{"id":"https://openalex.org/W7160992005","doi":"https://doi.org/10.48550/arxiv.2605.10970","title":"Context-Gated Associative Retrieval: From Theory to Transformers","display_name":"Context-Gated Associative Retrieval: From Theory to Transformers","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160992005","doi":"https://doi.org/10.48550/arxiv.2605.10970"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.10970","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10970","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.10970","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034261952","display_name":"Moulik Choraria","orcid":"https://orcid.org/0000-0001-7609-3563"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choraria, Moulik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107496306","display_name":"Argyrios Gerogiannis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gerogiannis, Argyrios","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136023495","display_name":"Vidhata Jayaraman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jayaraman, Vidhata","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002047466","display_name":"Ankur Mani","orcid":"https://orcid.org/0000-0002-1357-3815"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mani, Ankur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065423139","display_name":"Lav R. Varshney","orcid":"https://orcid.org/0000-0003-2798-5308"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Varshney, Lav R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T10320","display_name":"Neural Networks and Applications","score":0.15610000491142273,"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/T10320","display_name":"Neural Networks and Applications","score":0.15610000491142273,"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/T10448","display_name":"Memory and Neural Mechanisms","score":0.12919999659061432,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.06679999828338623,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/associative-property","display_name":"Associative property","score":0.6764000058174133},{"id":"https://openalex.org/keywords/content-addressable-memory","display_name":"Content-addressable memory","score":0.6442999839782715},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5831000208854675},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5289999842643738},{"id":"https://openalex.org/keywords/content-addressable-storage","display_name":"Content-addressable storage","score":0.5066999793052673},{"id":"https://openalex.org/keywords/associative-learning","display_name":"Associative learning","score":0.43700000643730164},{"id":"https://openalex.org/keywords/hopfield-network","display_name":"Hopfield network","score":0.41350001096725464},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4066999852657318}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6983000040054321},{"id":"https://openalex.org/C159423971","wikidata":"https://www.wikidata.org/wiki/Q177251","display_name":"Associative property","level":2,"score":0.6764000058174133},{"id":"https://openalex.org/C53442348","wikidata":"https://www.wikidata.org/wiki/Q745101","display_name":"Content-addressable memory","level":3,"score":0.6442999839782715},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5831000208854675},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5289999842643738},{"id":"https://openalex.org/C2778618852","wikidata":"https://www.wikidata.org/wiki/Q1128613","display_name":"Content-addressable storage","level":4,"score":0.5066999793052673},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5024999976158142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49410000443458557},{"id":"https://openalex.org/C2983526489","wikidata":"https://www.wikidata.org/wiki/Q133500","display_name":"Associative learning","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C46421273","wikidata":"https://www.wikidata.org/wiki/Q1407668","display_name":"Hopfield network","level":3,"score":0.41350001096725464},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4066999852657318},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.38850000500679016},{"id":"https://openalex.org/C120620853","wikidata":"https://www.wikidata.org/wiki/Q506355","display_name":"Bidirectional associative memory","level":4,"score":0.3813000023365021},{"id":"https://openalex.org/C194544171","wikidata":"https://www.wikidata.org/wiki/Q21105679","display_name":"Gating","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.314300000667572},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.31150001287460327},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.2994999885559082},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C2985957978","wikidata":"https://www.wikidata.org/wiki/Q492","display_name":"Human memory","level":3,"score":0.27160000801086426},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2597000002861023}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.10970","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10970","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.10970","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10970","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7054506540298462}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Hopfield":[0],"networks":[1],"and":[2,15,55,102,159],"their":[3],"generalizations":[4],"have":[5],"established":[6],"deep":[7],"connections":[8],"among":[9],"biological":[10],"associative":[11,42,156],"memories,":[12],"statistical":[13],"physics,":[14],"transformers.":[16],"Yet":[17],"most":[18],"models":[19],"treat":[20],"retrieval":[21,51,92],"as":[22,128],"a":[23,40,46,83,98,103,118,138,152],"fixed":[24,86],"query-to-memory":[25],"mapping,":[26],"ignoring":[27],"the":[28,50,80,90,142],"role":[29],"of":[30],"external":[31],"context":[32,62,136],"in":[33,74],"recall.":[34,57],"In":[35],"this":[36,111,149],"work,":[37],"we":[38,77,116],"propose":[39],"two-stage":[41],"memory":[43,139,157],"architecture,":[44],"wherein":[45],"context-gate":[47],"subcircuit":[48],"reshapes":[49],"energy":[52],"landscape":[53],"before":[54],"during":[56],"We":[58,108],"show":[59],"theoretically":[60],"that":[61,79,89,124],"gating":[63],"increases":[64],"inter-memory":[65],"separation":[66],"while":[67],"inducing":[68],"sparsity,":[69],"translating":[70],"into":[71],"exponential":[72],"improvements":[73],"retrieval.":[75,130],"Crucially,":[76],"prove":[78],"system":[81],"admits":[82],"unique":[84],"self-consistent":[85],"point,":[87],"revealing":[88],"resulting":[91],"state":[93],"is":[94],"driven":[95],"by":[96],"both":[97],"direct":[99],"contextual":[100],"bias":[101],"second-order":[104],"retrieval-gate":[105],"feedback":[106],"loop.":[107],"then":[109],"bridge":[110],"theory":[112,158],"to":[113,145],"transformers;":[114],"specifically,":[115],"evaluate":[117],"first-order":[119],"approximation":[120],"on":[121],"Llama-3,":[122],"confirming":[123],"in-context":[125],"learning":[126],"acts":[127],"context-gated":[129],"Native":[131],"dynamics":[132],"mirror":[133],"our":[134],"theory:":[135],"localizes":[137],"subspace,":[140],"enabling":[141],"zero-shot":[143],"query":[144],"cleanly":[146],"discriminate.":[147],"Ultimately,":[148],"framework":[150],"provides":[151],"mechanistic":[153],"link":[154],"between":[155],"LLM":[160],"phenomenology.":[161]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-14T00:00:00"}