Long-running AI agents create a control problem: each action they take changes the state, which in turn affects the trajectory of future actions. If the agent is not fully aligned, then guaranteeing safety requires approving consequential actions before allow...
VQV Signal
RESEARCH
SOURCE-BACKED
TECHNICAL
Delegating Authorization to Misaligned Agents: Coalitional Alignment and Safe Control
Long-running AI agents create a control problem: each action they take changes the state, which in turn affects the trajectory of future actions. If the agent is not fully aligned, then guaranteeing safety requires approving consequential actions before allow...
Long-running AI agents create a control problem: each action they take changes the state, which in turn affects the trajectory of future actions. If the agent is not fully aligned, then guaranteeing safety requires approving consequential actions before allowing them to be executed. But requiring human approval at...
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Signal Strength 95%
Technical label SOURCE-BACKED
Public Interest 18
Category RESEARCH
Reader Depth TECHNICAL
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
Public Interest components
Recognizable Entity Score 0
Practical Impact Score 0
Novelty Interest Score 48
Consequence Score 18
Curiosity Score 16
Shareability Score 37
Topics
VQV surfaced this signal because it is recent, relevant to AI Agents, connected to arXiv.
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