Saved in:
| Main Authors: | Tung, Nguyen, Nguyen, Tuyen |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.07425 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Trust-Aware Routing for Distributed Generative AI Inference at the Edge
by: Nguyen, Chanh, et al.
Published: (2026)
by: Nguyen, Chanh, et al.
Published: (2026)
Speculative Decoding in Decentralized LLM Inference: Turning Communication Latency into Computation Throughput
by: Song, Jingwei, et al.
Published: (2025)
by: Song, Jingwei, et al.
Published: (2025)
Remoe: Towards Efficient and Low-Cost MoE Inference in Serverless Computing
by: Liu, Wentao, et al.
Published: (2025)
by: Liu, Wentao, 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)
by: Ramachandran, Arun, et al.
Published: (2025)
LLM as HPC Expert: Extending RAG Architecture for HPC Data
by: Miyashita, Yusuke, et al.
Published: (2024)
by: Miyashita, Yusuke, et al.
Published: (2024)
Benchmarking Federated Learning in Edge Computing Environments: A Systematic Review and Performance Evaluation
by: Aribe Jr., Sales, et al.
Published: (2026)
by: Aribe Jr., Sales, et al.
Published: (2026)
Towards Verifiable Federated Unlearning: Framework, Challenges, and The Road Ahead
by: Nguyen, Thanh Linh, et al.
Published: (2025)
by: Nguyen, Thanh Linh, et al.
Published: (2025)
Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers
by: Renney, Harri, et al.
Published: (2026)
by: Renney, Harri, et al.
Published: (2026)
Federated PCA on Grassmann Manifold for IoT Anomaly Detection
by: Nguyen, Tung-Anh, et al.
Published: (2024)
by: Nguyen, Tung-Anh, et al.
Published: (2024)
Accelerating LLM Inference with Precomputed Query Storage
by: Park, Jay H., et al.
Published: (2025)
by: Park, Jay H., et al.
Published: (2025)
Counting Without Running: Evaluating LLMs' Reasoning About Code Complexity
by: Bolet, Gregory, et al.
Published: (2025)
by: Bolet, Gregory, et al.
Published: (2025)
Beyond the Buzz: A Pragmatic Take on Inference Disaggregation
by: Mitra, Tiyasa, et al.
Published: (2025)
by: Mitra, Tiyasa, et al.
Published: (2025)
MSCCL++: Rethinking GPU Communication Abstractions for AI Inference
by: Hwang, Changho, et al.
Published: (2025)
by: Hwang, Changho, et al.
Published: (2025)
LLM Inference Serving: Survey of Recent Advances and Opportunities
by: Li, Baolin, et al.
Published: (2024)
by: Li, Baolin, et al.
Published: (2024)
Decentralized AI: Permissionless LLM Inference on POKT Network
by: Olshansky, Daniel, et al.
Published: (2024)
by: Olshansky, Daniel, et al.
Published: (2024)
Large Language Model Partitioning for Low-Latency Inference at the Edge
by: Kafetzis, Dimitrios, et al.
Published: (2025)
by: Kafetzis, Dimitrios, et al.
Published: (2025)
FairBatching: Fairness-Aware Batch Formation for LLM Inference
by: Lyu, Hongtao, et al.
Published: (2025)
by: Lyu, Hongtao, et al.
Published: (2025)
Taming the Chaos: Coordinated Autoscaling for Heterogeneous and Disaggregated LLM Inference
by: Li, Rongzhi, et al.
Published: (2025)
by: Li, Rongzhi, et al.
Published: (2025)
Opara: Exploiting Operator Parallelism for Expediting DNN Inference on GPUs
by: Chen, Aodong, et al.
Published: (2023)
by: Chen, Aodong, et al.
Published: (2023)
A-IO: Adaptive Inference Orchestration for Memory-Bound NPUs
by: Zhang, Chen, et al.
Published: (2026)
by: Zhang, Chen, et al.
Published: (2026)
Seesaw: High-throughput LLM Inference via Model Re-sharding
by: Su, Qidong, et al.
Published: (2025)
by: Su, Qidong, et al.
Published: (2025)
DeServe: Towards Affordable Offline LLM Inference via Decentralization
by: Wu, Linyu, et al.
Published: (2025)
by: Wu, Linyu, et al.
Published: (2025)
TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms
by: Stojkovic, Jovan, et al.
Published: (2025)
by: Stojkovic, Jovan, et al.
Published: (2025)
KAIROS: Stateful, Context-Aware Power-Efficient Agentic Inference Serving
by: Yuan, Yichao, et al.
Published: (2026)
by: Yuan, Yichao, et al.
Published: (2026)
Token-Budget-Aware Pool Routing for Cost-Efficient LLM Inference
by: Chen, Huamin, et al.
Published: (2026)
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)
by: Kim, Joon Ha, et al.
Published: (2026)
Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference
by: He, Zifan, et al.
Published: (2026)
by: He, Zifan, et al.
Published: (2026)
Profiling-Driven Adaptive Distributed Transformer Inference on Embedded Edge Deployment
by: Qazi, Muhammad Azlan, et al.
Published: (2026)
by: Qazi, Muhammad Azlan, et al.
Published: (2026)
Identifying and Mitigating Systemic Measurement Bias in Production LLM Inference Benchmarks
by: Chandrasekar, Ashok, et al.
Published: (2026)
by: Chandrasekar, Ashok, et al.
Published: (2026)
ELANA: A Simple Energy and Latency Analyzer for LLMs
by: Chiang, Hung-Yueh, et al.
Published: (2025)
by: Chiang, Hung-Yueh, et al.
Published: (2025)
Balanced and Elastic End-to-end Training of Dynamic LLMs
by: Wahib, Mohamed, et al.
Published: (2025)
by: Wahib, Mohamed, et al.
Published: (2025)
Why Smaller Is Slower? Dimensional Misalignment in Compressed LLMs
by: Xin, Jihao, et al.
Published: (2026)
by: Xin, Jihao, et al.
Published: (2026)
KVSwap: Disk-aware KV Cache Offloading for Long-Context On-device Inference
by: Zhang, Huawei, et al.
Published: (2025)
by: Zhang, Huawei, et al.
Published: (2025)
Reconstruction-Based Adaptive Scheduling Using AI Inferences in Safety-Critical Systems
by: Alshaer, Samer, et al.
Published: (2025)
by: Alshaer, Samer, et al.
Published: (2025)
SpecEE: Accelerating Large Language Model Inference with Speculative Early Exiting
by: Xu, Jiaming, et al.
Published: (2025)
by: Xu, Jiaming, et al.
Published: (2025)
FlowSpec: Continuous Pipelined Speculative Decoding for Efficient Distributed LLM Inference
by: Liu, Xing, et al.
Published: (2025)
by: Liu, Xing, et al.
Published: (2025)
AIBrix: Towards Scalable, Cost-Effective Large Language Model Inference Infrastructure
by: The AIBrix Team, et al.
Published: (2025)
by: The AIBrix Team, et al.
Published: (2025)
Efficient MoE Inference with Fine-Grained Scheduling of Disaggregated Expert Parallelism
by: Pan, Xinglin, et al.
Published: (2025)
by: Pan, Xinglin, et al.
Published: (2025)
Verify Distributed Deep Learning Model Implementation Refinement with Iterative Relation Inference
by: Wang, Zhanghan, et al.
Published: (2025)
by: Wang, Zhanghan, et al.
Published: (2025)
ECCENTRIC: Edge-Cloud Collaboration Framework for Distributed Inference Using Knowledge Adaptation
by: Kamani, Mohammad Mahdi, et al.
Published: (2025)
by: Kamani, Mohammad Mahdi, et al.
Published: (2025)
Similar Items
-
Trust-Aware Routing for Distributed Generative AI Inference at the Edge
by: Nguyen, Chanh, et al.
Published: (2026) -
Speculative Decoding in Decentralized LLM Inference: Turning Communication Latency into Computation Throughput
by: Song, Jingwei, et al.
Published: (2025) -
Remoe: Towards Efficient and Low-Cost MoE Inference in Serverless Computing
by: Liu, Wentao, 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) -
LLM as HPC Expert: Extending RAG Architecture for HPC Data
by: Miyashita, Yusuke, et al.
Published: (2024)