi-turn agentic workloads with bi-directional KV transfer in vLLM

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

Generate images and video with vLLM-Omni on SageMaker AI – Part 2

What’s Trending in AI?

Summary

Key points

Companies, models and people in this story

Reported by arXiv

Related AI coverage

Push-based KV transfer to improve TTFT and TPOT for disaggregated inference in vLLM

More on BharatHunt

Improve TTFT for multi-turn agentic workloads with bi-directional KV transfer in vLLM

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

Generate images and video with vLLM-Omni on SageMaker AI – Part 2