Introduces the MMLU benchmark of 57 tasks and shows that current models, including GPT-3, achieve low accuracy far below expert level across academic and professional domains.
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The Geometric Reciprocity Theorem proves that DIBR disocclusion masks for stereo synthesis equal the pixels lost during reverse warping, enabling self-supervised stereo inpainting training from monocular images alone.
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Measuring Massive Multitask Language Understanding
Introduces the MMLU benchmark of 57 tasks and shows that current models, including GPT-3, achieve low accuracy far below expert level across academic and professional domains.
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Geometric Reciprocity: Unlocking Self-Supervision for Stereoscopic Video Generation
The Geometric Reciprocity Theorem proves that DIBR disocclusion masks for stereo synthesis equal the pixels lost during reverse warping, enabling self-supervised stereo inpainting training from monocular images alone.