SpecMind: Enabling Spectrum Intelligence via Multi-Agent Hybrid Retrieval-Augmented Generation

arXiv:2609.00427 · cs.AI · Submitted 2026-08-31 · Read on arXiv

cs.AI

Submitted: 2026-08-31

Updated: 2026-08-31

Comments: Accepted to IEEE GLOBECOM 2026. Project website: https://specmindrag.github.io

Project page: https://specmindrag.github.io

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• RAG — 38× in this paper · explained in 3 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Verification — 3× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Graph Construction — 2× in this paper · explained in 3 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Hallucination — 2× in this paper · explained in 3 episodes
• Multi-hop Reasoning — 2× in this paper · explained in 3 episodes
• Prompt Engineering — 2× in this paper · explained in 4 episodes
• Retrieval-Augmented Generation (RAG) — 2× in this paper · explained in 16 episodes
• Task Decomposition — 2× in this paper · explained in 2 episodes
• Abstention — 1× in this paper · explained in 1 episode
• Adaptive Mechanism — 1× in this paper · explained in 1 episode
• Adaptive Planning — 1× in this paper · explained in 1 episode
• Agent Interactions — 1× in this paper · explained in 1 episode
• Agentic AI — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Evaluation Dimensions — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Multi-Agent Retrieval-Augmented Generation — 1× in this paper

Sources

• Language Models are Few-Shot Learners
• Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG
• Retrieval-Augmented Generation for Large Language Models: A Survey
• REALM: Retrieval-Augmented Language Model Pre-Training
• Retrieval-Augmented Generation for Reliable Interpretation of Radio Regulations
• From Local to Global: A Graph RAG Approach to Query-Focused Summarization
• ReAct: Synergizing Reasoning and Acting in Language Models

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• Agents' Last Exam
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems