Procedural Graphs: Self-Evolving Execution Structures for LLM Agents
- View PDF HTML (experimental) Abstract:Large language models are increasingly deployed as agents that plan over long horizons and act through external tools.
- Most agents select actions through unconstrained generation over an accumulating history, leaving implicit the procedural knowledge of what to do, in what order, and under which conditions.
- As trajectories lengthen, agents can lose track of their objectives, invoke tools out of order, and repeat unproductive actions.
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- View PDF HTML (experimental) Abstract:Large language models are increasingly deployed as agents that plan over long horizons and act through external tools.
- Most agents select actions through unconstrained generation over an accumulating history, leaving implicit the procedural knowledge of what to do, in what order, and under which conditions.
- As trajectories lengthen, agents can lose track of their objectives, invoke tools out of order, and repeat unproductive actions.
Sources: Arxiv