[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-293169-105":59,"doc-detail-293169-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","charactergpt-a-persona-reconstruction-framework-for-role-playing-agents-293169","CharacterGPT - A Persona Reconstruction Framework for Role-Playing Agents","","The introduction of the Assistants API strengthens the use of large language models in role-playing agents, yet persona consistency remains difficult because information extraction from documents can miss key elements such as backstory or interpersonal relationships. CharacterGPT addresses this by using Character Persona Training to incrementally reconstruct personas from chapter-wise novel summaries. Evaluation uses Big Five personality assessments and creative narrative tasks, showing improved persona coherence, controllability, and role-specific knowledge, with code and results provided.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/charactergpt-a-persona-reconstruction-framework-for-role-playing-agents-293169/293169/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/charactergpt-a-persona-reconstruction-framework-for-role-playing-agents-293169/293169.png","ImageObject",300,407,{"name":92,"@type":93},"8796093062539","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",14,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What problem does CharacterGPT target in role-playing agents?","Question",{"text":113,"@type":114},"CharacterGPT targets inconsistent persona coherence caused by document-based information extraction that often omits crucial traits like backstory, motivations, or relationships.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How does Character Persona Training (CPT) work in CharacterGPT?",{"text":118,"@type":114},"CPT extracts eight essential character traits from chapter-wise novel summaries and incrementally appends them to an evolving persona document in chronological order.",{"name":120,"@type":111,"acceptedAnswer":121},"How is CharacterGPT evaluated?",{"text":122,"@type":114},"Evaluation includes Big Five Inventory (BFI) personality tests for persona consistency and crowd-worker judgments on generated short narratives across multiple Likert-scale metrics.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},293169,1789660566,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":66,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":144,"preview_page_count":4},8796093062539,"CharacterGPT: A Persona Reconstruction Framework for Role-Playing  \nAgents  \nJeiyoon Park 1 , Chanjun Park2†, Heuiseok Lim2†  \n1 SOOP, 2 Korea University  \n[naruto@sooplive.com](naruto@sooplive.com)  \n{bcj1210, [limhseok}@korea.ac.kr](limhseok}@korea.ac.kr)  \nAbstract  \nThe recent introduction of the Assistants API highlights its potential for large language models (LLMs) in role-playing agents (RPA) . However, maintaining consistent character personas remains a significant challenge due to variability in information extraction, which frequently omits critical elements such as backstory or interpersonal relationships. To address this limitation, we introduce CharacterGPT, a framework designed to dynamically reconstruct character personas through Character Persona Training (CPT) . This approach incrementally updates personas by extracting traits from chapter-wise novel summaries, reflecting the progression of the narrative. Our framework is evaluated through Big Five personality evaluations and creative tasks, in which characters generate original narratives, demonstrating the efficacy of CharacterGPT in preserving persona consistency. The code and results are available at [https://github](https://github) . com/Jeiyoon/charactergpt  \n1 Introduction  \nThe rapid advancements in large language models (LLMs) have positioned them as the core module of various AI systems (OpenAI, 2023a,c; Anthropic, 2023 ; Google, 2024 ; DeepSeek-AI et al., 2024, 2025), enabling a wide range of applications. Building on this progress, the recent introduction of the Assistants API (OpenAI, 2023b), a tool designed for document-based information retrieval, demonstrates the potential of LLM in multiple domains, especially in role-playing agents (RPA) (Kim et al., 2019 ; Yu et al., 2023 ; Jiang et al., 2023 ; Park et al., 2023 ; Wang et al., 2023b ; Zhang et al., 2024 ; Kong et al., 2024 ; Wang et al., 2025) . However, RPAs that rely solely on documents as input often face problems of inconsistent information extraction,  \n† Corresponding Author  \nFigure 1: Comparison of response accuracy between persona-based GPT-4 assistants utilizing unstructured versus structured character traits as input. When provided with unstructured traits, the assistant demonstrates limited success in generating accurate responses. In contrast, the use of structured traits significantly improves the correctness of the assistant’s responses.  \nwhere key personality traits or background knowledge are omitted, leading to degraded persona coherence (Sadeq et al., 2024) . For example, as illustrated in Figure 1, when the Assistants API is provided with an unstructured Wiki document about the novel God’s Blessing on This Wonderful World!, it often fails to provide accurate responses, while  \n287  \nProceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies  \n(Industry Track), pages 287–303  \nApril 30, 2025 ©2025 Association for Computational Linguistics  \nstructured character traits produce more reliable, role-specific answers.  \nIn this paper, we propose a novel framework called CharacterGPT, which addresses this challenge through a structured persona reconstruction process. Drawing inspiration from cognitive memory models, we introduce Character Persona Training (CPT), a method that incrementally updates character personas by extracting traits from chapterwise summaries of novels. This approach mirrors how human memory consolidates information into schemas over time (van Kesteren and Meeter, 2020), enabling more consistent and contextually appropriate responses from RPAs.  \nCPT operates by identifying eight essential traits—personality, physical description, motivations, backstory, emotions, relationships, growth and change, and conflict—based on character analysis literature (Forster, 1927 ; Reams, 2015) . For each chapter of a novel, these traits are extracted from summaries and appended to","cbCaigLPXG7Sc7ll","https://ap.wps.com/l/cbCaigLPXG7Sc7ll","pdf",1259929,17,"English","# Introduction\n# Proposed Method","[{\"question\":\"What problem does CharacterGPT target in role-playing agents?\",\"answer\":\"CharacterGPT targets inconsistent persona coherence caused by document-based information extraction that often omits crucial traits like backstory, motivations, or relationships.\"},{\"question\":\"How does Character Persona Training (CPT) work in CharacterGPT?\",\"answer\":\"CPT extracts eight essential character traits from chapter-wise novel summaries and incrementally appends them to an evolving persona document in chronological order.\"},{\"question\":\"How is CharacterGPT evaluated?\",\"answer\":\"Evaluation includes Big Five Inventory (BFI) personality tests for persona consistency and crowd-worker judgments on generated short narratives across multiple Likert-scale metrics.\"}]","CharacterGPT - A Persona Reconstruction Framework for Role-Playing Agents | PDF",43]