The Verifier Tax: Horizon-Dependent Safety–Success Tradeoffs in Tool-Using LLM Agents [R]
Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.
We recently presented a paper at ACM CAIS 2026 on safety evaluation for tool-using LLM agents.
The core issue is that task completion alone can be misleading: an agent may complete a task while violating a safety or policy constraint. We separate outcomes into safe success, unsafe success, and failure, and study how verification changes this tradeoff.
We evaluate this using τ-bench / Tau-bench tool-use scenarios and propose a two-tier verification architecture: deterministic policy/tool checks first, followed by an LLM-based verifier for more contextual safety cases.
The main finding is that verification can reduce unsafe success, but it can also reduce task completion as the task horizon increases. This creates what we call the Verifier Tax: a horizon-dependent safety–success tradeoff in tool-using agents.
Paper: https://dl.acm.org/doi/full/10.1145/3786335.3813160
Curious how others think agent evaluations should report unsafe success. Should unsafe completion be counted as success, failure, or a separate category?
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