Cover Image

B-PASTE: Beam-Aware Pattern-Guided Speculative Execution for Resource-Constrained LLM Agents

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Song, Yanfei
Format:	Preprint
Published:	2026
Subjects:	Distributed, Parallel, and Cluster Computing Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Act While Thinking: Accelerating LLM Agents via Pattern-Aware Speculative Tool Execution
by: Sui, Yifan, et al.
Published: (2026)

SPECTRE: Hybrid Ordinary-Parallel Speculative Serving for Resource-Efficient LLM Inference
by: Xie, Jincheng, et al.
Published: (2026)

Speculative Decoding in Decentralized LLM Inference: Turning Communication Latency into Computation Throughput
by: Song, Jingwei, et al.
Published: (2025)

Fast LLM Post-training via Decoupled and Fastest-of-N Speculation
by: Cheng, Rongxin, et al.
Published: (2025)

StreamServe: Adaptive Speculative Flows for Low-Latency Disaggregated LLM Serving
by: Kumar, Satyam, et al.
Published: (2026)

FlowSpec: Continuous Pipelined Speculative Decoding for Efficient Distributed LLM Inference
by: Liu, Xing, et al.
Published: (2025)

SpecBranch: Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch Parallelism
by: Shen, Yuhao, et al.
Published: (2025)

Safe and Compliant Cross-Market Trade Execution via Constrained RL and Zero-Knowledge Audits
by: Borjigin, Ailiya, et al.
Published: (2025)

Striking the Right Balance between Compute and Copy: Improving LLM Inferencing Under Speculative Decoding
by: Ramachandran, Arun, et al.
Published: (2025)

Federated Fine-Tuning of Sparsely-Activated Large Language Models on Resource-Constrained Devices
by: Chen, Fahao, et al.
Published: (2025)

SMART: When is it Actually Worth Expanding a Speculative Tree?
by: Wang, Lifu, et al.
Published: (2026)

SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding
by: Abramovich, Talor, et al.
Published: (2026)

LLM-42: Enabling Determinism in LLM Inference with Verified Speculation
by: Gond, Raja, et al.
Published: (2026)

Hardware-Aware Reformulation of Convolutions for Efficient Execution on Specialized AI Hardware: A Case Study on NVIDIA Tensor Cores
by: Bikshandi, Ganesh
Published: (2026)

Nightjar: Dynamic Adaptive Speculative Decoding for Large Language Models Serving
by: Li, Rui, et al.
Published: (2025)

Artificial Intelligence for Cost-Aware Resource Prediction in Big Data Pipelines
by: Goyal, Harshit
Published: (2025)

Byzantine-Robust Decentralized Coordination of LLM Agents
by: Jo, Yongrae, et al.
Published: (2025)

SpecEE: Accelerating Large Language Model Inference with Speculative Early Exiting
by: Xu, Jiaming, et al.
Published: (2025)

LAPS: A Length-Aware-Prefill LLM Serving System
by: She, Jianshu, et al.
Published: (2026)

PALS: Power-Aware LLM Serving for Mixture-of-Experts Models
by: Hankendi, Can, et al.
Published: (2026)

FairBatching: Fairness-Aware Batch Formation for LLM Inference
by: Lyu, Hongtao, et al.
Published: (2025)

ModServe: Modality- and Stage-Aware Resource Disaggregation for Scalable Multimodal Model Serving
by: Qiu, Haoran, et al.
Published: (2025)

KORAL: Knowledge Graph Guided LLM Reasoning for SSD Operational Analysis
by: Akewar, Mayur, et al.
Published: (2026)

Token-Budget-Aware Pool Routing for Cost-Efficient LLM Inference
by: Chen, Huamin, et al.
Published: (2026)

Dooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation
by: Kim, Joon Ha, et al.
Published: (2026)

TinyServe: Query-Aware Cache Selection for Efficient LLM Serving
by: Liu, Dong, et al.
Published: (2025)

TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms
by: Stojkovic, Jovan, et al.
Published: (2025)

HiveMind: OS-Inspired Scheduling for Concurrent LLM Agent Workloads
by: Agyemang, Justice Owusu, et al.
Published: (2026)

Watt Counts: Energy-Aware Benchmark for Sustainable LLM Inference on Heterogeneous GPU Architectures
by: Argerich, Mauricio Fadel, et al.
Published: (2026)

KVComp: A High-Performance, LLM-Aware, Lossy Compression Framework for KV Cache
by: Jiang, Bo, et al.
Published: (2025)

VibeServe: Can AI Agents Build Bespoke LLM Serving Systems?
by: Kamahori, Keisuke, et al.
Published: (2026)

PackKV: Reducing KV Cache Memory Footprint through LLM-Aware Lossy Compression
by: Jiang, Bo, et al.
Published: (2025)

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation
by: Kaplan, Erel, et al.
Published: (2026)

MoE-Lens: Towards the Hardware Limit of High-Throughput MoE LLM Serving Under Resource Constraints
by: Yuan, Yichao, et al.
Published: (2025)

Distributed Speculative Execution for Resilient Cloud Applications
by: Li, Tianyu, et al.
Published: (2024)

DeServe: Towards Affordable Offline LLM Inference via Decentralization
by: Wu, Linyu, et al.
Published: (2025)

BucketServe: Bucket-Based Dynamic Batching for Smart and Efficient LLM Inference Serving
by: Zheng, Wanyi, et al.
Published: (2025)

ProMoE: Fast MoE-based LLM Serving using Proactive Caching
by: Song, Xiaoniu, et al.
Published: (2024)

A Resource-Adaptive Approach for Federated Learning under Resource-Constrained Environments
by: Zhang, Ruirui, et al.
Published: (2024)

Mixture-of-Schedulers: An Adaptive Scheduling Agent as a Learned Router for Expert Policies
by: Wang, Xinbo, et al.
Published: (2025)