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#latency

3 curated events
papersSEP 10 04:00 UTC

RelayS2S: Dual-Path Speculative Generation for Real-Time Speech-to-Speech Dialogue

A new arXiv paper proposes RelayS2S, a dual-path speculative generation method for real-time spoken dialogue systems. It addresses the trade-off between latency and response quality, since end-to-end speech-to-speech models can respond instantly and manage turn-taking, backchanneling, and interruptions, but tend to produce semantically weaker replies. The method aims to combine immediate responsiveness with improved response content.

speech-to-speech/real-time/dialogue/latency
papersSEP 12 04:00 UTC

arXiv Paper Proposes Tail-Aware Scheduling for Agentic LLM Workflows

A new arXiv preprint examines how agentic LLM workflows, which alternate model turns with tool calls, are affected by the timing of when completed turns are dispatched. The authors argue that separating a turn's readiness from its release lets runtimes optimize for tail latency rather than simply pushing each turn out immediately. The work targets scheduling policies that reduce worst-case end-to-end completion times for these multi-step pipelines.

agents/scheduling/llm-serving/latency
papersSEP 10 04:00 UTC

PACE framework targets perceived latency in retrieval-augmented dialogue serving

Researchers introduce PACE, a serving framework for retrieval-augmented dialogue systems that defines Perceived Time-to-First-Response as a quality-of-experience metric and optimizes it subject to quality and cost limits. The approach combines cascaded service routing with filler response control to reduce how long users wait before receiving an initial answer. The work extends prior research on cascading and semantic caching by treating perceived latency as an explicit optimization objective.

research/rag/latency/serving