arXiv Artificial Intelligence

HINTBench: Horizon-agent Intrinsic Non-attack Trajectory Benchmark

HINTBench: Horizon-agent Intrinsic Non-attack Trajectory Benchmark

Quick summary

arXiv:2604.13954v2 Announce Type: replace-cross Abstract: Existing agent-safety evaluation has focused mainly on externally induced risks. Yet agents may still enter unsafe trajectories under benign conditions. We study this complementary but underexplored setting through the lens of \emph{intrinsic} risk, where intrinsic failures remain latent, propagate across long-horizon execution, and eventually lead to high-consequence outcomes. To evaluate this setting, we introduce \emph{non-attack intrinsic risk auditing}, a guard-oriented safety evaluation task, and present \textbf{HINTBench}, a benc

Key takeaways

  • arXiv:2604.13954v2 Announce Type: replace-cross Abstract: Existing agent-safety evaluation has focused mainly on externally induced risks.
  • Yet agents may still enter unsafe trajectories under benign conditions.
  • We study this complementary but underexplored setting through the lens of \emph{intrinsic} risk, where intrinsic failures remain latent, propagate across long-horizon execution, and eventually lead to high-consequence outcomes.

Why it matters

“HINTBench: Horizon-agent Intrinsic Non-attack Trajectory Benchmark” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗