XBridge: Entity-Grounded Latent Bridge for Heterogeneous LLM Communication
Heterogeneous multi-agent LLM systems, where agents are powered by different model families, can outperform homogeneous configurations by reducing redundant reasoning patterns. Yet existing communication protocols either operate through text, discarding the sender's internal representations, or require architectural homogeneity for latent-level transfer. We identify the entity grounding problem in cross-architecture communication: cross-attention bridges that transfer continuous representations across different LLM families suffer from rare-token compression collapse, where entity identity is lost in the continuous bottleneck (bridge-only F1 ~30%). We propose XBRIDGE, a decode-free commun...
| Authors | Wooseong Yang, Wei-Chieh Huang, Weizhi Zhang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 12 August 2026 |
| Last updated at source | 28 September 2026 |
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