{"id":"https://openalex.org/W7160234830","doi":"https://doi.org/10.48550/arxiv.2605.01759","title":"PointCSP: Cross-Sample Semantic Propagation and Stability Preservation in Self-Supervised Point Cloud Learning","display_name":"PointCSP: Cross-Sample Semantic Propagation and Stability Preservation in Self-Supervised Point Cloud Learning","publication_year":2026,"publication_date":"2026-05-03","ids":{"openalex":"https://openalex.org/W7160234830","doi":"https://doi.org/10.48550/arxiv.2605.01759"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.01759","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01759","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.2605.01759","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129731551","display_name":"Xinxing Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Xinxing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087070904","display_name":"Ajian Liu","orcid":"https://orcid.org/0009-0009-5238-0387"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Ajian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042422660","display_name":"Sunyuan Qiang","orcid":"https://orcid.org/0000-0001-5298-5815"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiang, Sunyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135347324","display_name":"Hui Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Hui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135323193","display_name":"Liying Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Liying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135415129","display_name":"Yuzhong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuzhong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135334615","display_name":"Zhi Rao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rao, Zhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135417282","display_name":"Yanyan Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Yanyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9294999837875366,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9294999837875366,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.009399999864399433,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.006599999964237213,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/semantic-computing","display_name":"Semantic computing","score":0.6047999858856201},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5759999752044678},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5485000014305115},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.5005000233650208},{"id":"https://openalex.org/keywords/semantic-grid","display_name":"Semantic grid","score":0.49549999833106995},{"id":"https://openalex.org/keywords/semantic-data-model","display_name":"Semantic data model","score":0.47620001435279846},{"id":"https://openalex.org/keywords/semantic-compression","display_name":"Semantic compression","score":0.4474000036716461},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.41929998993873596},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.3871000111103058}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8325999975204468},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.6047999858856201},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5759999752044678},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5485000014305115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5346999764442444},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.5005000233650208},{"id":"https://openalex.org/C103692084","wikidata":"https://www.wikidata.org/wiki/Q1765824","display_name":"Semantic grid","level":3,"score":0.49549999833106995},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.47620001435279846},{"id":"https://openalex.org/C202708506","wikidata":"https://www.wikidata.org/wiki/Q7449050","display_name":"Semantic compression","level":5,"score":0.4474000036716461},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.41929998993873596},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35989999771118164},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.35109999775886536},{"id":"https://openalex.org/C2778180026","wikidata":"https://www.wikidata.org/wiki/Q18378163","display_name":"Semantic heterogeneity","level":4,"score":0.35100001096725464},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3427000045776367},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.3346000015735626},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.2994000017642975},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C6881194","wikidata":"https://www.wikidata.org/wiki/Q7449091","display_name":"Semantic technology","level":4,"score":0.2574000060558319},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.01759","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01759","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.2605.01759","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01759","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":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5024795532226562}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Scene-level":[0],"point":[1],"cloud":[2],"self-supervised":[3],"learning":[4],"(PC-SSL)":[5],"has":[6],"demonstrated":[7],"potential":[8],"in":[9,21,35,71,102,114,204],"enhancing":[10],"the":[11,19,22,27,47,97,103,107,115,177],"generalization":[12],"capability":[13],"of":[14,37,49,145,161],"3D":[15],"vision":[16],"models.":[17],"Despite":[18],"advances":[20],"field":[23],"through":[24,164],"existing":[25],"methods,":[26],"sample-independent":[28],"modeling":[29],"paradigm":[30],"still":[31],"poses":[32],"significant":[33],"limitations":[34],"terms":[36],"maintaining":[38],"consistent":[39],"semantic":[40,54,68,90,112,121,135,146,171,182,208],"representations":[41],"across":[42,100],"scenes.":[43],"This":[44,93,175],"challenge":[45],"hinders":[46],"construction":[48],"a":[50,62,75,85,165,170],"unified":[51],"and":[52,82,118,148,169,184,207],"transferable":[53],"space.":[55],"To":[56],"address":[57],"this":[58],"issue,":[59],"we":[60,130],"propose":[61],"PC-SSL":[63],"framework":[64],"based":[65],"on":[66,192],"cross-sample":[67,111],"propagation":[69],"(CSP),":[70],"which":[72],"samples":[73,101],"within":[74],"batch":[76,153],"are":[77],"serialized":[78],"into":[79],"continuous":[80],"input":[81,128,167],"processed":[83],"by":[84,152],"state-space":[86],"model":[87,178],"to":[88,109,141,179],"enable":[89],"state":[91,104],"propagation.":[92],"mechanism":[94,168],"explicitly":[95],"models":[96],"dynamic":[98],"dependencies":[99],"space,":[105],"allowing":[106],"network":[108],"establish":[110],"consistency":[113,183],"latent":[116],"space":[117],"achieve":[119,142],"global":[120],"alignment.":[122],"Since":[123],"serialization-based":[124],"pretraining":[125],"requires":[126],"batch-level":[127],"organization,":[129],"further":[131],"introduce":[132],"an":[133],"asymmetric":[134],"preservation":[136],"distillation":[137],"(SPD)":[138],"during":[139],"finetuning":[140],"structural":[143],"alignment":[144,173],"transfer":[147,160],"eliminate":[149],"inconsistencies":[150],"caused":[151],"dependency.":[154],"The":[155],"proposed":[156],"SPD":[157],"ensures":[158],"stable":[159],"pretrained":[162],"semantics":[163],"heterogeneous":[166],"feature":[172],"constraint.":[174],"enables":[176],"maintain":[180],"structured":[181],"robustness":[185],"under":[186],"single-scene":[187],"testing":[188],"conditions.":[189],"Extensive":[190],"experiments":[191],"multiple":[193],"benchmark":[194],"datasets":[195],"demonstrate":[196],"that":[197],"our":[198],"method":[199],"consistently":[200],"outperforms":[201],"state-of-the-art":[202],"methods":[203],"both":[205],"performance":[206],"consistency.":[209]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-06T00:00:00"}
