{"id":"https://openalex.org/W7128638379","doi":"https://doi.org/10.48550/arxiv.2602.09764","title":"Self-Supervised Learning as Discrete Communication","display_name":"Self-Supervised Learning as Discrete Communication","publication_year":2026,"publication_date":"2026-02-10","ids":{"openalex":"https://openalex.org/W7128638379","doi":"https://doi.org/10.48550/arxiv.2602.09764"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.09764","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.09764","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.2602.09764","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120694160","display_name":"Kawtar Zaher","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zaher, Kawtar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010372672","display_name":"Ilyass Moummad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moummad, Ilyass","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125641942","display_name":"Olivier Buisson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Buisson, Olivier","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124773945","display_name":"Alexis Joly","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joly, Alexis","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7271000146865845,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7271000146865845,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.08619999885559082,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.06700000166893005,"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/binary-number","display_name":"Binary number","score":0.6748999953269958},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5899999737739563},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5403000116348267},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4383000135421753},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.42170000076293945},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4203000068664551},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.39489999413490295},{"id":"https://openalex.org/keywords/discrete-time-and-continuous-time","display_name":"Discrete time and continuous time","score":0.39399999380111694},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3490000069141388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6797000169754028},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.6748999953269958},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5899999737739563},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5403000116348267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5040000081062317},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4383000135421753},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42820000648498535},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.42170000076293945},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4203000068664551},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.39399999380111694},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3375000059604645},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.3149000108242035},{"id":"https://openalex.org/C105842133","wikidata":"https://www.wikidata.org/wiki/Q1899679","display_name":"Visual communication","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.2955000102519989},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2802000045776367},{"id":"https://openalex.org/C146749787","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete-time signal","level":5,"score":0.27070000767707825},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.09764","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.09764","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.2602.09764","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.09764","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":[{"display_name":"Quality Education","score":0.718912661075592,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Most":[0],"self-supervised":[1,34,145],"learning":[2,35],"(SSL)":[3],"methods":[4],"learn":[5],"continuous":[6,61,126],"visual":[7,33,135],"representations":[8],"by":[9,70,110],"aligning":[10,60],"different":[11],"views":[12],"of":[13,91],"the":[14,63,71,92,104,152],"same":[15],"input,":[16],"offering":[17],"limited":[18],"control":[19],"over":[20,125],"how":[21],"information":[22,50],"is":[23,51,75],"structured":[24,96],"across":[25,116,171],"representation":[26],"dimensions.":[27],"In":[28],"this":[29,108],"work,":[30],"we":[31,150],"frame":[32],"as":[36,138,140],"a":[37,42,45,54,84,161],"discrete":[38,118,165],"communication":[39],"process":[40],"between":[41],"teacher":[43],"and":[44,133,156,163],"student":[46,64],"network,":[47],"where":[48],"semantic":[49,168],"transmitted":[52],"through":[53,77,144],"fixed-capacity":[55],"binary":[56,67,80,154],"channel.":[57],"Rather":[58],"than":[59],"features,":[62],"predicts":[65],"multi-label":[66],"messages":[68],"produced":[69],"teacher.":[72],"Discrete":[73],"agreement":[74,127],"enforced":[76],"an":[78],"element-wise":[79],"cross-entropy":[81],"objective,":[82],"while":[83],"coding-rate":[85],"regularization":[86],"term":[87],"encourages":[88],"effective":[89],"utilization":[90],"constrained":[93],"channel,":[94],"promoting":[95],"representations.":[97],"We":[98],"further":[99],"show":[100,157],"that":[101,113,158],"periodically":[102],"reinitializing":[103],"projection":[105],"head":[106],"strengthens":[107],"effect":[109],"encouraging":[111],"embeddings":[112],"remain":[114],"predictive":[115],"multiple":[117],"encodings.":[119],"Extensive":[120],"experiments":[121],"demonstrate":[122],"consistent":[123],"improvements":[124],"baselines":[128],"on":[129],"image":[130],"classification,":[131],"retrieval,":[132],"dense":[134],"prediction":[136],"tasks,":[137],"well":[139],"under":[141],"domain":[142],"shift":[143],"adaptation.":[146],"Beyond":[147],"backbone":[148],"representations,":[149],"analyze":[151],"learned":[153],"codes":[155],"they":[159],"form":[160],"compact":[162],"informative":[164],"language,":[166],"capturing":[167],"factors":[169],"reusable":[170],"classes.":[172]},"counts_by_year":[],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2026-02-12T00:00:00"}
