Adversarial compromise of tool outputs misleads agentic AI via breadth and depth attacks, revealing that epistemic and navigational robustness are distinct and often trade off against each other.
Findings of the Association for Computational Linguistics: EACL 2024 , pages=
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A neuro-symbolic system is proposed that uses formal logic to constrain LLM outputs so legal inferences stay faithful to source text.
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How Adversarial Environments Mislead Agentic AI?
Adversarial compromise of tool outputs misleads agentic AI via breadth and depth attacks, revealing that epistemic and navigational robustness are distinct and often trade off against each other.
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Bridging Legal Interpretation and Formal Logic: Faithfulness, Assumption, and the Future of AI Legal Reasoning
A neuro-symbolic system is proposed that uses formal logic to constrain LLM outputs so legal inferences stay faithful to source text.