{"url":"/dataset/machine-mindset-mbti-dataset","name":"Machine_Mindset_MBTI_dataset","full_name":null,"description_markdown":"## Dataset introduction\r\n\r\nThere are four dimension in MBTI. And there are two opposite attributes within each dimension.\r\n\r\nTo be specific:\r\n\r\n+ Energe: Extraversion (E) - Introversion (I)\r\n\r\n+ Information: Sensing (S) - Intuition (N)\r\n\r\n+ Decision: Thinking (T) - Feeling (F)\r\n\r\n+ Execution: Judging (J) - Perceiving (P)\r\n\r\nBased on the above, you can infer the content of the json file from its name.\r\n\r\nThe datasets follow the Alpaca format, consisting of instruction, input and output.\r\n\r\n## How to use these datasets for behavior supervised fine-tuning (SFT)\r\n\r\nFor example, if you want to make an LLM behave like an ***ISFJ***, you need to select ***the four corresponding files*** (en_energe_introversion.json, en_information_sensing.json, en_decision_feeling.json, en_execution_judging.json). \r\n\r\nAnd use the four for SFT.\r\n\r\n## How to use these datasets for direct preference optimization (DPO)\r\n\r\nFor example, if you want to make an LLM be ***more feeling (F) than thinking (T)*** by DPO, you need to select ***the two corresponding files*** (en_decision_feeling.json, en_decision_thinking.json). \r\n\r\nAnd then compile the two into the correct format for DPO. For the correct format, please refer to [this](https://github.com/PKU-YuanGroup/Machine-Mindset/blob/main/datasets/dpo/README.md).","description_withheld":null,"homepage":"https://huggingface.co/datasets/FarReelAILab/Machine_Mindset_MBTI_dataset","introduced_date":"2023-12-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/machine-mindset-an-mbti-exploration-of-large","title":"Machine Mindset: An MBTI Exploration of Large Language Models","first_author":"Jiaxi Cui","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Text Generation","url":"/task/text-generation","datasets_with_task":"/datasets/task/text-generation"},{"name":"Core Psychological Reasoning","url":"/task/core-psychological-reasoning","datasets_with_task":"/datasets/task/core-psychological-reasoning"}],"languages":[{"name":"English","url":"/datasets/language/english"},{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":["Machine_Mindset_MBTI_dataset"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}