Bad Genius: Counterfactual-Guided Harness Evolution Beyond Task-Specific Shortcuts
Reliable agent evaluation is complicated by automatic harness optimization, which repeatedly uses a released benchmark $B_{\mathrm{rel}}$ to guide a Proposer that edits prompts, memory, retrieval, tools, and control code around a fixed foundation model. Task holdout is commonly used to guard against harness overfitting. It varies semantic tasks but leaves the benchmark protocol fixed, so a bad genius Proposer can produce a cheating harness whose improvement over the initial harness on $B_{\mathrm{rel}}$ depends on a benchmark-wide shortcut. We introduce Counterfactual Harness Search and Evolution (CHASE), which casts harness evolution as constraint generation over valid counterfactual ben...
| Authors | Guojun Zhu, Xunheng Huang, Peng Yin et al. |
|---|---|
| Primary category | cs.AI |
| Published | 16 September 2026 |
| Last updated at source | 24 September 2026 |
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