Checkpointed Whistleblower Audits Surface Incidents Earlier and More Often Than End-of-Run Shared-State Monitoring

The general approach seems strong, and the argument for why it should be an improvement is clear, not overstated, and supported by evidence. The literature review was appropriate, albeit non-exhaustive; more work on that could better tie in to the history of the approaches, but this is not critical. The limitations section was appropriate and useful.

The reliance on "selected checkpoints" is weak; selected how? The comparison of audits over local history compared to external monitoring is somewhat disengenious; the proposer comparison would be to full audits, with a cost and accuracy comparison - but it is reasonable for this not to be done as part of the current sprint.

It would be valuable to understand what the impact of the audits would be; is the intent that these audits would be used to stop agents, or to flag risks quickly, or just as an alternative or supplement to other post-hoc analyses? Is the cost of the current method, of suspending the normal task while an audit occurs, reasonable in real-world environments? It would also be useful to try this on swarm-like behavior instead of the application in a multi-agent environments where each agent was operating as a single player.

I really liked this one. The technique of doing whistleblower audits at specific checkpoints during the agent run, and then mid-run assigning the whistleblower objective to trace and audit the behavior, is an intelligent framing rather than depending only on the Sentinel's final logs, and the paper correctly defines this as an information access problem. I also liked the honesty of the false positive findings in the paper, but I think the n=3 negative sample is a binding limitation - the false-positive and precision numbers can't bear much weight. Even 15–20 more trajectories may turn the FP rate from caveat to finding. Overall nice work, the code in git and per trajectory data made the results easy to trust.

Its a good and simple idea, alot of potential for practical use.

Temporarily switch an agent with access to its own local history into an audit role, instead of relying only on a separate monitor that sees shared state. The gap in detection is interesting and suggests local context really can contain useful evidence that an outside monitor misses. The current dataset is too small and imbalanced to judge reliability though, especially with only three negative examples. A larger balanced evaluation with complete histories, multiple audit models and live checkpoints would make the result much stronger.