{"id":"https://openalex.org/W7223384569","doi":"https://doi.org/10.48550/arxiv.2610.30215","title":"AI Mindmeld: A Latent Interconnect Protocol","display_name":"AI Mindmeld: A Latent Interconnect Protocol","publication_year":2026,"publication_date":"2026-10-21","ids":{"openalex":"https://openalex.org/W7223384569","doi":"https://doi.org/10.48550/arxiv.2610.30215"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.30215","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.30215","pdf_url":"https://arxiv.org/pdf/2610.30215","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.30215","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020401988","display_name":"Siavash Golkar","orcid":"https://orcid.org/0000-0002-1867-2054","observed_orcids":["https://orcid.org/0000-0002-1867-2054"]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Golkar, Siavash","raw_affiliation_strings":["Center for Data Science , New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Data Science , New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116249301","display_name":"Jake Kovalic","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kovalic, Jake","raw_affiliation_strings":["Department of Applied Physics , Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Physics , Yale University","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5159142508","display_name":"Shirley Ho","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ho, Shirley","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.7196999788284302,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.7196999788284302,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10028","display_name":"Topic Modeling","score":0.13019999861717224,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.07429999858140945,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/zero-shot-transfer","display_name":"zero-shot transfer","score":0.6840000152587891},{"id":"https://openalex.org/keywords/compositional-reasoning","display_name":"compositional reasoning","score":0.6359999775886536},{"id":"https://openalex.org/keywords/protein-representation","display_name":"protein representation","score":0.5410000085830688}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7433000206947327},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7064999938011169},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6841999888420105},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6057999730110168},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.5993000268936157},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5080000162124634},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4740999937057495},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.41179999709129333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3605000078678131},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.33660000562667847},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3089999854564667},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3041999936103821},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2694999873638153},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C52723943","wikidata":"https://www.wikidata.org/wiki/Q1127410","display_name":"Serialization","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C123745756","wikidata":"https://www.wikidata.org/wiki/Q1665949","display_name":"Interconnection","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.30215","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.30215","pdf_url":"https://arxiv.org/pdf/2610.30215","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2610.30215","doi":"https://doi.org/10.48550/arxiv.2610.30215","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.30215","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.30215","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.30215","pdf_url":"https://arxiv.org/pdf/2610.30215","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320319356","display_name":"Flatiron Health","ror":"https://ror.org/0508h6p74"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7223384569.pdf","grobid_xml":"https://content.openalex.org/works/W7223384569.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W4386791134","https://openalex.org/W4393159659","https://openalex.org/W4416103085","https://openalex.org/W4417524783"],"related_works":["https://openalex.org/W7204819907","https://openalex.org/W7204275914","https://openalex.org/W7169829189","https://openalex.org/W4387507766","https://openalex.org/W7164993070","https://openalex.org/W7160988562","https://openalex.org/W7128609484","https://openalex.org/W4402671287","https://openalex.org/W4402670791","https://openalex.org/W7166817687"],"abstract_inverted_index":{"LLMs":[0,97,180],"can":[1],"act":[2],"as":[3,22,96,187],"scientific":[4,231],"agents":[5],"using":[6],"tools":[7],"to":[8,53,59,110,154,206,216,219],"consult":[9],"specialists":[10,72,109],"and":[11,65,67,99,105,114,117,143,162,222,242,247],"run":[12],"experiments.":[13],"Yet":[14],"specialist":[15,84,185,204],"information":[16,47,133,233],"must":[17],"enter":[18],"their":[19],"context,":[20],"generally":[21,164],"text,":[23],"images,":[24],"audio":[25],"or":[26,138,197],"video:":[27],"a":[28,41],"bottleneck":[29],"between":[30],"models":[31,218],"with":[32,166,169,224],"rich,":[33],"high-dimensional":[34],"representations.":[35],"We":[36,101,150,201],"advocate":[37],"direct":[38],"representation":[39,209],"exchange:":[40],"mindmeld":[42],"conveying":[43],"many":[44],"properties,":[45],"including":[46],"an":[48],"LLM":[49,87,137,167,214],"would":[50],"not":[51,182,192],"think":[52],"request.":[54],"It":[55],"should":[56],"be":[57],"extensible":[58],"new":[60,144],"specialists,":[61],"flexible":[62],"across":[63,69],"questions":[64],"tasks,":[66],"compositional":[68],"independently":[70],"connected":[71],"without":[73,134,157],"joint":[74,158],"training.":[75,159],"The":[76],"Latent":[77],"Interconnect":[78],"Protocol":[79],"(LIP)":[80],"learns":[81],"connectors":[82,92,130],"mapping":[83],"representations":[85,186],"into":[86],"internal":[88],"states.":[89],"Training":[90],"only":[91],"keeps":[93],"this":[94],"practical":[95],"grow":[98],"evolve.":[100],"connect":[102],"three":[103,106],"protein":[104],"small":[107],"molecule":[108],"Gemma":[111],"3":[112],"(4B":[113],"12B":[115],"parameters)":[116],"Kimi":[118],"K2.6":[119],"(1T":[120],"total,":[121],"32B":[122],"active),":[123],"freezing":[124],"all":[125],"pretrained":[126,240],"models.":[127],"Independently":[128],"trained":[129,183],"provide":[131,207],"useful":[132],"changing":[135],"the":[136],"existing":[139],"connectors,":[140,241],"supporting":[141],"familiar":[142],"question":[145],"types":[146],"about":[147],"unseen":[148],"objects.":[149],"demonstrate":[151],"zero-shot":[152,174],"transfer":[153],"cross-domain":[155],"tasks":[156],"Task":[160],"performance":[161],"compositionality":[163],"improve":[165],"capability,":[168],"especially":[170],"strong":[171],"gains":[172],"in":[173,199],"task":[175],"transfer.":[176],"Limitations":[177],"remain:":[178],"current":[179],"were":[181],"for":[184,244],"native":[188],"inputs;":[189],"access":[190],"does":[191],"ensure":[193],"reliable":[194],"interpretation,":[195],"integration":[196],"use":[198],"reasoning.":[200],"call":[202],"on":[203,213],"developers":[205,215],"consistent":[208],"interfaces":[210],"and,":[211],"especially,":[212],"train":[217],"receive,":[220],"combine":[221],"reason":[223],"these":[225],"inputs.":[226],"These":[227],"efforts":[228],"could":[229],"expand":[230],"agents'":[232],"while":[234],"preserving":[235],"conventional":[236],"tools'":[237],"flexibility.":[238],"Data,":[239],"code":[243],"training,":[245],"evaluation":[246],"interactive":[248],"inference:":[249],"https://github.com/PolymathicAI/AI-Mindmeld":[250]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-24T00:00:00"}
