{"id":"https://openalex.org/W7171975303","doi":"https://doi.org/10.48550/arxiv.2607.27418","title":"Context-Informed Ship Trajectory Prediction via Conditional Attention","display_name":"Context-Informed Ship Trajectory Prediction via Conditional Attention","publication_year":2026,"publication_date":"2026-07-29","ids":{"openalex":"https://openalex.org/W7171975303","doi":"https://doi.org/10.48550/arxiv.2607.27418"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.27418","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.27418","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":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.2607.27418","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101754434","display_name":"Yuan Guan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058350509","display_name":"Chandler Squires","orcid":"https://orcid.org/0000-0002-1783-2802"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Squires, Chandler","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144161086","display_name":"Timothy Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Timothy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5144095377","display_name":"Pradeep Ravikumar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ravikumar, Pradeep","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/T11622","display_name":"Maritime Navigation and Safety","score":0.9659000039100647,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T11622","display_name":"Maritime Navigation and Safety","score":0.9659000039100647,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T12126","display_name":"Maritime Transport Emissions and Efficiency","score":0.011300000362098217,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11604","display_name":"Ship Hydrodynamics and Maneuverability","score":0.003800000064074993,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/trajectory","display_name":"Trajectory","score":0.7450000047683716},{"id":"https://openalex.org/keywords/kinematics","display_name":"Kinematics","score":0.6137999892234802},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5895000100135803},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.54339998960495},{"id":"https://openalex.org/keywords/intermittency","display_name":"Intermittency","score":0.40849998593330383},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.3732999861240387},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.3628999888896942}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7450000047683716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6851000189781189},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.6137999892234802},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5895000100135803},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.54339998960495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47119998931884766},{"id":"https://openalex.org/C2780388094","wikidata":"https://www.wikidata.org/wiki/Q1666248","display_name":"Intermittency","level":3,"score":0.40849998593330383},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.3732999861240387},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.33149999380111694},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C2781147146","wikidata":"https://www.wikidata.org/wiki/Q1569795","display_name":"Sea state","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2671000063419342},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.27418","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.27418","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":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.2607.27418","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.27418","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","display_name":"Life below water","score":0.7374922037124634}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Long-term":[0],"ship":[1],"trajectory":[2,99],"prediction":[3,100,180],"is":[4,40,132,184],"a":[5,93,102,108,149],"fundamental":[6],"capability":[7],"for":[8],"maritime":[9,38],"safety":[10],"and":[11,48,64,165,174],"autonomous":[12],"navigation.":[13],"While":[14],"recent":[15],"Transformer-based":[16],"architectures":[17],"have":[18],"improved":[19],"forecasting":[20],"horizons,":[21],"they":[22],"predominantly":[23],"rely":[24],"on":[25,82,163],"historical":[26],"kinematic":[27,173],"states,":[28],"treating":[29,66],"vessel":[30,52,80,115,137],"motion":[31],"as":[32,69,101],"an":[33,197],"isolated":[34],"system.":[35],"In":[36,85],"reality,":[37],"navigation":[39],"profoundly":[41],"modulated":[42],"by":[43,50,135,177,195],"extrinsic":[44],"factors":[45],"like":[46],"weather":[47,128],"constrained":[49],"static":[51],"characteristics.":[53],"Existing":[54],"multimodal":[55],"approaches":[56],"fundamentally":[57],"model":[58],"the":[59,75,90,114,124,142],"joint":[60],"distribution":[61],"over":[62],"states":[63],"contexts,":[65],"environmental":[67,83,119],"variables":[68],"peer":[70],"features":[71],"rather":[72],"than":[73],"encoding":[74,123],"directional":[76],"physical":[77,125],"dependence":[78],"of":[79,144,199],"dynamics":[81],"conditions.":[84],"this":[86],"work,":[87],"we":[88,147],"propose":[89],"Conditional":[91,110],"Informer,":[92],"novel":[94],"encoder-decoder":[95],"architecture":[96],"that":[97,127,169],"formulates":[98],"conditional":[103],"generation":[104],"task.":[105],"We":[106],"employ":[107],"dedicated":[109],"Attention":[111],"mechanism":[112],"where":[113],"state":[116],"explicitly":[117],"queries":[118],"contexts":[120],"through":[121],"cross-attention,":[122],"prior":[126],"modulates":[129],"-":[130,136],"but":[131],"not":[133],"generated":[134],"dynamics.":[138],"Furthermore,":[139],"to":[140,154,202],"address":[141],"intermittency":[143],"real-world":[145],"data,":[146],"introduce":[148],"Modality":[150,187],"Masking":[151,188],"training":[152],"strategy":[153],"prevent":[155],"catastrophic":[156],"degradation":[157],"during":[158],"sensor":[159],"fallback.":[160],"Extensive":[161],"experiments":[162],"AIS":[164],"ERA5":[166],"data":[167],"demonstrate":[168],"our":[170],"approach":[171],"outperforms":[172],"concatenation-based":[175],"baselines":[176],"15.4%":[178],"in":[179],"accuracy":[181],"when":[182],"context":[183],"available.":[185],"Crucially,":[186],"prevents":[189],"shortcut":[190],"learning,":[191],"reducing":[192],"fallback":[193],"error":[194],"nearly":[196],"order":[198],"magnitude":[200],"compared":[201],"unconstrained":[203],"models.":[204]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-08-01T00:00:00"}
