{"total":131,"rows":[{"id":"2309.06180","title":"Efficient Memory Management for Large Language Model Serving with PagedAttention","created":"2023-09-12","cited_by_count":5944,"area":"inference"},{"id":"2302.01318","title":"Accelerating Large Language Model Decoding with Speculative Sampling","created":"2023-02-02","cited_by_count":1006,"area":"inference"},{"id":"2401.09670","title":"DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving","created":"2024-01-18","cited_by_count":617,"area":"inference"},{"id":"2403.02310","title":"Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve","created":"2024-03-04","cited_by_count":526,"area":"inference"},{"id":"2305.09781","title":"SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification","created":"2023-05-16","cited_by_count":365,"area":"inference"},{"id":"2402.02057","title":"Break the Sequential Dependency of LLM Inference Using Lookahead Decoding","created":"2024-02-03","cited_by_count":298,"area":"inference"},{"id":"2310.07240","title":"CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Serving","created":"2023-10-11","cited_by_count":203,"area":"inference"},{"id":"2308.16369","title":"SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills","created":"2023-08-31","cited_by_count":193,"area":"inference"},{"id":"2406.03243","title":"Llumnix: Dynamic Scheduling for Large Language Model Serving","created":"2024-06-05","cited_by_count":174,"area":"inference"},{"id":"2305.05920","title":"Fast Distributed Inference Serving for Large Language Models","created":"2023-05-10","cited_by_count":145,"area":"inference"},{"id":"2405.12981","title":"Reducing Transformer Key-Value Cache Size with Cross-Layer Attention","created":"2024-05-21","cited_by_count":131,"area":"inference"},{"id":"2404.09526","title":"LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism","created":"2024-04-15","cited_by_count":112,"area":"inference"},{"id":"2312.15234","title":"Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems","created":"2023-12-23","cited_by_count":102,"area":"inference"},{"id":"2408.12757","title":"NanoFlow: Towards Optimal Large Language Model Serving Throughput","created":"2024-08-22","cited_by_count":90,"area":"inference"},{"id":"2311.15566","title":"SpotServe: Serving Generative Large Language Models on Preemptible Instances","created":"2023-11-27","cited_by_count":87,"area":"inference"},{"id":"2305.13144","title":"Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline","created":"2023-05-22","cited_by_count":86,"area":"inference"},{"id":"2408.15792","title":"Efficient LLM Scheduling by Learning to Rank","created":"2024-08-28","cited_by_count":85,"area":"inference"},{"id":"2401.02669","title":"Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache","created":"2024-01-05","cited_by_count":73,"area":"inference"},{"id":"2312.04916","title":"EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism","created":"2023-12-08","cited_by_count":69,"area":"inference"},{"id":"2312.05516","title":"Stateful Large Language Model Serving with Pensieve","created":"2023-12-09","cited_by_count":61,"area":"inference"},{"id":"2203.13240","title":"Token Dropping for Efficient BERT Pretraining","created":"2022-03-24","cited_by_count":42,"area":"inference"},{"id":"2502.14051","title":"RocketKV: Accelerating Long-Context LLM Inference via Two-Stage KV Cache Compression","created":"2025-02-19","cited_by_count":41,"area":"inference"},{"id":"2502.04420","title":"KVTuner: Sensitivity-Aware Layer-Wise Mixed-Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference","created":"2025-02-06","cited_by_count":40,"area":"inference"},{"id":"2411.02886","title":"TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection","created":"2024-11-05","cited_by_count":39,"area":"inference"},{"id":"2403.09919","title":"Recurrent Drafter for Fast Speculative Decoding in Large Language Models","created":"2024-03-14","cited_by_count":37,"area":"inference"},{"id":"2402.01869","title":"InferCept: Efficient Intercept Support for Augmented Large Language Model Inference","created":"2024-02-02","cited_by_count":33,"area":"inference"},{"id":"2504.06261","title":"Hogwild! Inference: Parallel LLM Generation via Concurrent Attention","created":"2025-04-08","cited_by_count":32,"area":"inference"},{"id":"2408.05499","title":"LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at Scale","created":"2024-08-10","cited_by_count":31,"area":"inference"},{"id":"2505.09999","title":"ServeGen: Workload Characterization and Generation of Large Language Model Serving in Production","created":"2025-05-15","cited_by_count":29,"area":"inference"},{"id":"2412.03131","title":"DiffKV: Differentiated Memory Management for Large Language Models with Parallel KV Compaction","created":"2024-12-04","cited_by_count":26,"area":"inference"},{"id":"2402.13720","title":"Ouroboros: Generating Longer Drafts Phrase by Phrase for Faster Speculative Decoding","created":"2024-02-21","cited_by_count":25,"area":"inference"},{"id":"2411.17116","title":"Star Attention: Efficient LLM Inference over Long Sequences","created":"2024-11-26","cited_by_count":25,"area":"inference"},{"id":"2502.09334","title":"ThunderServe: High-performance and Cost-efficient LLM Serving in Cloud Environments","created":"2025-02-13","cited_by_count":23,"area":"inference"},{"id":"2502.00722","title":"Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs","created":"2025-02-02","cited_by_count":22,"area":"inference"},{"id":"2502.07578","title":"PIM Is All You Need: A CXL-Enabled GPU-Free System for Large Language Model Inference","created":"2025-02-11","cited_by_count":22,"area":"inference"},{"id":"2505.07203","title":"PrefillOnly: An Inference Engine for Prefill-only Workloads in Large Language Model Applications","created":"2025-05-12","cited_by_count":21,"area":"inference"},{"id":"2410.03960","title":"SwiftKV: Fast Prefill-Optimized Inference with Knowledge-Preserving Model Transformation","created":"2024-10-04","cited_by_count":19,"area":"inference"},{"id":"2410.03804","title":"Mixture of Attentions For Speculative Decoding","created":"2024-10-04","cited_by_count":17,"area":"inference"},{"id":"2410.00428","title":"LayerKV: Optimizing Large Language Model Serving with Layer-wise KV Cache Management","created":"2024-10-01","cited_by_count":16,"area":"inference"},{"id":"2504.19720","title":"Taming the Titans: A Survey of Efficient LLM Inference Serving","created":"2025-04-28","cited_by_count":16,"area":"inference"},{"id":"2503.06433","title":"Seesaw: High-throughput LLM Inference via Model Re-sharding","created":"2025-03-09","cited_by_count":15,"area":"inference"},{"id":"2402.00518","title":"EE-Tuning: An Economical yet Scalable Solution for Tuning Early-Exit Large Language Models","created":"2024-02-01","cited_by_count":13,"area":"inference"},{"id":"2406.01698","title":"Demystifying AI Platform Design for Distributed Inference of Next-Generation LLM models","created":"2024-06-03","cited_by_count":12,"area":"inference"},{"id":"2305.15273","title":"Revisiting Token Dropping Strategy in Efficient BERT Pretraining","created":"2023-05-24","cited_by_count":11,"area":"inference"},{"id":"2412.20322","title":"GreenLLM: Disaggregating Large Language Model Serving on Heterogeneous GPUs for Lower Carbon Emissions","created":"2024-12-29","cited_by_count":10,"area":"inference"},{"id":"2501.14808","title":"HyGen: Efficient LLM Serving via Elastic Online-Offline Request Co-location","created":"2025-01-15","cited_by_count":10,"area":"inference"},{"id":"2505.17052","title":"SpecEdge: Scalable Edge-Assisted Serving Framework for Interactive LLMs","created":"2025-05-16","cited_by_count":10,"area":"inference"},{"id":"2507.11953","title":"IAM: Efficient Inference through Attention Mapping between Different-scale LLMs","created":"2025-07-16","cited_by_count":10,"area":"inference"},{"id":"2508.15601","title":"LMDeploy Accelerates Mixed-Precision LLM Inference with TurboMind","created":"2025-08-21","cited_by_count":10,"area":"inference"},{"id":"2606.16824","title":"CacheWise: Understanding Workloads and Optimizing KVCache Management for Efficiently Serving LLM Coding Agents","created":"2026-06-15","cited_by_count":10,"area":"inference"},{"id":"2501.08192","title":"PRESERVE: Prefetching Model Weights and KV-Cache in Distributed LLM Serving","created":"2025-01-14","cited_by_count":9,"area":"inference"},{"id":"2506.11309","title":"SwiftSpec: Ultra-Low Latency LLM Decoding by Scaling Asynchronous Speculative Decoding","created":"2025-06-12","cited_by_count":9,"area":"inference"},{"id":"2504.10724","title":"HELIOS: Adaptive Model And Early-Exit Selection for Efficient LLM Inference Serving","created":"2025-04-14","cited_by_count":8,"area":"inference"},{"id":"2606.23050","title":"Unlimited OCR Works","created":"2026-06-22","cited_by_count":8,"area":"inference"},{"id":"2403.08845","title":"Bifurcated Attention: Accelerating Massively Parallel Decoding with Shared Prefixes in LLMs","created":"2024-03-13","cited_by_count":7,"area":"inference"},{"id":"2507.07120","title":"Helix Parallelism: Rethinking Sharding Strategies for Interactive Multi-Million-Token LLM Decoding","created":"2025-07-07","cited_by_count":7,"area":"inference"},{"id":"2401.09486","title":"LoMA: Lossless Compressed Memory Attention","created":"2024-01-16","cited_by_count":6,"area":"inference"},{"id":"2405.05329","title":"KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation","created":"2024-05-08","cited_by_count":6,"area":"inference"},{"id":"2502.15572","title":"DReSD: Dense Retrieval for Speculative Decoding","created":"2025-02-21","cited_by_count":6,"area":"inference"},{"id":"2504.07494","title":"Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving","created":"2025-04-10","cited_by_count":6,"area":"inference"},{"id":"2505.23022","title":"Scorpio: Serving Right Requests at the Right Time for Heterogeneous SLOs in LLM Inference","created":"2025-05-29","cited_by_count":6,"area":"inference"},{"id":"2601.10729","title":"OrbitFlow: SLO-Aware Long-Context LLM Serving with Fine-Grained KV Cache Reconfiguration","created":"2026-01-05","cited_by_count":6,"area":"inference"},{"id":"2602.10729","title":"BOute: Cost-Efficient LLM Serving with Heterogeneous LLMs and GPUs via Multi-Objective Bayesian Optimization","created":"2026-02-11","cited_by_count":6,"area":"inference"},{"id":"2602.22593","title":"FLYING SERVING: On-the-Fly Parallelism Switching for Large Language Model Serving","created":"2026-02-26","cited_by_count":6,"area":"inference"},{"id":"2404.18322","title":"BlockLLM: Multi-tenant Finer-grained Serving for Large Language Models","created":"2024-04-28","cited_by_count":5,"area":"inference"},{"id":"2405.13019","title":"A Comprehensive Survey of Accelerated Generation Techniques in Large Language Models","created":"2024-05-15","cited_by_count":5,"area":"inference"},{"id":"2412.20166","title":"PIMphony: Overcoming Bandwidth and Capacity Inefficiency in PIM-based Long-Context LLM Inference System","created":"2024-12-28","cited_by_count":5,"area":"inference"},{"id":"2506.04203","title":"Cascadia: An Efficient Cascade Serving System for Large Language Models","created":"2025-06-04","cited_by_count":5,"area":"inference"},{"id":"2603.17946","title":"CARE: Covariance-Aware and Rank-Enhanced Decomposition for Enabling Multi-Head Latent Attention","created":"2026-03-18","cited_by_count":5,"area":"inference"},{"id":"2409.15012","title":"Inference-Friendly Models With MixAttention","created":"2024-09-23","cited_by_count":4,"area":"inference"},{"id":"2502.09921","title":"A Cost-Effective Near-Storage Processing Solution for Offline Inference of Long-Context LLMs","created":"2025-02-14","cited_by_count":4,"area":"inference"},{"id":"2503.04253","title":"ADOR: A Design Exploration Framework for LLM Serving with Enhanced Latency and Throughput","created":"2025-03-06","cited_by_count":4,"area":"inference"},{"id":"2504.04104","title":"SpecPipe: Accelerating Pipeline Parallelism-based LLM Inference with Speculative Decoding","created":"2025-04-05","cited_by_count":4,"area":"inference"},{"id":"2510.13602","title":"NOSA: Native and Offloadable Sparse Attention","created":"2025-10-15","cited_by_count":4,"area":"inference"},{"id":"2602.02108","title":"Out of the Memory Barrier: A Highly Memory Efficient Training System for LLMs with Million-Token Contexts","created":"2026-02-02","cited_by_count":4,"area":"inference"},{"id":"2605.21312","title":"Frontier: Towards Comprehensive and Accurate LLM Inference Simulation","created":"2026-05-20","cited_by_count":4,"area":"inference"},{"id":"2502.02493","title":"EasySpec: Layer-Parallel Speculative Decoding for Efficient Multi-GPU Utilization","created":"2025-02-04","cited_by_count":3,"area":"inference"},{"id":"2503.08461","title":"FastCache: Optimizing Multimodal LLM Serving through Lightweight KV-Cache Compression Framework","created":"2025-03-11","cited_by_count":3,"area":"inference"},{"id":"2504.08791","title":"Prima.cpp: Fast 30-70B LLM Inference on Heterogeneous and Low-Resource Home Clusters","created":"2025-04-07","cited_by_count":3,"area":"inference"},{"id":"2508.15919","title":"HFX: Joint Design of Algorithms and Systems for Multi-SLO Serving and Fast Scaling","created":"2025-08-21","cited_by_count":3,"area":"inference"},{"id":"2509.17542","title":"Disaggregated Prefill and Decoding Inference System for Large Language Model Serving on Multi-Vendor GPUs","created":"2025-09-22","cited_by_count":3,"area":"inference"},{"id":"2601.22438","title":"Towards Resiliency in Large Language Model Serving with KevlarFlow","created":"2026-01-30","cited_by_count":3,"area":"inference"},{"id":"2602.12151","title":"OServe: Accelerating LLM Serving via Spatial-Temporal Workload Orchestration","created":"2026-02-12","cited_by_count":3,"area":"inference"},{"id":"2604.12171","title":"PipeLive: Efficient Live In-place Pipeline Parallelism Reconfiguration for Dynamic LLM Serving","created":"2026-04-14","cited_by_count":3,"area":"inference"},{"id":"2605.00831","title":"GhostServe: A Lightweight Checkpointing System in the Shadow for Fault-Tolerant LLM Serving","created":"2026-03-26","cited_by_count":3,"area":"inference"},{"id":"2605.07719","title":"An Efficient Hybrid Sparse Attention with CPU-GPU Parallelism for Long-Context Inference","created":"2026-05-08","cited_by_count":3,"area":"inference"},{"id":"2410.21340","title":"Meta-Learning for Speeding Up Large Model Inference in Decentralized Environments","created":"2024-10-28","cited_by_count":2,"area":"inference"},{"id":"2504.09590","title":"Efficient LLM Serving on Hybrid Real-time and Best-effort Requests","created":"2025-04-13","cited_by_count":2,"area":"inference"},{"id":"2509.04827","title":"VoltanaLLM: Energy-Efficient and SLO-Aware Disaggregated LLM Serving via Adaptive Frequency Control and State-Space Routing","created":"2025-09-05","cited_by_count":2,"area":"inference"},{"id":"2510.13161","title":"Mirror Speculative Decoding: Breaking the Serial Barrier in LLM Inference","created":"2025-10-15","cited_by_count":2,"area":"inference"},{"id":"2605.04357","title":"Coral: Cost-Efficient Multi-LLM Serving over Heterogeneous Cloud GPUs","created":"2026-05-05","cited_by_count":2,"area":"inference"},{"id":"2606.16135","title":"SwiftCache: Efficient LLM Serving for Multi-turn Conversations with Heterogeneous KV Cache Sharing","created":"2026-06-15","cited_by_count":2,"area":"inference"},{"id":"2501.13111","title":"iServe: An Intent-based Serving System for LLMs","created":"2025-01-08","cited_by_count":1,"area":"inference"},{"id":"2502.17728","title":"LLM Inference Acceleration via Efficient Operation Fusion","created":"2025-02-24","cited_by_count":1,"area":"inference"},{"id":"2505.23219","title":"Ghidorah: Fast LLM Inference on Edge with Speculative Decoding and Hetero-Core Parallelism","created":"2025-05-29","cited_by_count":1,"area":"inference"},{"id":"2506.07311","title":"Paged Attention Meets FlexAttention: Unlocking Long-Context Efficiency in Deployed Inference","created":"2025-06-08","cited_by_count":1,"area":"inference"},{"id":"2507.02620","title":"FlowSpec: Continuous Pipelined Speculative Decoding for Efficient Distributed LLM Inference","created":"2025-07-03","cited_by_count":1,"area":"inference"},{"id":"2507.18006","title":"Unlock the Potential of Fine-grained LLM Serving via Dynamic Module Scaling","created":"2025-07-24","cited_by_count":1,"area":"inference"},{"id":"2508.15881","title":"TPLA: Tensor Parallel Latent Attention for Efficient Disaggregated Prefill and Decode Inference","created":"2025-08-21","cited_by_count":1,"area":"inference"},{"id":"2511.11733","title":"Speculative Decoding in Decentralized LLM Inference: Turning Communication Latency into Computation Throughput","created":"2025-11-13","cited_by_count":1,"area":"inference"}],"next_cursor":"100"}