Key papers

• ELDR: Expert-Locality-Aware Decode Routing for PD-Disaggregated MoE Serving (2026)
  Sangjin Choi et al.
  11.22
• Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning (2026)
  Jian Hu et al.
  6.72
• Modeling and Chasing the Energy-Efficiency Sweet Spots in Modern GPUs (2026)
  Ayesha Afzal et al.
  5.01
• Mixture-of-Parallelisms: Towards Memory-Efficient Training Stack for Mixture-of-Experts Models (2026)
  Xuan-Phi Nguyen et al.
  5.01
• WattGPU: Predicting Inference Power and Latency on Unseen GPUs and LLMs (2026)
  Mauricio Fadel Argerich et al.
  5.01
• SmoothAgent: Efficient Long-Horizon LLM-Based Agent Serving with Lookahead Context Engineering (2026)
  Zaifeng Pan et al.
  4.39
• CloudyGUI: A Novel Python-based Framework for Auto-Scaling and Cloud Workload Analysis (2026)
  Jyoti Bawa et al.
  4.39
• All-out Attack: Optimal Block Withholding Under Pay-Per-Share Scheme (2026)
  Mustafa Doger et al.
  4.39
• HYPIC: Accelerating Hybrid-Attention LLM Serving with Position-Independent Caching (2026)
  Yifei Liu et al.
  4.39
• The Rollout Infrastructure Tax in Coding-Agent Reinforcement Learning (2026)
  Daniel Thi Graviet et al.
  4.39
• SLFS: a Flexible, Low-Cost Distributed File System Using Serverless Designs (2026)
  Cheng Hao (Ryan) et al.
  4.39
• DeadPool: Resilient LLM Training with Hot-Swapping via Zero-Overhead Checkpoint (2026)
  Haotian Xie et al.
  4.39
• SCAPE: Accurate and Efficient LLM Training with Extreme Sparse Communication (2026)
  Mingkai Zheng et al.
  4.39
• Arachne: Orchestrating Cascades for Efficient Text-to-Video Model Training (2026)
  Peng Yu et al.
  4.39
• Exploiting Task-Based Parallelism for the Red-Black Gauss-Seidel Method on 2D Grids (2026)
  Shiting Long et al.
  4.39
• HCMS: Head-Chunked Multi-Stream Pipeline for Communication-Computation Overlap in Long-Sequence Parallel Attention (2026)
  Chao Yuan et al.
  4.39
• Lynx: Progressive Speculative Quantization for accelerating KV Transfer in Long-Context Inference (2026)
  Wenchen Han et al.
  4.39
• Cadence: Extreme Pipelining with Multiple Concurrent Proposers (2026)
  Fatima Elsheimy et al.
  4.39
• FlintKV: A Fast Durable Storage Engine for Modern Databases (2026)
  Sergey Egorov (Royal Holloway et al.
  4.39
• Multi-Factor Trust-Driven Secure Communication Model for Cloud-Based Digital Twins (2026)
  Deepika Saxena and Ashutosh Kumar Singh
  4.27
• Semantic-aware Token Selection and Resource Optimization for Communication-efficient Split Federated Fine-tuning in Edge Intelligence (2026)
  Xianke Qiang et al.
  4.27
• Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System (2026)
  Cheng-Wei Ching et al.
  4.27
• Autonomic Federated-Market Orchestration for the Edge-Cloud Continuum (2026)
  Lauri Lov\'en et al.
  4.27
• Polynomial Histograms for Memory-Efficient Representation of Long-tailed System Distributions (2026)
  Murray Stokely et al.
  4.27
• Federated Variational Preference Alignment with Gumbel-Softmax Prior for Personalized User Preferences (2026)
  Jabin Koo et al.
  4.27
• A Datalog Framework for Conflict-Free Replicated Data Types (2026)
  Elena Yanakieva et al.
  4.27
• Floe: Federated Specialization for Real-Time LLM-SLM Inference (2026)
  Chunlin Tian et al.
  3.98
• Design rules for fault-tolerant multi-gate teleportation (2026)
  Mathys Rennela
  3.51
• ADASCALE: An Adaptive Scaling and Placement Framework for Microservices Under Dynamics (2026)
  Ming Chen et al.
  3.51
• Safecloud: A Distributed, Encrypted Storage Cloud for Streaming (2026)
  Gregory Magarshak
  3.45
• FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture (2025)
  Somayeh Sobati-M
  2.93
• Time-varying Mixing Matrix Design for Energy-efficient Decentralized Federated Learning (2025)
  Xusheng Zhang et al.
  2.68
• When Less is More: Achieving Faster Convergence in Distributed Edge Machine Learning (2024)
  Advik Raj Basani et al.
  2.49
• Entanglement geometry separates circuit cutting, classical hardness, and trainability (2026)
  Maria Gragera Garces et al.
  2.00
• Keeping the Cache Warm Pays: Keepalive Economics for Agentic Workloads (2026)
  Maxim Khailo
  2.00
• FBLayout: Optimizing Memory Layout for Efficient LLM Finetuning on Mobile GPUs (2026)
  Kahou Tam et al.
  2.00
• PRISM: Evaluating POSIX Storage Systems for AI Research Workflows (2026)
  Adithya Kumar et al.
  2.00
• Decentralized Compute on Untrusted Hardware Using Intel TDX and Encrypted CVMs (2026)
  Venish Patidar et al.
  2.00
• Unified Static-Dynamic Pruning for Efficient LLM Inference (2026)
  Jinhyeok Kim et al.
  2.00
• Smart Contract Tells: Aircraft Maintenance Records Are Now Trustworthy (2026)
  Woosuk Choi et al.
  2.00
• Accountable Transaction Inclusion Lists: Enhancing Ethereum's Censorship Resistance (2026)
  Patrick Spiesberger et al.
  2.00
• Duet: Co-Optimizing P2P Message Propagation and Rotating-Leader Consensus (2026)
  Yifeng Ye et al.
  2.00
• Agentic CPU-GPU Scheduling for Heterogeneous AI Workloads (2026)
  Tianxi Lu et al.
  2.00
• NUMA balancing hampering performance of spiking network simulations (2026)
  Melissa Lober et al.
  2.00
• TileSight: A First-Principles Tile-Centric Analytical GPU Performance Model from Cores to Clusters (2026)
  Zhiwen Mo et al.
  2.00
• GuidaPA: Privacy-Preserving Chatbot for Public Administration via Federated Learning (2026)
  Daniel M. Jimenez-Gutierrez et al.
  1.94
• Boosting Multimodal Federated Learning via Chained Modality Optimization (2026)
  Zixin Zhang et al.
  1.94
• IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning (2026)
  Farhin Farhad Riya et al.
  1.94
• PoCQ: Proof of Contribution Quality as a Lightweight Blockchain Consensus for Secure Federated Learning (2026)
  Sudad Abed et al.
  1.94
• Towards Serverless Semi-Decentralized Federated Learning with Heterogeneous Optimizers (2026)
  Su Wang et al.
  1.94
• Predictive Autoscaling in Cloud-Native and Federated Cloud-Edge Computing Environments: A Taxonomy and Future Directions (2026)
  Bablu Kumar et al.
  1.94
• HASA: Subnet Allocation for Compute-Constrained Model-Heterogeneous Federated Learning (2026)
  Amir Hossein Shahdadian et al.
  1.94
• AlignFed: Alignment-Aware Asynchronous Federated Fine-Tuning for Large Language Models in Heterogeneous Edge Environments (2026)
  Yan Wang et al.
  1.94
• Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning (2026)
  Sheng Wan et al.
  1.94
• Unifying von-Neumann HPC and Neuromorphic Acceleration via the EBRAINS Research Infrastructure: A Framework for High-Performance Workflows (2026)
  Krishna Kant Singh et al.
  1.94
• JiRAIYA: A Reputation-Based Hierarchical Federated Learning Framework on Web3 (2026)
  Venkata Raghava Kurada and Pallav Kumar Baruah
  1.94
• Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers (2026)
  Samuel Erickson et al.
  1.94
• FedACT: Concurrent Federated Intelligence across Heterogeneous Data Sources (2026)
  Md Sirajul Islam et al.
  1.89
• Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design (2026)
  Seyed Mohammad Azimi-Abarghouyi et al.
  1.89
• FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training (2026)
  Yijiang Li et al.
  1.89