AgentForesight: a 7B online auditor that catches multi-agent failures mid-run
jiqizhixin · x · 2026-10-17
Rutgers, UT Austin, and Purdue present AgentForesight (NeurIPS 2026), shifting multi-agent failure analysis from post-hoc attribution to online auditing.
- Motivating scenario: a search agent silently sets a $200 headphone budget to $300; every downstream step executes flawlessly, yet the whole pipeline has drifted — no single agent made an obvious error, they all inherited a bad premise.
- Approach: after every step, an external 7B auditor model reads the execution trajectory so far and decides whether to continue or raise an alert, buying an intervention window before the task is ruined.
- Contrast with post-hoc attribution: retrospective analysis only localizes the decisive error after failure is locked in; online auditing flags it the moment it's committed (the paper's figure shows the auditor catching the wrong price filter at step 3 and the corrected run producing the right report).
- Validated on benchmarks including AFTbench (details truncated in source; see paper).
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