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AdaExploreBench finds LLM agents struggle to detect rule drift

huggingface.co by Rui Wang et al. Editor score 8/10

Across eight leading LLMs, GPT-6 Sol reaches 61.9% calibrated accuracy, and sufficient evidence or removing rule drift improves average performance by nearly 10%. The benchmark tests whether agents can explore hidden rules and recognize when those rules change.

What

AdaExploreBench tests whether LLM agents proactively explore unfamiliar environments and adapt when hidden rules change.

Method

Under implicit rule drift, agents must infer rules from evidence and notice degraded performance as a signal to re-explore.

Why it matters

Experiments found proactive evidence gathering and recognizing stale knowledge remain bottlenecks, even when agents can reason from informative evidence.

Read on huggingface.co → Code · 1 stars

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