Key papers

• Sparse Delta Memory: Scaling the State of Linear RNNs through Sparsity (2026)
  Lo\"ic Cabannes et al.
  9.54
• Research on Edge Computing and Cloud Collaborative Resource Scheduling Optimization Based on Deep Reinforcement Learning (2025)
  Yuqing Wang et al.
  7.96
• ReSpec: Towards Optimizing Speculative Decoding in Reinforcement Learning Systems (2025)
  Qiaoling Chen et al.
  6.56
• Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning (2025)
  Yang Wang et al.
  6.28
• Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis (2024)
  Guangchen Lan et al.
  5.34
• STEEL: Sparsity-Aware Fused Attention for Energy-Efficient Long-Sequence Inference on AMD's XDNA NPU (2026)
  Victor J. B. Jung et al.
  5.01
• Trinity-RFT: A General-Purpose and Unified Framework for Reinforcement Fine-Tuning of Large Language Models (2025)
  Xuchen Pan et al.
  4.87
• Deep Reinforcement Learning for Job Scheduling and Resource Management in Cloud Computing: An Algorithm-Level Review (2025)
  Yan Gu et al.
  4.71
• Think Before You Grid-Search: Floor-First Triage for LLM Serving (2026)
  Yihua Liu
  4.39
• TriRoute: Unified Learned Routing for Joint Adaptive Attention, Experts, and KV-Cache Allocation (2026)
  Andrii Balashov et al.
  4.39
• LLM-Guided Task-Semantic Field Factorization for Industrial Process Forecasting (2026)
  Youcheng Zong et al.
  4.39
• Diffusion enabled Optimal Transport distances for graph matching (2026)
  Iman Seyedi et al.
  4.39
• Entropy-Guided Tensor Compression for Multimodal Federated Learning on Edge Devices (2026)
  Quoc Bao Phan et al.
  4.39
• Robust Federated Learning Under Real-World Client Churn (2026)
  Dhruv Garg et al.
  4.39
• HERO: A Heterogeneity-Aware Benchmark Library for Federated Continual Learning (2026)
  Thinh T. H. Nguyen et al.
  4.39
• Mixed-Timescale Differential Coding for Downlink Model Broadcast in Wireless Federated Learning (2026)
  Chung-Hsuan Hu et al.
  4.39
• CRAWO: Custom Resources for Adaptive Workload Orchestration (2026)
  Eug\^enio Santos et al.
  4.39
• Workload-Aware Caching for Multi-Agent Systems (2026)
  Anas Mohamed et al.
  4.39
• A Framework for Reputation Aware Uninorm-driven Consensus Algorithms for Blockchain Networks (2026)
  Bruno Ramos-Cruz et al.
  4.39
• Clustered Edge Intelligence: Beyond Just Convergence of Edge Computing and AI (2026)
  Chinmaya Kumar Dehury et al.
  4.39
• Spectral Transformation for Layer-wise Global Rank Discovery in Federated LoRA for Vision Transformers (2026)
  Hariharan Ramesh et al.
  4.39
• Accelerating Disaggregated RL for Visual Generative LLMs with Diffusion-Based Parallelism and Trainer-Assisted Generation (2026)
  Sijie Wang et al.
  4.33
• PlexRL: Cluster-Level Orchestration of Serviceized LLM Execution for RLVR (2026)
  Yiqi Zhang et al.
  4.27
• Joint Optimization of Training and Inference in Federated Edge Learning via Constrained Multi-Objective Deep Reinforcement Learning (2026)
  Zhen Li et al.
  4.27
• RL in the Wild: Characterizing RLVR Training in LLM Deployment (2025)
  Jiecheng Zhou et al.
  3.97
• Athena: Synergizing Data Prefetching and Off-Chip Prediction via Online Reinforcement Learning (2026)
  Rahul Bera et al.
  3.92
• Deep Reinforcement Learning for Dynamic Resource Allocation in Wireless Networks (2025)
  Shubham Malhotra et al.
  3.59
• Autonomous Resource Management in Microservice Systems via Reinforcement Learning (2025)
  Yujun Zou et al.
  2.93
• CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning (2025)
  Xiaoya Li et al.
  2.93
• Crowd-SFT: Crowdsourcing for LLM Alignment (2025)
  Alex Sotiropoulos et al.
  2.87
• Reinforcement Learning Optimization for Large-Scale Learning: An Efficient and User-Friendly Scaling Library (2025)
  Weixun Wang et al.
  2.87
• Scaling Multi Agent Reinforcement Learning for Underwater Acoustic Tracking via Autonomous Vehicles (2025)
  Matteo Gallici et al.
  2.82
• Adaptive Security Policy Management in Cloud Environments Using Reinforcement Learning (2025)
  Muhammad Saqib et al.
  2.82
• Distributed Intelligence in the Computing Continuum with Active Inference (2025)
  Victor Casamayor Pujol et al.
  2.82
• Intelligent Offloading in Vehicular Edge Computing: A Comprehensive Review of Deep Reinforcement Learning Approaches and Architectures (2025)
  Ashab Uddin et al.
  2.65
• Enhancing Disaster Resilience with UAV-Assisted Edge Computing: A Reinforcement Learning Approach to Managing Heterogeneous Edge Devices (2025)
  Talha Azfar et al.
  2.60
• DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agents (2024)
  Taiyi Wang et al.
  2.49
• Harmonia: Enhancing Data Placement and Migration in Hybrid Storage Systems via Multi-Agent Reinforcement Learning (2025)
  Rakesh Nadig et al.
  2.18
• Lodestar: An Online-Learning LLM Inference Router (2026)
  Gangmuk Lim et al.
  1.94
• Libra: Efficient Resource Management for Agentic RL Post-Training (2026)
  Kaiwen Chen et al.
  1.94
• SparseRL-Sync: Lossless Weight Synchronization with ~100x Less Communication (2026)
  Lucas Hu et al.
  1.89
• MARLaaS: Multi-Tenant Asynchronous Reinforcement Learning as a Service (2026)
  Timothy Tin Long Yu et al.
  1.89
• Dynamic Transaction Scheduling and Pricing in the Ethereum Mempool (2026)
  Fatemeh Fardno et al.
  1.89
• MARLIN: Multi-Agent Game-Theoretic Reinforcement Learning for Sustainable LLM Inference in Cloud Datacenters (2026)
  H. Moore et al.
  1.89
• Heterogeneous Tasks Offloading in Vehicular Edge Computing: A Federated Meta Deep Reinforcement Learning Approach (2026)
  Yaorong Huang et al.
  1.89
• StreamSplit: Continuous Audio Representation Learning via Uncertainty-Guided Adaptive Splitting (2026)
  Minh K. Quan and Pubudu N. Pathirana
  1.89
• FedQHD: Closed-Form Function-Space Federated Reinforcement Learning (2026)
  Yuchen Hou et al.
  1.89
• CA-AC-MPC: CUDA-Accelerated Actor-Critic Model Predictive Control (2026)
  Antoonio Buo et al.
  1.89
• TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training (2026)
  Chenhao Ye et al.
  1.83
• ARGUS: Agentic GPU Optimization Guided by Data-Flow Invariants (2026)
  Haohui Mai and Xiaoyan Guo and Xiangyun Ding and Daifeng Li and Qiuchu Yu and Chenzhun Guo and Cong Wang and Jiacheng Zhao and Christos Kozyrakis and Binhang Yuan
  1.83
• DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training (2026)
  Tianhao Hu et al.
  1.83
• AGMARL-DKS: An Adaptive Graph-Enhanced Multi-Agent Reinforcement Learning for Dynamic Kubernetes Scheduling (2026)
  Hamed Hamzeh
  1.78
• ARL-Tangram: Unleash the Resource Efficiency in Agentic Reinforcement Learning (2026)
  Bangjun Xiao et al.
  1.78
• DeFRiS: Silo-Cooperative IoT Applications Scheduling via Decentralized Federated Reinforcement Learning (2026)
  Zhiyu Wang et al.
  1.78
• Decentralized Task Scheduling in Distributed Systems: A Deep Reinforcement Learning Approach (2026)
  Daniel Benniah John
  1.78
• Asynchronous MultiAgent Reinforcement Learning for 5G Routing under Side Constraints (2026)
  Sebastian Racedo and Brigitte Jaumard and Oscar Delgado and Meysam Masoudi
  1.72
• FedMOA: Federated GRPO for Personalized Reasoning LLMs under Heterogeneous Rewards (2026)
  Ziyao Wang et al.
  1.72
• ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning (2026)
  Jingwei Song et al.
  1.72
• iScheduler: Reinforcement Learning-Driven Continual Optimization for Large-Scale Resource Investment Problems (2026)
  Yi-Xiang Hu et al.
  1.72
• Reinforcement Learning-Based Dynamic Management of Structured Parallel Farm Skeletons on Serverless Platforms (2026)
  Lanpei Li et al.
  1.72