Anchor: Mitigating Artifact Drift in Agent Benchmark Generation
AI agents are beginning to complete valuable, long-horizon business operations tasks, but training and evaluation environments for enterprise work still struggle to balance realism, verifiability, and scale. Environment and task creation frequently suffers from a failure mode we call artifact drift: when instructions, environments, oracles, and verifiers are created by loosely coupled processes, they frequently disagree on what a task requires, producing environments that are unsolvable, reward-hackable, or inconsistent. We introduce Anchor, a task-generation pipeline that formalizes domain experts' specifications of business workflows into constraint optimization programs. From a single ...
| Authors | Maksim Ivanov, Abhijay Rana |
|---|---|
| Primary category | cs.AI |
| Published | 25 May 2026 |
| Last updated at source | 25 May 2026 |
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