Conleash uses a risk lattice, policy engine, and refinement loop to deliver scoped, consent-driven authorization for MCP tool calls, reaching 98.2% accuracy and 99.4% escalation catch rate on 984 traces with 8.2 ms overhead and higher user preference in a 16-person study.
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Position paper proposing compliance-by-construction for neuro-symbolic agents in regulated process automation and calling for research on associated challenges.
citing papers explorer
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Options, Not Clicks: Lattice Refinement for Consent-Driven MCP Authorization
Conleash uses a risk lattice, policy engine, and refinement loop to deliver scoped, consent-driven authorization for MCP tool calls, reaching 98.2% accuracy and 99.4% escalation catch rate on 984 traces with 8.2 ms overhead and higher user preference in a 16-person study.
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Neuro-Symbolic Agents for Regulated Process Automation: Challenges and Research Agenda
Position paper proposing compliance-by-construction for neuro-symbolic agents in regulated process automation and calling for research on associated challenges.