Empirical evaluation shows that GPT-4's standardized exam benchmark capabilities originate primarily from post-training alignment rather than pre-training.
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When evaluated on multiple-choice standardized exam sections, what average score is achieved by the base pre-trained GPT-4 model?
Empirical evaluation shows that GPT-4's standardized exam benchmark capabilities originate primarily from post-training alignment rather than pre-training.
Based on empirical evaluations on standardized exam benchmarks, what effect does reinforcement learning from human feedback (RLHF) have on the fundamental capabilities acquired by GPT-4 during pre-training?
In empirical evaluations of GPT-4, which finding provides evidence that standardized exam performance originates primarily in pre-training rather than post-training alignment?
On what specific format of standardized exam sections were the base pre-trained and post-RLHF GPT-4 models evaluated to compare their benchmark capabilities?
Evaluation Asymmetry in Base and RLHF Free-Response Comparison