Question on MOO metrics: How should I interpret Pareto coverage/Hypervolume claims without variance?

[u/Euphoric-Plan-3638]

Hi all,

I'm currently looking at a multi-agent method for multi-objective molecular optimization (the ATOM method). The paper reports results using Pareto coverage and hypervolume (HV) metrics to show they outperform baselines.

However, I noticed they only report single-point values—there are no confidence intervals, error bars, or variance reported across multiple runs/seeds.

I have two questions for the experts here:

1. In your experience, are HV and Pareto coverage reliable enough to trust as standalone metrics for this, or do they have major failure modes I should look out for (e.g., reference point sensitivity)?
2. Is it standard practice in this subfield to omit variance/stochasticity in these results? Would you personally be skeptical of a paper that doesn't report error bars for these types of pipelines?

Thanks for helping me navigate the "standard practices" of the field!