惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

U
Unit 42
V
V2EX
Martin Fowler
Martin Fowler
博客园 - Franky
P
Proofpoint News Feed
P
Palo Alto Networks Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
B
Blog
The Register - Security
The Register - Security
Latest news
Latest news
S
Security @ Cisco Blogs
Simon Willison's Weblog
Simon Willison's Weblog
Recorded Future
Recorded Future
大猫的无限游戏
大猫的无限游戏
M
Microsoft Research Blog - Microsoft Research
Scott Helme
Scott Helme
T
Tailwind CSS Blog
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Application and Cybersecurity Blog
Application and Cybersecurity Blog
T
True Tiger Recordings
有赞技术团队
有赞技术团队
I
Intezer
Cisco Talos Blog
Cisco Talos Blog
Hacker News - Newest:
Hacker News - Newest: "LLM"
The GitHub Blog
The GitHub Blog
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
T
Tenable Blog
博客园 - 叶小钗
Hugging Face - Blog
Hugging Face - Blog
Hacker News: Ask HN
Hacker News: Ask HN
S
Security Archives - TechRepublic
F
Future of Privacy Forum
爱范儿
爱范儿
PCI Perspectives
PCI Perspectives
H
Help Net Security
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
T
The Blog of Author Tim Ferriss
MyScale Blog
MyScale Blog
N
Netflix TechBlog - Medium
罗磊的独立博客
Apple Machine Learning Research
Apple Machine Learning Research
MongoDB | Blog
MongoDB | Blog
Security Latest
Security Latest
美团技术团队
博客园 - 三生石上(FineUI控件)
S
Schneier on Security
量子位
C
CERT Recently Published Vulnerability Notes
SecWiki News
SecWiki News

cs.LG updates on arXiv.org

Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines Tabular foundation models for robust calibration of near-infrared chemical sensing data ECPO: Evidence-Coupled Policy Optimization for Evidence-Certified Candidate Ranking The Attribution Impossibility: No Feature Ranking Is Faithful, Stable, and Complete Under Collinearity IKNO: Infinite-order Kernel Neural Operators Symbolic Density Estimation for Discrete Distributions Tailoring Teaching to Aptitude: Direction-Adaptive Self-Distillation for LLM Reasoning How Sparsity Allocation Shapes Label-Free Post-Pruning Recoverability Quantitative coronary calcification analysis for prediction of myocardial ischemia using non-contrast CT calcium scoring Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction CausalGuard: Conformal Inference under Graph Uncertainty Reinforced Graph of Thoughts: RL-Driven Adaptive Prompting for LLMs TBP-mHC: full expressivity for manifold-constrained hyper connections through transportation polytopes MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems Alike Parts: A Feature-Informed Approach to Local and Global Prototype Explanations Temporal Contrastive Transformer for Financial Crime Detection: Self-Supervised Sequence Embeddings via Predictive Contrastive Coding Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics Representation Gap: Explaining the Unreasonable Effectiveness of Neural Networks from a Geometric Perspective Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data Dynamic Mixture of Latent Memories for Self-Evolving Agents Detecting Atypical Clients in Federated Learning via Representation-Level Divergence Aerodynamic force reconstruction using physics-informed Gaussian processes One-Way Policy Optimization for Self-Evolving LLMs Thermodynamic Irreversibility of Training Algorithms TONIC: Token-Centric Semantic Communication for Task-Oriented Wireless Systems Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimization AgForce Enables Antigen-conditioned Generative Antibody Design SCI-Defense: Defending Manipulation Attacks from Generative Engine Optimization DualOptim+: Bridging Shared and Decoupled Optimizer States for Better Machine Unlearning in Large Language Models AutoMCU: Feasibility-First MCU Neural Network Customization via LLM-based Multi-Agent Systems Discovering Entity-Conditioned Lag Heterogeneity: A Lag-Gated Neural Audit Framework for Panel Time Series Calibration, Uncertainty Communication, and Deployment Readiness in CKD Risk Prediction: A Framework Evaluation Study How Many Different Outputs Can a Transformer Generate? Learning Mixture Models via Efficient High-dimensional Sparse Fourier Transforms EmoTrack: Robust Depression Tracking from Counseling Transcripts across Session Regimes Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery Support-aware offline policy selection for advertising marketplaces Double descent for least-squares interpolation on contaminated data: A simulation study Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation Cross-domain benchmarks reveal when coordinated AI agents improve scientific inference from partial evidence When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning $\textit{BlockFormer}$ : Transformer-based inference from interaction maps MMD-Balls as Credal Sets: A PAC-Bayesian Framework for Epistemic Uncertainty in Test-Time Adaptation Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentation Objective-Induced Bias and Search Dynamics in Multiobjective Unsupervised Feature Selection Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs What are the Right Symmetries for Formal Theorem Proving? Leveraging Self-Paced Curriculum Learning for Enhanced Modality Balance in Multimodal Conversational Emotion Recognition On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation Can Transformers Learn to Verify During Backtracking Search? Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation When to Switch, Not Just What: Transition Quality Prediction in Clash Royale Can Breath Biomarkers Causally Influence Blood Glucose? Investigating VOC-Mediated Modulation in Diabetes Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability Holomorphic Neural ODEs with Kolmogorov-Arnold Networks for Interpretable Discovery of Complex Dynamics ARC-STAR: Auditable Post-Hoc Correction for PDE Foundation Models Skill Weaving: Efficient LLM Improvement via Modular Skillpacks From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$-Sparse GLMs Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability Harnesses for Inference-Time Alignment over Execution Trajectories Predicting Performance of Symbolic and Prompt Programs with Examples The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs I-SAFE: Wasserstein Coherence Metrics for Structural Auditing of Scientific AI Models Compiling Agentic Workflows into LLM Weights: Near-Frontier Quality at Two Orders of Magnitude Less Cost Scalable On-Policy Reinforcement Learning via Adaptive Batch Scaling ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning Bandit Convex Optimization with Gradient Prediction Adaptivity Engineering Hybrid Physics-Informed Neural Networks for Next-Generation Electricity Systems: A State-of-the-Art Review Manifold-Guided Attention Steering Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning Noise Schedule Design for Diffusion Models: An Optimal Control Perspective Machine learning prediction of obstructive coronary artery disease using opportunistic coronary calcium and epicardial fat assessments from CT calcium scoring scans Same Architecture, Different Capacity: Optimizer-Induced Spectral Scaling Laws Equilibrium Propagation and Hamiltonian Inference in the Diffusive Fitzhugh-Nagumo Model Provable Joint Decontamination for Benchmarking Multiple Large Language Models Correcting Class Imbalance in Prior-Data Fitted Networks for Tabular Classification A Reproducible Log-Driven AutoML Framework for Interpretable Pipeline Optimization in Healthcare Risk Prediction Three Costs of Amortizing Gaussian Process Inference with Neural Processes OPPO: Bayesian Value Recursion for Token-Level Credit Assignment in LLM Reasoning CASE-NET: Deep Spatio-Temporal Representation Learning via Causal Attention and Channel Recalibration for Multivariate Time Series Classification Beyond Single Slot: Joint Optimization for Multi-Slot Guaranteed Display Advertising One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs LCGuard: Latent Communication Guard for Safe KV Sharing in Multi-Agent Systems Evaluation of Pipelines for Data Integration into Knowledge Graphs Optimal Guarantees for Auditing Rényi Differentially Private Machine Learning Memory-R2: Fair Credit Assignment for Long-Horizon Memory-Augmented LLM Agents
WarmServe: Enabling One-for-Many GPU Prewarming for Multi-LLM Serving
Chiheng Lou, · 2026-05-23 · via cs.LG updates on arXiv.org

View PDF HTML (experimental)

Abstract:Deploying multiple models within shared GPU clusters is a key strategy to improve resource efficiency in large language model (LLM) serving. Existing multi-LLM serving systems improve GPU utilization at the cost of degraded inference performance, particularly time-to-first-token (TTFT). We attribute this degradation to the lack of awareness regarding future workload characteristics. In contrast, recent analyses have shown the strong periodicity and long-term predictability of real-world LLM serving workloads. In this paper, we propose one-for-many GPU prewarming, which proactively loads parameters from multiple models onto GPUs based on workload forecasts. These prewarmed weights enable the system to promptly instantiate serving instances upon encountering request bursts. We design and implement WarmServe, a multi-LLM serving system incorporating three key techniques: (1) a model placement algorithm that optimizes prewarming decisions to minimize cross-model prewarming interference, (2) a KV cache reservation strategy that repurposes idle KV cache space on running GPUs for prewarming new models, and (3) an efficient GPU memory switching mechanism for tensor management. Evaluation on real-world datasets shows that WarmServe reduces tail TTFT by up to 50.8$\times$ compared to the state-of-the-art autoscaling-based system, while supporting up to 2.5$\times$ higher request throughput than the GPU-sharing system.
Comments: Accepted at ICML 2026
Subjects: Distributed, Parallel, and Cluster Computing (cs.DC); Machine Learning (cs.LG)
Cite as: arXiv:2512.09472 [cs.DC]
  (or arXiv:2512.09472v2 [cs.DC] for this version)
  https://doi.org/10.48550/arXiv.2512.09472

arXiv-issued DOI via DataCite

Submission history

From: Chiheng Lou [view email]
[v1] Wed, 10 Dec 2025 09:47:40 UTC (689 KB)
[v2] Thu, 21 May 2026 07:26:42 UTC (554 KB)