SmoothAgent: Efficient Long-Horizon LLM-Based Agent Serving with Lookahead Context Engineering
2026-07-02T08:52:18Z•f0d8a9b596ea7af0e1ef28235378fc391de1a43d063a91393fdcafa44c5d3ab8
AReaL2.0agentic-rlasync-runtimescloud-autoscalingcloudyguicontext-engineeringdiscrete-diffusioneldrentropy-regularizationfederated-learninggpu-energy-efficiencykv-cache-compressionllm-servinglookahead-schedulingmicroservice-availabilitymoe-routingmosaickvmpi-one-sidedparallel-samplingpromise-futureself-evolving-agentssparse-modelsstochastic-connectivity
What happened
This document is a batch of recent arXiv CS papers (July 2, 2026) covering systems and ML infrastructure advances. Key contributions include: SmoothAgent — a lookahead context-engineering model and runtime that precomputes segment-decomposable context transformations to eliminate transformation overhead and reduce time-to-first-token (TTFT) up to 11.9×; MosaicKV — dynamic two-dimensional KV-cache compression for very long-context LLM serving delivering up to 16× attention speedup, ~3× memory reduction and only ~1.8% accuracy loss; ELDR — expert-locality-aware decode routing for PD-disaggregatd
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_dc
- Record identifier
- f0d8a9b596ea7af0e1ef28235378fc391de1a43d063a91393fdcafa44c5d3ab8
- Enrichment time
- 2026-07-02T08:52:18Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.