@ms_aifrontiers: A lot of agent benchmarks assume the world changes only when the agent acts. Many real tasks are different: tickets go …
Summary
Discusses a limitation of current agent benchmarks that assume the world changes only when the agent acts, whereas many real-world tasks require the agent to wait for external events before acting.
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Cached at: 06/09/26, 01:31 AM
How patient is your agent?
We’re releasing SentinelBench: web monitoring tasks across 10 synthetic apps, designed to test whether agents can watch, wait, and act when the world changes.
Turns out “how you wait” matters. A lot. SentinelBench, a Benchmark for Long-Running Monitoring Agents - Microsoft Research
A lot of agent benchmarks assume the world changes only when the agent acts. Many real tasks are different: tickets go on sale, messages arrive, prices move, posts get likes. Rather than continuing to click or search, agents should watch patiently, then act at the right moment
SentinelBench tests agents in time-evolving web environments where success requires waiting. How you wait matters: on 40-minute tasks, agents that sleep and poll in a loop can cost 9.7× more, while completing fewer tasks than agents with a specialized change-detection tool.
Blog: https://microsoft.com/en-us/research/articles/sentinelbench-a-benchmark-for-long-running-monitoring-agents/…
Code: https://github.com/microsoft/sentinel_environments/…
Authors: @matheusmaldaner @adamfourney @ASwearngin77874 @HsseinMzannar @bansalg_ @MayaMurad0 @HosnRafa @SaleemaAmershi
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