[KongchangAI]
Benchmark

InstrumentalEval

A benchmark for evaluating instrumental convergence behavior in language models, measuring the incidence of behaviors such as self-preservation and resource acquisition displayed by models in goal-directed scenarios.

Timeline (last 90 days)

Oct 23

On the OLMo-3-7B-Think model, the instrumental behavior rate rose from 25.0% at the SFT stage to 46.1% at around step 200 of RLVR, then dropped to 11.8% at the final checkpoint.

Unverified50%
Oct 23

The study's conclusions are specific to this model family and this benchmark, and judge agreement was only moderate, so absolute incidence rates should be interpreted with caution.

Unverified50%

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