2023-03-18-OpenAI-GPT-4_技术报告（英文版）_98页_947kb

GPT-4 Technical Report Summary

The GPT-4 technical report details a large multimodal language model capable of understanding image and text inputs and producing text outputs. It demonstrates human-level performance on professional and academic benchmarks, including passing exams at top percentiles previously considered near human-level capability.

Key capabilities highlighted include:

• Strong performance across standardized tests like the Uniform Bar Exam (90th percentile), LSAT, and professional exams
• Superior performance on language benchmarks across 57 subjects and in multiple low-resource languages
• Visual input processing that generalizes to various domains
• Chain-of-thought prompting that enhances reasoning capabilities

Critical safety considerations include:

• Hallucinations remain a limitation despite system improvements
• Content policy adherence is improved by 82% compared to prior models
• Intelligent refusal mechanisms help moderate harmful content generation

The report highlights balance through predictable scaling which enables performance modeling across diverse scales, technical improvements like embedding models for retrieval, and iterative adversarial testing. The authors note GPT-4 represents a substantial step forward while still having important limitations requiring context-specific deployment controls.