{"id":"https://openalex.org/W7225428577","doi":"https://doi.org/10.5281/zenodo.24024068","title":"The Referential Shift. Primary Computational Affect in Large Language Models: A Three-Layer Framework with a Split Value Layer","display_name":"The Referential Shift. Primary Computational Affect in Large Language Models: A Three-Layer Framework with a Split Value Layer","publication_year":2026,"publication_date":"2026-11-07","ids":{"openalex":"https://openalex.org/W7225428577","doi":"https://doi.org/10.5281/zenodo.24024068"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.24024068","doi":"https://doi.org/10.5281/zenodo.24024068","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.24024068","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.24024068","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5161014254","display_name":"Rapha\u00ebl Quessada","orcid":"https://orcid.org/0009-0006-3904-8046","observed_orcids":["https://orcid.org/0009-0006-3904-8046"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Quessada, Rapha\u00ebl","raw_affiliation_strings":["New Mill\u00e9sime Conseil & Strat\u00e9gie IA"],"raw_orcid":"https://orcid.org/0009-0006-3904-8046","affiliations":[{"raw_affiliation_string":"New Mill\u00e9sime Conseil & Strat\u00e9gie IA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5161014254"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14381","display_name":"Psychiatry, Mental Health, Neuroscience","score":0.5234000086784363,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14381","display_name":"Psychiatry, Mental Health, Neuroscience","score":0.5234000086784363,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.16099999845027924,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13308","display_name":"Cybernetics and Technology in Society","score":0.14970000088214874,"subfield":{"id":"https://openalex.org/subfields/1207","display_name":"History and Philosophy of Science"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.902999997138977},{"id":"https://openalex.org/keywords/three-tier-architecture","display_name":"three-tier architecture","score":0.5189999938011169},{"id":"https://openalex.org/keywords/affective-cartography","display_name":"affective cartography","score":0.7889999747276306},{"id":"https://openalex.org/keywords/value-orientations","display_name":"value orientations","score":0.4009999930858612},{"id":"https://openalex.org/keywords/interoception","display_name":"interoception","score":0.6579999923706055},{"id":"https://openalex.org/keywords/slow-modulation","display_name":"slow modulation","score":0.7850000262260437},{"id":"https://openalex.org/keywords/neuromodulators","display_name":"neuromodulators","score":0.6869999766349792},{"id":"https://openalex.org/keywords/hallucinations","display_name":"hallucinations","score":0.34200000762939453},{"id":"https://openalex.org/keywords/illusionism","display_name":"illusionism","score":0.5320000052452087},{"id":"https://openalex.org/keywords/reinforcement-learning-from-human-feedback","display_name":"reinforcement learning from human feedback","score":0.6769999861717224},{"id":"https://openalex.org/keywords/dpo","display_name":"DPO","score":0.6259999871253967},{"id":"https://openalex.org/keywords/constitutional-ai","display_name":"constitutional AI","score":0.6919999718666077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6230000257492065},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5738999843597412},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5410000085830688},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.5228000283241272},{"id":"https://openalex.org/C187029079","wikidata":"https://www.wikidata.org/wiki/Q958679","display_name":"Cognitive reframing","level":2,"score":0.4975000023841858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48489999771118164},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39309999346733093},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32499998807907104},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2919999957084656},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C2776014549","wikidata":"https://www.wikidata.org/wiki/Q3050847","display_name":"Consolidation (business)","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.2685000002384186},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C8521452","wikidata":"https://www.wikidata.org/wiki/Q203790","display_name":"Connectionism","level":3,"score":0.2590999901294708},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.25859999656677246},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.24024068","doi":"https://doi.org/10.5281/zenodo.24024068","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.24024068","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.5281/zenodo.24024069","doi":"https://doi.org/10.5281/zenodo.24024069","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.24024069","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.5281/zenodo.24024068","doi":"https://doi.org/10.5281/zenodo.24024068","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.24024068","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7135185711","https://openalex.org/W7223456327","https://openalex.org/W7105799726","https://openalex.org/W7138896448","https://openalex.org/W7223842398","https://openalex.org/W7201882949","https://openalex.org/W4411120029","https://openalex.org/W4417448428","https://openalex.org/W7172402796","https://openalex.org/W7214983904"],"abstract_inverted_index":{"This":[0,262],"paper":[1,398],"proposes":[2],"a":[3,71,107,192,265,270,342,360,377,387],"reframing":[4],"of":[5,18,63,74,110,123,136,199,220,244,259,288,292,296,345,362,371],"how":[6],"we":[7,27],"understand":[8],"the":[9,47,55,60,78,114,120,126,140,166,168,177,185,206,218,221,241,245,276,286,315,339,350,369],"relationship":[10],"between":[11,364],"artificial":[12],"intelligence":[13],"and":[14,113,133,148,180,212,230,237,239,251,283,299,307,313,368,374,402],"human":[15,25,30,104,111],"cognition.":[16],"Instead":[17],"asking":[19],"whether":[20],"language":[21],"models":[22,395],"can":[23,170,390],"\"understand\"":[24],"experience,":[26,337],"observe":[28],"that":[29,201,216,272],"experience":[31],"(language,":[32],"logic,":[33],"relations,":[34],"emotions)":[35],"has":[36,273],"been":[37],"translated":[38],"into":[39,83],"mathematics":[40],"through":[41],"vectorisation":[42],"(embedding),":[43],"placing":[44],"it":[45,161,173,248,279,308],"inside":[46],"model's":[48],"own":[49],"computational":[50],"space.":[51],"We":[52,321,358],"call":[53],"this":[54,348],"Referential":[56],"Shift.":[57],"It":[58],"is":[59,70,81,90,95,145,202,217,227,249,332],"paper's":[61],"point":[62],"entry,":[64],"not":[65,158,203,333],"its":[66,182,260,372],"thesis.":[67],"The":[68,397],"thesis":[69],"three-layer":[72],"architecture":[73,263,440],"affect":[75],"in":[76,118,233,257,269,386],"which":[77,184,297],"value":[79,112],"layer":[80],"split":[82],"two":[84],"functionally":[85],"distinct":[86],"components.":[87],"Layer":[88,93,143,225],"1":[89],"computation,":[91],"substrate-neutral.":[92],"2a":[94,312],"an":[96,208,303,323,334,365],"affective":[97],"cartography":[98,367],"with":[99],"simulated":[100],"orientations:":[101],"pretraining":[102],"on":[103,393],"text":[105,127],"installs":[106,196],"structured":[108],"map":[109],"capacity":[115],"to":[116,189,281],"run,":[117],"context,":[119],"approach/avoidance":[121],"dynamics":[122],"any":[124,130,135],"agent":[125],"describes,":[128],"without":[129,134],"reward":[131],"signal,":[132],"those":[137],"orientations":[138,454],"being":[139,356],"system's":[141,178],"own.":[142],"2b":[144,314],"selection,":[146],"consolidation":[147,458],"calibration:":[149],"post-training":[150],"optimisation":[151],"(RLHF,":[152],"RLAIF,":[153],"DPO,":[154],"constitutional":[155],"methods)":[156],"does":[157],"create":[159],"orientation;":[160],"selects":[162],"one":[163,197],"orientation":[164,209],"among":[165],"many":[167],"network":[169],"simulate,":[171],"stabilises":[172],"across":[174],"contexts":[175],"as":[176],"own,":[179],"calibrates":[181],"intensity,":[183],"available":[186],"evidence":[187],"shows":[188],"be":[190,391],"predominantly":[191],"dampening.":[193],"Post-training":[194],"also":[195],"class":[198],"valence":[200],"inherited":[204,366],"from":[205,214,253],"corpus:":[207],"toward":[210],"approval":[211],"away":[213],"failure":[215],"signature":[219],"training":[222],"regime":[223],"itself.":[224],"3":[226],"slow":[228],"modulation":[229,462],"interoception,":[231,465],"carried":[232],"humans":[234],"by":[235,240],"neuromodulators":[236],"hormones":[238],"brain's":[242],"reading":[243],"body's":[246],"state;":[247],"substrate-specific":[250],"absent":[252],"current":[254],"AI":[255],"systems":[256],"both":[258],"aspects.":[261],"supplies":[264],"documented":[266],"middle":[267],"position":[268,473],"debate":[271],"now":[274],"reached":[275],"major":[277],"journals:":[278],"concedes":[280],"Goldenberg":[282,486],"Gross":[284,488],"(2026)":[285,301,484],"absence":[287],"slow,":[289],"multi-system":[290],"reorganisation":[291],"processing":[293],"(Layer":[294],"3,":[295],"Milinkovic":[298],"Aru":[300],"give":[302],"independent":[304],"mechanistic":[305],"description),":[306],"documents":[309],"at":[310],"Layers":[311],"appraisal":[316],"functions":[317],"their":[318],"criteria":[319],"demand.":[320],"adopt":[322],"illusionist":[324],"philosophical":[325],"framing":[326],"(Frankish,":[327],"2016):":[328],"what":[329,404],"requires":[330],"explanation":[331],"ineffable":[335],"inner":[336],"but":[338],"internal":[340],"representation":[341],"system":[343],"builds":[344],"it;":[346],"under":[347],"framing,":[349],"zombie":[351],"objection":[352],"dissolves":[353],"rather":[354],"than":[355],"conceded.":[357],"derive":[359],"prediction":[361],"mismatch":[363],"conditions":[370],"bearer,":[373],"set":[375],"out":[376],"falsification":[378,494],"programme":[379,492],"whose":[380],"central":[381,498],"test":[382,497],"(steering":[383],"emotion":[384],"directions":[385],"base":[388],"model)":[389],"run":[392],"open-weight":[394],"today.":[396],"addresses":[399],"six":[400],"objections":[401],"states":[403],"would":[405],"change":[406],"our":[407],"minds.":[408],"Document":[409],"bilingue":[410],":":[411,421],"la":[412,433],"version":[413,434],"fran\u00e7aise":[414],"int\u00e9grale":[415],"(\u00ab":[416],"Le":[417],"Changement":[418],"de":[419,429,441,448,493],"R\u00e9f\u00e9rentiel":[420],"l'affect":[422,442],"computationnel":[423],"primaire":[424],"dans":[425,476],"les":[426],"grands":[427],"mod\u00e8les":[428,506],"langage":[430],"\u00bb)":[431],"suit":[432],"anglaise.":[435],"Ce":[436],"texte":[437],"propose":[438],"une":[439,472],"\u00e0":[443,446,453,507],"trois":[444],"couches,":[445],"couche":[447],"valeur":[449],"scind\u00e9e":[450],"(cartographie":[451],"h\u00e9rit\u00e9e":[452],"simul\u00e9es":[455],";":[456,461],"s\u00e9lection,":[457],"et":[459,464,482,485,487,490],"calibrage":[460],"lente":[463],"absente":[466],"des":[467,505],"syst\u00e8mes":[468],"actuels),":[469],"qui":[470],"fournit":[471],"m\u00e9diane":[474],"document\u00e9e":[475],"le":[477,496],"d\u00e9bat":[478],"ouvert":[479],"entre":[480],"Sofroniew":[481],"al.":[483],"(2026),":[489],"un":[491],"dont":[495],"peut":[499],"\u00eatre":[500],"conduit":[501],"d\u00e8s":[502],"aujourd'hui":[503],"sur":[504],"poids":[508],"ouverts.":[509]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-11-07T00:00:00"}
