[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-85616-en":3,"doc-seo-85616-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},85616,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","Bootstrap Theory of Representational Emergence","Representation learning is positioned as a key paradigm that shifts from handcrafted features toward embeddings, latent spaces, foundation models, world models, and digital twins. Yet research often optimizes representations after a framework is chosen, while underaddressing when new representational levels are required. The Bootstrap Theory of Representational Emergence (TBER) proposes that explanatory insufficiency—persistent gaps that prevent understanding organization or transformations—triggers representation transition via a recursive bootstrap dynamic and a five-stage model.","arXiv :2606 .07303v2 [ cs .LG] 13 Jul 2026  \nBootstrap Theory of Representational Emergence: Explanatory Insufficiency as a Driver of Representation Learning and World Models  \nJacques Raynal 1 , ∗ , Pierre Slangen2 , Elsa Raynal3 , Jacques Margerit4  \n1Laboratory of Bioengineering and Nanosciences (LBN), University of Montpellier, Montpellier, France  \n2EuroMov Digital Health in Motion, University of Montpellier, IMT Mines Alès, Alès, France  \n3 Certified Sophrologist and Dental Assistant, Sensorimotor Practice, Montpellier, France  \n4Emeritus Professor, University of Montpellier, Montpellier, France  \n∗ Corresponding author: [raynal.cab@gmail.com](raynal.cab@gmail.com)  \nAbstract  \nRepresentation learning has become a central paradigm in modern machine learning, enabling systems to move from handcrafted features to learned embeddings, latent spaces, foundation models, world models, and digital twins. However, most research focuses on how representations are optimized once a representational framework has been chosen. Less attention has been given to the question of when anew level of representation becomes necessary.  \nWe introduce the Bootstrap Theory of Representational Emergence (TBER), an initial conceptual theory and research program for describing how new representations arise when existing ones become explanatorily insufficient. In this view, representational innovation is not only the result of more data, larger models, or increased computational power. It is also driven by persistent explanatory gaps revealed when a current representation can still describe observations but can no longer make their organization or transformations intelligible.  \nTBER identifies explanatory insufficiency as a positive signal for representational transition. A representation becomes insufficient not because it is necessarily false, but because its explanatory domain has been exceeded. The proposed bootstrap dynamic follows a recursive sequence: observations reveal anomalies; anomalies expose explanatory insufficiencies; insufficiencies motivate new representations;  \nand these new representations generate further observations and possible new insufficiencies.  \nWe formalize this process through a five-stage model: stabilized observation, anomaly detection, recognition of explanatory insufficiency, representational emergence, and provisional stabilization.  \nThe framework concerns transitions between scientific or computational representations rather than transitions occurring within physical systems themselves. We discuss how this framework may apply to representation learning, latent-space construction, foundation models, world models, digital twins, adaptive biological systems, and scientific discovery.  \nTBER suggests a possible design criterion for future artificial intelligence systems: the capacity to detect when their internal representations have reached explanatory limits. Such mechanisms could support autonomous representational evolution, self-directed model refinement, and more adaptive forms of knowledge generation.  \nKeywords: Representation Learning, Representational Emergence, Explanatory Insufficiency, Latent Spaces, World Models, Foundation Models, Autonomous Artificial Intelligence, Machine Learning, Meta-Representation, Adaptive Systems.  \n1 Introduction  \nRepresentation learning is one of the central foundations of modern machine learning [14] . Its objective is not only to process observed data, but also to construct internal representations that make relevant  \nstructures, relations, and transformations more accessible to learning systems. This progression can be observed historically in the transition from handcrafted features to learned embeddings, latent spaces, foundation models, world models, and digital twins [13, 14, 15, 16] .  \nMost work in machine learning focuses on improving representations once a representational framework has already been selected. Deep learning architectures, self-supervised learni","cbCaio1T8NIhzHPg","https://ap.wps.com/l/cbCaio1T8NIhzHPg","pdf",209769,1,25,"English","en",105,"# Abstract\n# 1 Introduction\n## Representation learning and representation frameworks\n## Limitations of existing optimization-focused research\n## Explanatory insufficiency in adaptive systems and AI","[{\"question\":\"What does the Bootstrap Theory of Representational Emergence (TBER) explain?\",\"answer\":\"TBER describes how new representations arise when existing ones become explanatorily insufficient, even if they can still describe observations. It treats representational innovation as driven by persistent explanatory gaps rather than only by more data or compute.\"},{\"question\":\"What is explanatory insufficiency, according to TBER?\",\"answer\":\"A representation becomes insufficient when its explanatory domain is exceeded: it can summarize observations but can no longer make their organization or transformations intelligible. The mechanism is framed as a positive signal for representational transition.\"},{\"question\":\"How is the bootstrapping process formalized in TBER?\",\"answer\":\"TBER follows a recursive cycle where observations reveal anomalies, anomalies expose explanatory insufficiencies, insufficiencies motivate new representations, and these generate further observations that may reveal new insufficiencies. The paper also formalizes this as a five-stage model including stabilized observation through provisional stabilization.\"}]",1784204950,63,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":27},"bootstrap-theory-of-representational-emergence","",{"@graph":35,"@context":85},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/bootstrap-theory-of-representational-emergence/85616/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-17","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What does the Bootstrap Theory of Representational Emergence (TBER) explain?","Question",{"text":75,"@type":76},"TBER describes how new representations arise when existing ones become explanatorily insufficient, even if they can still describe observations. It treats representational innovation as driven by persistent explanatory gaps rather than only by more data or compute.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is explanatory insufficiency, according to TBER?",{"text":80,"@type":76},"A representation becomes insufficient when its explanatory domain is exceeded: it can summarize observations but can no longer make their organization or transformations intelligible. The mechanism is framed as a positive signal for representational transition.",{"name":82,"@type":73,"acceptedAnswer":83},"How is the bootstrapping process formalized in TBER?",{"text":84,"@type":76},"TBER follows a recursive cycle where observations reveal anomalies, anomalies expose explanatory insufficiencies, insufficiencies motivate new representations, and these generate further observations that may reveal new insufficiencies. The paper also formalizes this as a five-stage model including stabilized observation through provisional stabilization.","https://schema.org",{"og:url":51,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":45,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":45,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":45,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":45,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":45,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":45,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":45,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]