{"id":"https://openalex.org/W7159662593","doi":"https://doi.org/10.48550/arxiv.2604.27124","title":"Better Models, Faster Training: Sigmoid Attention for single-cell Foundation Models","display_name":"Better Models, Faster Training: Sigmoid Attention for single-cell Foundation Models","publication_year":2026,"publication_date":"2026-04-29","ids":{"openalex":"https://openalex.org/W7159662593","doi":"https://doi.org/10.48550/arxiv.2604.27124"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.27124","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27124","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.2604.27124","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017331139","display_name":"Vijay Sadashivaiah","orcid":"https://orcid.org/0000-0003-3375-3810"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sadashivaiah, Vijay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094018032","display_name":"Georgios Dasoulas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dasoulas, Georgios","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074292004","display_name":"Judith Mueller","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mueller, Judith","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134940563","display_name":"Soumya Ghosh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ghosh, Soumya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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":0.8704000115394592,"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":0.8704000115394592,"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":0.03819999843835831,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.01489999983459711,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.9247000217437744},{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.8657000064849854},{"id":"https://openalex.org/keywords/jacobian-matrix-and-determinant","display_name":"Jacobian matrix and determinant","score":0.4869000017642975},{"id":"https://openalex.org/keywords/clipping","display_name":"Clipping (morphology)","score":0.4065000116825104},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4027000069618225},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.31850001215934753}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9247000217437744},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.8657000064849854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5881999731063843},{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.4869000017642975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48590001463890076},{"id":"https://openalex.org/C2776848632","wikidata":"https://www.wikidata.org/wiki/Q853463","display_name":"Clipping (morphology)","level":2,"score":0.4065000116825104},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4027000069618225},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C178009071","wikidata":"https://www.wikidata.org/wiki/Q93344","display_name":"Trigonometric functions","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C130367717","wikidata":"https://www.wikidata.org/wiki/Q189791","display_name":"Diagonal","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25999999046325684},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.27124","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27124","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.2604.27124","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27124","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Training":[0],"stable":[1,66],"biological":[2,169,184],"foundation":[3,185],"models":[4,50,116],"requires":[5],"rethinking":[6],"attention":[7,14,22,53,81,115,175],"mechanisms:":[8],"we":[9,140],"find":[10],"that":[11,79,149],"using":[12],"sigmoid":[13,33,52,80,136,174],"as":[15,88,176],"a":[16,93],"drop":[17],"in":[18,74,97],"replacement":[19],"for":[20,168,183],"softmax":[21,61,75,124],"a)":[23],"produces":[24],"better":[25,39],"learned":[26],"representations:":[27],"on":[28,112,121,153],"six":[29],"diverse":[30],"single-cell":[31],"datasets,":[32],"achieves":[34,150],"25%":[35],"higher":[36],"cell-type":[37,40],"separation,":[38],"cohesion":[41],"metrics,":[42],"and":[43,63,92,142,159,180],"lower":[44],"validation":[45],"loss,":[46],"b)":[47],"faster":[48,58],"training,":[49],"with":[51,99,127,161],"train":[54],"up":[55],"to":[56,90],"10%":[57],"than":[59],"their":[60],"counterparts,":[62],"c)":[64],"more":[65],"training":[67,107],"by":[68,130],"eliminating":[69],"inherent":[70],"sources":[71],"of":[72,133],"instability":[73],"attention.":[76],"We":[77],"establish":[78,173],"has":[82],"globally":[83],"bounded":[84],"derivatives":[85],"($\\leq":[86],"0.25$)":[87],"opposed":[89],"softmax,":[91],"diagonal":[94],"Jacobian":[95],"structure":[96],"contrast":[98],"softmax's":[100],"dense":[101],"coupling,":[102],"which":[103,165],"together":[104],"help":[105],"alleviate":[106],"instabilities.":[108],"In":[109],"stress":[110],"tests":[111],"160M-parameter":[113],"bidirectional":[114],"trained":[117],"without":[118],"gradient":[119],"clipping":[120],"8K-token":[122],"sequences,":[123],"diverges":[125],"catastrophically,":[126],"gradients":[128],"exploding":[129],"four":[131],"orders":[132],"magnitude,":[134],"while":[135],"remains":[137],"stable.":[138],"Finally,":[139],"implement":[141],"open-source":[143],"TritonSigmoid,":[144],"an":[145],"efficient":[146],"GPU":[147],"kernel":[148],"515":[151],"TFLOPS":[152],"H100":[154],"GPUs,":[155],"outperforming":[156],"both":[157,177],"FlashAttention-2":[158],"FlashSigmoid,":[160],"native":[162],"padding":[163],"support,":[164],"is":[166,188],"essential":[167],"sequences.":[170],"Our":[171],"results":[172],"theoretically":[178],"grounded":[179],"empirically":[181],"superior":[182],"models.":[186],"Code":[187],"available":[189],"at":[190],"https://github.com/MSDLLCpapers/triton-sigmoid":[191]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-02T00:00:00"}