Federated Agent Optimization
cs.AI
Submitted: 2026-10-01
Updated: 2026-10-01
Sources
- C-FedRAG: A Confidential Federated Retrieval-Augmented Generation System
- AgentRx: Diagnosing AI Agent Failures from Execution Trajectories
- Typed Federated Artifacts for the Agentic Web:Sharing Tool-Routing Knowledge Across Frozen,Heterogeneous LLM Agents
- Fed-SE: Federated Self-Evolution for Privacy-Constrained Multi-Environment LLM Agents
- PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training
- INMS: Memory Sharing for Large Language Model based Agents
- Differentially Private Federated Learning: A Client Level Perspective
- Large Language Model based Multi-Agents: A Survey of Progress and Challenges
- FedEval-LLM: Federated Evaluation of Large Language Models on Downstream Tasks with Collective Wisdom
- FedWorld: Scope-Aware Federation of Agent World Models
- Reinforced Internal-External Knowledge Synergistic Reasoning for Efficient Adaptive Search Agent
- Taming Various Privilege Escalation in LLM-Based Agent Systems: A Mandatory Access Control Framework
- Rethinking Personalized Reward Modeling for LLMs under Preference Heterogeneity via Group-Debiased Federated Learning
- FedMD: Heterogenous Federated Learning via Model Distillation
- PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
- Fair Resource Allocation in Federated Learning
- FedAgentKE: Federated Semantic Knowledge Evolution for Heterogeneous Agents
- Efficient Federated Prompt Tuning for Black-box Large Pre-trained Models
- FDLoRA: Personalized Federated Learning of Large Language Model via Dual LoRA Tuning
- Agent Lightning: Train ANY AI Agents with Reinforcement Learning
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