{"id":"https://openalex.org/W7138306397","doi":"https://doi.org/10.48550/arxiv.2603.13401","title":"MAD: Microenvironment-Aware Distillation -- A Pretraining Strategy for Virtual Spatial Omics from Microscopy","display_name":"MAD: Microenvironment-Aware Distillation -- A Pretraining Strategy for Virtual Spatial Omics from Microscopy","publication_year":2026,"publication_date":"2026-03-11","ids":{"openalex":"https://openalex.org/W7138306397","doi":"https://doi.org/10.48550/arxiv.2603.13401"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.13401","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13401","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.13401","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129712628","display_name":"Jiashu Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Jiashu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086830328","display_name":"Kunzan Liu","orcid":"https://orcid.org/0000-0002-3923-3720"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Kunzan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006586376","display_name":"Yeojin Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Yeojin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129732239","display_name":"Saurabh Sinha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sinha, Saurabh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129649951","display_name":"Sixian You","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"You, Sixian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.8794999718666077,"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"}},"topics":[{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.8794999718666077,"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"}},{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.10790000110864639,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0026000000070780516,"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/bridging","display_name":"Bridging (networking)","score":0.5357999801635742},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5047000050544739},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.48980000615119934},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4788999855518341},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.3488999903202057},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3215999901294708},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.31929999589920044}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6352999806404114},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.5357999801635742},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5047000050544739},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.48980000615119934},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4788999855518341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4778999984264374},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.3885999917984009},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3416000008583069},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3215999901294708},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.31929999589920044},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2874999940395355},{"id":"https://openalex.org/C147080431","wikidata":"https://www.wikidata.org/wiki/Q1074953","display_name":"Microscopy","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.26649999618530273},{"id":"https://openalex.org/C162317418","wikidata":"https://www.wikidata.org/wiki/Q252857","display_name":"Transcriptome","level":4,"score":0.2612999975681305},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.25949999690055847},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.13401","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13401","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.13401","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13401","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Bridging":[0],"microscopy":[1,171],"and":[2,15,20,75,92,108,143,166],"omics":[3,24,165],"would":[4],"allow":[5],"us":[6],"to":[7,37],"read":[8],"molecular":[9],"states":[10],"from":[11,169],"images-at":[12],"single-cell":[13,39],"resolution":[14],"tissue":[16,42],"scale-without":[17],"the":[18,44,72,76,80,141],"cost":[19],"throughput":[21],"limits":[22],"of":[23,46,79,120,145],"technologies.":[25],"Self-supervised":[26],"pretraining":[27,63],"offers":[28],"a":[29,62,85,117,154],"scalable":[30],"approach":[31],"with":[32,116],"minimal":[33],"labels,":[34],"yet":[35],"how":[36],"encode":[38],"identity":[40],"within":[41,147],"environments-and":[43],"extent":[45],"biological":[47,167],"information":[48],"such":[49],"models":[50,115],"can":[51],"capture-remains":[52],"an":[53],"open":[54],"question.":[55],"Here,":[56],"we":[57],"introduce":[58],"MAD":[59,95,111,152],"(microenvironment-aware":[60],"distillation),":[61],"strategy":[64],"that":[65,123,134],"learns":[66],"cell-centric":[67],"embeddings":[68],"by":[69],"jointly":[70],"self-distilling":[71],"morphology":[73],"view":[74,78],"microenvironment":[77],"same":[81],"indexed":[82],"cell":[83,104],"into":[84],"unified":[86],"embedding":[87],"space.":[88],"Across":[89],"diverse":[90],"tissues":[91],"imaging":[93],"modalities,":[94],"achieves":[96],"state-of-the-art":[97],"prediction":[98],"performance":[99],"on":[100,127],"downstream":[101],"tasks":[102],"including":[103],"subtyping,":[105],"transcriptomic":[106],"prediction,":[107],"bioinformatic":[109],"inference.":[110],"even":[112],"outperforms":[113],"foundation":[114],"similar":[118],"number":[119],"model":[121],"parameters":[122],"have":[124],"been":[125],"trained":[126],"substantially":[128],"larger":[129],"datasets.":[130,172],"These":[131],"results":[132],"demonstrate":[133],"MAD's":[135],"dual-view":[136],"joint":[137],"self-distillation":[138],"effectively":[139],"captures":[140],"complexity":[142],"diversity":[144],"cells":[146],"tissues.":[148],"Together,":[149],"this":[150],"establishes":[151],"as":[153],"general":[155],"tool":[156],"for":[157],"representation":[158],"learning":[159],"in":[160],"microscopy,":[161],"enabling":[162],"virtual":[163],"spatial":[164],"insights":[168],"vast":[170]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-18T00:00:00"}