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arXiv AI By Zihou Ren, Byungchul Tak, Long Wang

REALM: Identifying Minimal Task Assets for LLM Agents

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REALM (Required Execution Assets Linked to a Mission) is a method for identifying and managing the minimal set of assets that a large language model (LLM) agent needs to complete a task, even when those assets are discovered only during execution. It represents required assets as nodes in a dependency graph, separates asset discovery from authorization, and uses a REALM Builder to maintain grants and a Partial API Manager to expose resource‑bound APIs within a task container. In experiments on 60 clean tasks and 560 injected cases, REALM achieved 40.0% task completion and reduced attack success rate from 16.6% to 0.2% when using qwen3.5‑flash as the base model.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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