{"id":"https://openalex.org/W7161797798","doi":"https://doi.org/10.48550/arxiv.2605.19343","title":"What Makes a Representation Good for Single-Cell Perturbation Prediction?","display_name":"What Makes a Representation Good for Single-Cell Perturbation Prediction?","publication_year":2026,"publication_date":"2026-05-19","ids":{"openalex":"https://openalex.org/W7161797798","doi":"https://doi.org/10.48550/arxiv.2605.19343"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.19343","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19343","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,"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.2605.19343","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136508863","display_name":"Wenkang Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Wenkang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136559622","display_name":"Yuhang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yuhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136577897","display_name":"Yichao Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Yichao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136571257","display_name":"Erdun Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Erdun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136601414","display_name":"Jiayi Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Jiayi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058061726","display_name":"Ehsan Abbasnejad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abbasnejad, Ehsan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136583728","display_name":"Lina Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Lina","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127074255","display_name":"Javen Qinfeng Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Javen Qinfeng","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":0.9430000185966492,"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":0.9430000185966492,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.009399999864399433,"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/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.004699999932199717,"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/spurious-relationship","display_name":"Spurious relationship","score":0.8422999978065491},{"id":"https://openalex.org/keywords/identifiability","display_name":"Identifiability","score":0.5873000025749207},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.522599995136261},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.4618000090122223},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.4104999899864197},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.38190001249313354}],"concepts":[{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.8422999978065491},{"id":"https://openalex.org/C122770356","wikidata":"https://www.wikidata.org/wiki/Q1656753","display_name":"Identifiability","level":2,"score":0.5873000025749207},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.522599995136261},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5103999972343445},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47909998893737793},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.4618000090122223},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4424000084400177},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.4104999899864197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4032000005245209},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.38190001249313354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37439998984336853},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2784999907016754},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.19343","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19343","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,"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.2605.19343","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19343","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,"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Single-cell":[0],"perturbation":[1,119],"modeling":[2],"is":[3,32],"fundamental":[4],"for":[5,68,104],"understanding":[6],"and":[7,51,57,95,158],"predicting":[8],"cellular":[9],"responses":[10],"to":[11,21,55,80,99],"genetic":[12],"perturbations.":[13],"However,":[14],"existing":[15],"approaches,":[16],"from":[17,91],"causal":[18,97],"representation":[19],"learning":[20],"foundation":[22],"models,":[23],"often":[24],"struggle":[25],"with":[26],"an":[27,109],"overlooked":[28],"challenge:":[29],"gene":[30],"expression":[31],"dominated":[33],"by":[34],"perturbation-invariant":[35],"information,":[36,53],"while":[37],"perturbation-specific":[38,52,62,89],"signals":[39,63],"are":[40],"intrinsically":[41],"sparse.":[42],"As":[43],"a":[44,76,143],"result,":[45],"learned":[46],"representations":[47,98],"either":[48],"entangle":[49],"invariant":[50,93],"leading":[54],"spurious":[56],"non-generalizable":[58],"predictors,":[59],"or":[60],"suppress":[61],"altogether,":[64],"rendering":[65],"them":[66],"ineffective":[67],"prediction.":[69,105],"To":[70],"address":[71],"this,":[72],"we":[73],"propose":[74],"PerturbedVAE,":[75],"general":[77],"framework":[78,86,129],"designed":[79],"resolve":[81],"this":[82],"signal":[83],"imbalance.":[84],"The":[85],"explicitly":[87],"separates":[88],"information":[90,103],"dominant":[92],"structure":[94],"recovers":[96],"effectively":[100],"utilize":[101],"such":[102,135],"We":[106],"further":[107],"provide":[108],"identifiability":[110],"analysis":[111],"that":[112],"characterizes":[113],"the":[114,128],"conditions":[115],"under":[116,134],"which":[117],"sparse":[118],"effects":[120],"can":[121,130],"be":[122,131],"reliably":[123],"recovered,":[124],"thereby":[125],"clarifying":[126],"how":[127],"concretely":[132],"specified":[133],"conditions.":[136],"Empirically,":[137],"PerturbedVAE":[138],"achieves":[139],"state-of-the-art":[140],"performance":[141],"on":[142,154],"widely":[144],"used":[145],"benchmark":[146],"across":[147],"multiple":[148],"evaluation":[149],"settings,":[150],"yielding":[151],"significant":[152],"gains":[153],"out-of-distribution":[155],"combinatorial":[156],"predictions":[157],"uncovering":[159],"interpretable":[160],"perturbation-response":[161],"programs.":[162]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-21T00:00:00"}