Hybrid Reasoning Agents: LLM agents that think in latent space, act through text
Proposes LLM agents that reason in latent space and act through text, with code and models linked.
3 items · 3 sources · 3 days
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A new arXiv paper moves latent reasoning into continuous space for unified multimodal models, targeting weak language-based chain-of-thought in image tasks.
An Oct 18 paper proposed hybrid agents that reason in latent space but act through text. A paper on Oct 27 then applied latent reasoning to multi-agent systems by storing reusable skills in compact external memory.
Arc
Proposes LLM agents that reason in latent space and act through text, with code and models linked.
Adds a compact external skill memory for latent multi-agent reasoning.
Brings continuous-space latent reasoning to unified multimodal models.
Proposes LLM agents that reason in latent space and act through text, with code and models linked.
Adds a compact external skill memory for latent multi-agent reasoning.
Brings continuous-space latent reasoning to unified multimodal models.
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