{"id":"https://openalex.org/W7155536081","doi":"https://doi.org/10.48550/arxiv.2604.21573","title":"CHRep: Cross-modal Histology Representation and Post-hoc Calibration for Spatial Gene Expression Prediction","display_name":"CHRep: Cross-modal Histology Representation and Post-hoc Calibration for Spatial Gene Expression Prediction","publication_year":2026,"publication_date":"2026-04-23","ids":{"openalex":"https://openalex.org/W7155536081","doi":"https://doi.org/10.48550/arxiv.2604.21573"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.21573","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.21573","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":null,"license_id":null,"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.2604.21573","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134557701","display_name":"Changfan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Changfan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134517249","display_name":"Xinran Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xinran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134516315","display_name":"Donghai Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Donghai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134518003","display_name":"Fei Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Fei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075836215","display_name":"Lulu Sun","orcid":"https://orcid.org/0000-0001-7543-1532"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Lulu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053619472","display_name":"Zhicheng Zhao","orcid":"https://orcid.org/0000-0001-6506-7298"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Zhicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5109304713","display_name":"Zhu Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meng, Zhu","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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9656999707221985,"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":0.9656999707221985,"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/T10885","display_name":"Gene expression and cancer classification","score":0.012500000186264515,"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":0.01140000019222498,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7271000146865845},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6722999811172485},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6047000288963318},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6011000275611877},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5109999775886536},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.4433000087738037},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.4348999857902527},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4291999936103821}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7271000146865845},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6722999811172485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6255999803543091},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6047000288963318},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6011000275611877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5626000165939331},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5109999775886536},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4433000087738037},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4348999857902527},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4291999936103821},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36910000443458557},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.36500000953674316},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3050000071525574},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.3025999963283539},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2971000075340271},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C2988709989","wikidata":"https://www.wikidata.org/wiki/Q85784623","display_name":"Mean square","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C2986522900","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relationship","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.21573","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.21573","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.21573","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.21573","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spatial":[0],"transcriptomics":[1],"(ST)":[2],"enables":[3],"spatially":[4],"resolved":[5],"gene":[6,22],"profiling":[7],"but":[8],"remains":[9],"expensive":[10],"and":[11,16,27,48,82,148,191,208,216],"low-throughput,":[12],"limiting":[13],"large-cohort":[14],"studies":[15],"routine":[17,25],"clinical":[18],"use.":[19],"Predicting":[20],"spatial":[21,84],"expression":[23],"from":[24,44,113],"hematoxylin":[26],"eosin":[28],"(H&amp;E)":[29],"slides":[30],"is":[31,57,93],"a":[32,58,71,99,110,114,118,132],"promising":[33],"alternative,":[34],"yet":[35],"under":[36,152,164],"realistic":[37],"leave-one-slide-out":[38,165],"evaluation,":[39,166],"existing":[40],"models":[41],"often":[42],"suffer":[43],"slide-level":[45,153],"appearance":[46],"shifts":[47],"regression-driven":[49],"over-smoothing":[50],"that":[51,129],"suppress":[52],"biologically":[53],"meaningful":[54],"variation.":[55],"CHRep":[56,69,136,159],"two-phase":[59],"framework":[60],"for":[61],"robust":[62],"histology-to-expression":[63],"prediction.":[64],"In":[65,87],"the":[66,88,105,156,168,177],"training":[67,106,115],"phase,":[68,90],"learns":[70],"structure-aware":[72],"representation":[73,139],"by":[74,187,201],"jointly":[75],"optimizing":[76],"correlation-aware":[77],"regression,":[78],"symmetric":[79],"image-expression":[80],"alignment,":[81],"coordinate-induced":[83],"topology":[85],"regularization.":[86],"inference":[89],"cross-slide":[91],"robustness":[92],"improved":[94],"without":[95],"backbone":[96],"fine-tuning":[97],"through":[98],"lightweight":[100],"calibration":[101],"module":[102],"trained":[103],"on":[104,131,172,181,189,193,203],"slides,":[107],"which":[108],"combines":[109],"non-parametric":[111],"estimate":[112],"gallery":[116],"with":[117,141,167,206],"magnitude-regularized":[119],"correction":[120,151],"module.":[121],"Unlike":[122],"prior":[123],"embedding-alignment":[124],"or":[125],"retrieval-based":[126],"transfer":[127],"methods":[128],"rely":[130],"single":[133],"prediction":[134],"route,":[135],"couples":[137],"topology-preserving":[138],"learning":[140],"post-hoc":[142],"calibration,":[143],"enabling":[144],"stable":[145],"neighborhood":[146],"retrieval":[147],"controlled":[149],"bias":[150],"shifts.":[154],"Across":[155],"three":[157],"cohorts,":[158],"consistently":[160],"improves":[161,200],"gene-wise":[162],"correlation":[163,179],"largest":[169],"gains":[170],"observed":[171],"Alex+10x.":[173],"Relative":[174,195],"to":[175,196],"HAGE,":[176],"Pearson":[178],"coefficient":[180],"all":[182],"considered":[183],"genes":[184],"[PCC(ACG)]":[185],"increases":[186],"4.0%":[188],"cSCC":[190],"9.8%":[192],"HER2+.":[194],"mclSTExp,":[197],"PCC(ACG)":[198],"further":[199],"39.5%":[202],"Alex+10x,":[204],"together":[205],"9.7%":[207],"9.0%":[209],"reductions":[210],"in":[211],"mean":[212,217],"squared":[213],"error":[214,219],"(MSE)":[215],"absolute":[218],"(MAE),":[220],"respectively.":[221]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-25T00:00:00"}
