%0 Journal Article %1 OpenAI_GPT4_2023 %A OpenAI, %D 2023 %J ArXiv %K gpt-4 openai transformer multimodal bar_exam alignment_process paper_demo posted_with_chatgpt %T GPT-4 Technical Report %U https://arxiv.org/abs/2303.08774 %V abs/2303.08774

@article{OpenAI_GPT4_2023, added-at = {2023-10-23T16:08:31.000+0200}, author = {OpenAI}, biburl = {https://www.bibsonomy.org/bibtex/2b87062f1a9478148d2e5dd0006c9c455/tomvoelker}, description = {Technical report detailing the development of GPT-4, a multimodal model capable of handling both image and text inputs. The model achieved human-level performance on various benchmarks, including scoring in the top 10% on a simulated bar exam. The study highlights the importance of the post-training alignment process for enhancing the model's accuracy and behavior.}, interhash = {241e35649065841f159e6105eb87b1d3}, intrahash = {b87062f1a9478148d2e5dd0006c9c455}, journal = {ArXiv}, keywords = {gpt-4 openai transformer multimodal bar_exam alignment_process paper_demo posted_with_chatgpt}, timestamp = {2023-10-23T16:08:31.000+0200}, title = {GPT-4 Technical Report}, url = {https://arxiv.org/abs/2303.08774}, volume = {abs/2303.08774}, year = 2023 }