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Seonghyeon Cho

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#artificial intelligence Preprint Oct 2026

POLAR: Ontology-Guided Risk Prevention for Tool-Calling LLM Agents

LLM tool-use agents operate in dynamic environments where many actions carry operational risk. However, most safety mechanisms react only after errors manifest. Existing pre-emptive approaches either fine-tune the agent on chain-of-thought deliberation or compile natural-language guardrails into runtime checks, but the...

Yun-Ju Kang, Seonghyeon Cho, Irene Li et al. · 0 citations

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