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+personality+traits+into+large+language+models+(LLMs)%252C+addressing+the+challenges+of+personality+consistency+in+personalized+AI.+Our+method%252C+Machine+Mindset%252C+involves+a+two-phase+fine-tuning+and+Direct+Preference+Optimization+(DPO)+to+embed+MBTI+traits+into+LLMs.+This+approach+ensures+that+models+internalize+these+traits%252C+offering+a+stable+and+consistent+personality+profile.+We+demonstrate+the+effectiveness+of+our+models+across+various+domains%252C+showing+alignment+between+model+performance+and+their+respective+MBTI+traits.+The+paper+highlights+significant+contributions+in+the+development+of+personality+datasets+and+a+new+training+methodology+for+personality+integration+in+LLMs%252C+enhancing+the+potential+for+personalized+AI+applications.+We+also+open-sourced+our+model+and+part+of+the+data+at+url%7bhttps%3a%252F%252Fgithub.com%252FPKU-YuanGroup%252FMachine-Mindset%7d.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.c4d20f5227466f0b4624d44ec1e61137%3frik%3dvC%252fqEvcc6S9D0g%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Machine+Learning+Mindset&FORM=IRPRST&ck=939CBD748DB1E3CD55CB9AD560161AD7&selectedIndex=31&itb=0)
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