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This work proposes NeRF-aided Camera Ray Regression (NaCR), a unified framework that seamlessly bridges NeRF and CRR at the ray level and introduces a two-stage training curriculum to ensure stable convergence within the highly non-convex image space.
Trajectory-scoped safety monitors for LLM agents are fundamentally flawed, leading to a 50% chance of missing threats that span multiple iterations.
Finance LLM agents can now block unauthorized actions mid-trajectory without sacrificing performance, thanks to a novel inline safety harness that adaptively routes verification between lightweight and advanced LLM judges.
