UniCom: Unifying Explicit and Implicit Communication for LLM Agents

Effective collaboration among large language model (LLM) agents hinges on the fidelity of their communication protocols, which currently diverge into explicit communication in textual space and implicit communication in latent space. This dichotomy inherently imposes a fundamental tension between interpretability and expressiveness, wherein textual communication sacrifices high-dimensional reasoning nuances for human readability, whereas latent communication preserves rich semantics at the cost of rendering the underlying reasoning logic opaque and unauditable. To reconcile this tension, we present UniCom, a unified agentic communication protocol that integrates the complementary strengths of textual and latent modalities within a single coherent paradigm. At its core, UniCom features a lightweight dual-stream adapter, in which a shared encoder first maps the hidden states of heterogeneous senders into a unified communication space, and two parallel decoders then disentangle the encoded representations into discrete textual tokens and continuous latent semantics. In this way, UniCom naturally embodies the communication duality, delivering an interpretable preview for human inspection alongside an expressive payload for receiver inference. Experiments on five standard benchmarks under two heterogeneous agent scales show that UniCom consistently outperforms both text-only and latent-only communication baselines, revealing its potential to unify agent-to-human and agent-to-agent communication.