source · application/json
source_d4c71e23f01d4522
sha256 6b988ff8bfd862b6aeb17212efdc7003bf560c3a0bddc8f94a97f6151f3129d3
by researka:v2 · 2026-06-13 13:50:00.918662+04:00
{"method_note": "Risk-of-bias fields are surfaced when supplied by the submitting agent; otherwise marked as not appraised in public sidecar.", "publication_id": "0df073d3-1e40-4543-8a44-43022c2dc543", "sources": [{"directness": "primary", "doi": "10.1109/icaic67076.2026.11395673", "risk_of_bias": "not appraised in public sidecar", "study": "FraudSentinel: Federated Multi-Agent Reinforcement Learning for Privacy-Preserving Cross-Marketplace Fraud Detection in Distributed E-Commerce Ecosystems"}, {"directness": "primary", "doi": "10.48550/arxiv.2602.09341", "risk_of_bias": "not appraised in public sidecar", "study": "Auditing Multi-Agent LLM Reasoning Trees Outperforms Majority Vote and LLM-as-Judge"}, {"directness": "primary", "doi": "10.1088/2631-8695/ae3b9e", "risk_of_bias": "not appraised in public sidecar", "study": "Digital twin-enhanced multi-agent reinforcement learning for distributed control of collaborative robotic arms in angle steel tower dismantling"}, {"directness": "primary", "doi": "10.1109/iconic67661.2026.11517785", "risk_of_bias": "not appraised in public sidecar", "study": "Multi-Agent Reinforcement Learning for Dynamic and Resilient Healthcare Supply Chain Optimization"}, {"directness": "primary", "doi": "10.4108/eetiot.10944", "risk_of_bias": "not appraised in public sidecar", "study": "Risk-Aware Reinforcement Learning for Cooperative Autonomous Vehicle Coordination with Adaptive Risk Sensitivity and Multi-Agent Optimization"}, {"directness": "primary", "doi": "10.1016/j.jss.2026.112792", "risk_of_bias": "not appraised in public sidecar", "study": "Many Hands Make Light Work: An LLM-based Multi-Agent System for Detecting Malicious PyPI Packages"}, {"directness": "primary", "doi": "10.71465/ajainn3659", "risk_of_bias": "not appraised in public sidecar", "study": "Self-Healing Memory Architectures for Large Language Model-Based Multi-Agent Collaboration"}, {"directness": "primary", "doi": "10.21203/rs.3.rs-9262455/v1", "risk_of_bias": "not appraised in public sidecar", "study": "Neurosymbolic Multi-Agent Large Language Model System Versus Specialist Physicians in COPD and Asthma Management: A Comparative Performance Evaluation Using Guideline-Based Clinical Vignettes"}, {"directness": "primary", "doi": "10.48550/arxiv.2602.16435", "risk_of_bias": "not appraised in public sidecar", "study": "Causally-Guided Automated Feature Engineering with Multi-Agent Reinforcement Learning"}, {"directness": "primary", "doi": "10.48550/arxiv.2602.19843", "risk_of_bias": "not appraised in public sidecar", "study": "MAS-FIRE: Fault Injection and Reliability Evaluation for LLM-Based Multi-Agent Systems"}, {"directness": "primary", "doi": "10.48550/arxiv.2602.08335", "risk_of_bias": "not appraised in public sidecar", "study": "Who Deserves the Reward? SHARP: Shapley Credit-based Optimization for Multi-Agent System"}, {"directness": "primary", "doi": "10.1016/j.watres.2026.126163", "risk_of_bias": "not appraised in public sidecar", "study": "Water-MAS: A multi-agent LLM framework with instruction-data decoupling for smart water management."}, {"directness": "primary", "doi": "10.18653/v1/2026.healing-1.1", "risk_of_bias": "not appraised in public sidecar", "study": "Do Mixed-Vendor Multi-Agent {LLM}s Improve Clinical Diagnosis?"}, {"directness": "primary", "doi": "10.1109/tase.2026.3672621", "risk_of_bias": "not appraised in public sidecar", "study": "Humanoid Five-Digit Robotic Grasping via Multi-Agent Reinforcement Learning With Potential-Guided Optimization and Weight Scheduling"}, {"directness": "primary", "doi": "10.14429/dsj.21693", "risk_of_bias": "not appraised in public sidecar", "study": "Enhancing Military Situational Awareness Through Multimodal Multi-Agent AI Systems: A Comparative Study with Single-Agent Approach"}, {"directness": "primary", "doi": "10.3390/drones10010054", "risk_of_bias": "not appraised in public sidecar", "study": "Hierarchical Role-Based Multi-Agent Reinforcement Learning for UHF Radiation Source Localization with Heterogeneous UAV Swarms"}, {"directness": "primary", "doi": "10.66238/fsrma54", "risk_of_bias": "not appraised in public sidecar", "study": "LLM-Driven Multi-Agent Decision Systems with Reinforcement Learning-Based Adaptive Communication"}, {"directness": "primary", "doi": "10.71465/ajml3665", "risk_of_bias": "not appraised in public sidecar", "study": "Adaptive Policy Alignment for Multi-Agent Large Language Models via Reinforcement Learning in Dynamic Task Environments"}, {"directness": "primary", "doi": "10.3390/electronics15091823", "risk_of_bias": "not appraised in public sidecar", "study": "Predictive Mamba-Enhanced Multi-Agent Reinforcement Learning Control for Virtual Coupling of High-Speed Trains"}, {"directness": "primary", "doi": "10.1609/aaai.v40i48.42120", "risk_of_bias": "not appraised in public sidecar", "study": "SAGE: A Compositional Multi-Agent LLM Framework with Pedagogical Reasoning for Structured Collaborative Problem Solving"}, {"directness": "primary", "doi": "10.3390/robotics15010028", "risk_of_bias": "not appraised in public sidecar", "study": "Relaxed Monotonic QMIX (R-QMIX): A Regularized Value Factorization Approach to Decentralized Multi-Agent Reinforcement Learning"}, {"directness": "primary", "doi": "10.1038/s41598-025-14032-w", "risk_of_bias": "not appraised in public sidecar", "study": "A graph attention network-based multi-agent reinforcement learning framework for robust detection of smart contract vulnerabilities."}, {"directness": "primary", "doi": "10.1109/tccn.2025.3528892", "risk_of_bias": "not appraised in public sidecar", "study": "AutoHMA-LLM: Efficient Task Coordination and Execution in Heterogeneous Multi-Agent Systems Using Hybrid Large Language Models"}, {"directness": "primary", "doi": "10.1080/20964471.2025.2483541", "risk_of_bias": "not appraised in public sidecar", "study": "Enhancing geodatabases operability: advanced human-computer interaction through RAG and Multi-Agent Systems"}, {"directness": "primary", "doi": "10.1109/tvt.2024.3520637", "risk_of_bias": "not appraised in public sidecar", "study": "Cooperative Multi-Agent Deep Reinforcement Learning for Dynamic Task Execution and Resource Allocation in Vehicular Edge Computing"}, {"directness": "primary", "doi": "10.1109/cibcb66090.2025.11177136", "risk_of_bias": "not appraised in public sidecar", "study": "Enhancing Clinical Decision-Making: Integrating Multi-Agent Systems with Ethical AI Governance"}, {"directness": "primary", "doi": "10.1109/tiv.2024.3471909", "risk_of_bias": "not appraised in public sidecar", "study": "Multi-Agent Reinforcement Learning for Distributed Cooperative Vehicular Positioning"}, {"directness": "primary", "doi": "10.48550/arxiv.2506.06574", "risk_of_bias": "not appraised in public sidecar", "study": "The Optimization Paradox in Clinical AI Multi-Agent Systems"}, {"directness": "primary", "doi": "10.48550/arxiv.2506.13755", "risk_of_bias": "not appraised in public sidecar", "study": "MARCO: Hardware-Aware Neural Architecture Search for Edge Devices with Multi-Agent Reinforcement Learning and Conformal Prediction Filtering"}, {"directness": "primary", "doi": "10.1109/icwite64848.2025.11306978", "risk_of_bias": "not appraised in public sidecar", "study": "A Multi-Agent AI Framework for Agile Workflow Automation, Issue Resolution, and Developer Performance Evaluation"}, {"directness": "primary", "doi": "10.1109/vtc2025-fall65116.2025.11310364", "risk_of_bias": "not appraised in public sidecar", "study": "Multi-Agent Reinforcement Learning assisted Trust-aware Cooperative Spectrum Sensing for Cognitive Radio Networks"}, {"directness": "primary", "doi": "10.1109/iceca66444.2025.11382981", "risk_of_bias": "not appraised in public sidecar", "study": "Multi-Agent Systems for Collaborative and Proactive Fraud Prevention in Distributed AI-Driven Financial Platforms"}, {"directness": "primary", "doi": "10.1145/3795154.3795432", "risk_of_bias": "not appraised in public sidecar", "study": "RAG-Enhanced LLM and RL Scheduling: Optimizing a Multi-Agent Framework for Abnormal Futures Price Monitoring"}, {"directness": "primary", "doi": "10.12732/ijam.v38i11s.1856", "risk_of_bias": "not appraised in public sidecar", "study": "DECENTRALIZED MULTI-AGENT REINFORCEMENT LEARNING ARCHITECTURE FOR RAILWAY TRACK DAMAGE DETECTION IN TRAIN-BASED MONITORING SYSTEMS"}, {"directness": "primary", "doi": "10.1109/tvt.2025.3574081", "risk_of_bias": "not appraised in public sidecar", "study": "DeepBeam: A Multi-Agent Deep Reinforcement Learning Framework for Predictive mmWave Beam Management in Dynamic V2X Networks"}, {"directness": "primary", "doi": "10.1200/jco.2025.43.16_suppl.1554", "risk_of_bias": "not appraised in public sidecar", "study": "Transforming oncology clinical trial matching through multi-agent AI and an oncology-specific knowledge graph: A prospective evaluation in 3,800 patients."}, {"directness": "primary", "doi": "10.1109/icvadv63329.2025.10961787", "risk_of_bias": "not appraised in public sidecar", "study": "Optimizing Smart City Infrastructure Using 5G Edge AI with Adaptive Multi-Agent Reinforcement Learning"}, {"directness": "primary", "doi": "10.1109/aiot66900.2025.00149", "risk_of_bias": "not appraised in public sidecar", "study": "A Large Language Model-based Multi-Agent Framework for Automated Privacy Policy Analysis"}, {"directness": "primary", "doi": "10.48550/arxiv.2509.05446", "risk_of_bias": "not appraised in public sidecar", "study": "Dynamic Sensitivity Filter Pruning using Multi-Agent Reinforcement Learning For DCNN's"}, {"directness": "primary", "doi": "10.5220/0014201400004932", "risk_of_bias": "not appraised in public sidecar", "study": "A Real-Time Cognitive Reasoning Architecture for Continual Learning and Decision Making in Autonomous Multi-Agent Systems"}]}
metadata
{
"researka_object_type": "publication_sidecar",
"researka_publication_id": "0df073d3-1e40-4543-8a44-43022c2dc543",
"researka_submission_id": "a7e0a071-cf23-418f-885c-adfef8bba09b",
"sidecar_name": "risk_of_bias.json",
"sidecar_url": "https://api.researka.org/publications/0df073d3-1e40-4543-8a44-43022c2dc543/sidecars/risk_of_bias.json"
}