This paper investigates distributed latent-space alignment in multi-user semantic MIMO interference networks with cognitive radio constraints.

The paper proposes Multi-Order Communication (MOC) to overcome the limitations of standard first-order message passing in LLM-based multi-agent systems, significantly improving performance by capturin…

This paper proposes a spatial semantic communication (SSC) system using fluid antenna-index modulation (FA-IM) technology, which synergizes residual quantization (RQ) and IM for efficient semantic tra…

This survey examines explainable AI (XAI) in wireless PHY layers, formalizing goals, taxonomy, and applications.

The paper proposes a communication-centric 6G-LLM architecture for tactical autonomous defense vehicles, demonstrating significant improvements in coordination and communication efficiency over conven…

The paper proposes iCoTASC, a framework for real-time, channel-adaptive semantic resource allocation in collaborative multi-device systems using importance-aware embedding selection, data-driven utili…

This paper proposes a semantic-aware multiple access scheme for efficient transmission of high-volume visual data among nearby vehicles in uplink-dominant 6G systems, reducing redundant transmissions…

The paper proposes DySCo, a dynamic trust-aware sparse consensus mechanism, to efficiently manage communication in multi-agent LLM systems by selectively connecting agents based on real-time value, th…

The paper introduces RadioMaster, a novel multi-agent system that successfully translates high-level user intents into physically viable, real-world radio signals, significantly outperforming existing…

This paper proposes a new communication framework, TokCom, for 6G wireless networks where tokens from large language models become the fundamental entities for information exchange.

This paper systematically analyzes the complex design space of hybrid multi-agent systems combining on-device and cloud AI models, finding that the optimal architecture is highly task-dependent and th…

This paper proposes a semantic-aware task clustering method for Cooperative multi-task semantic communication (CMT-SemCom) to ensure constructive cooperation and mitigate destructive cooperation and n…

The paper introduces a metric, the compositional residual eps*, to quantify how multi-component LLM agents violate basic probability axioms when combining local, coherent claims into a global predicti…

The paper introduces the Asymmetric Collaborative Framework (ACF), a novel method that enables robust covert communication between autonomous agents despite inherent cognitive asymmetry caused by dyna…

This paper demonstrates that using a communication algorithm (CommFormer) with heterogeneous agents significantly improves the speed and performance of multi-agent reinforcement learning for autonomou…

This paper proposes CoSMIC, a framework for semantic integrated sensing and communication (ISAC) that embeds semantic information into waveforms while maintaining covertness and sensing fidelity.

This paper presents a tutorial-and-survey on integrating agentic AI into Next-Generation Networks (NGNs), addressing the gap in protocol integration, evaluation, and standardization alignment.

This paper provides an information bottleneck perspective on the differences between single-agent and multi-agent systems, showing that the advantage of MAS arises under bounded relays and introducing…