{"id":"https://openalex.org/W7160887201","doi":"https://doi.org/10.48550/arxiv.2605.10020","title":"TrajDLM: Topology-Aware Block Diffusion Language Model for Trajectory Generation","display_name":"TrajDLM: Topology-Aware Block Diffusion Language Model for Trajectory Generation","publication_year":2026,"publication_date":"2026-05-11","ids":{"openalex":"https://openalex.org/W7160887201","doi":"https://doi.org/10.48550/arxiv.2605.10020"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.10020","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10020","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.2605.10020","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025726978","display_name":"Wilson Wongso","orcid":"https://orcid.org/0000-0003-0896-1941"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wongso, Wilson","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013214103","display_name":"Lihuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Lihuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066321379","display_name":"Arian Prabowo","orcid":"https://orcid.org/0000-0002-0459-354X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prabowo, Arian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102676496","display_name":"Xiachong Lin","orcid":"https://orcid.org/0009-0009-6762-8365"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Xiachong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135929609","display_name":"Baiyu Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Baiyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135993649","display_name":"Hao Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5090893421","display_name":"Flora D. Salim","orcid":"https://orcid.org/0000-0002-1237-1664"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salim, Flora D.","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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.18880000710487366,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.18880000710487366,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.07810000330209732,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11106","display_name":"Data Management and Algorithms","score":0.07569999992847443,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/trajectory","display_name":"Trajectory","score":0.758899986743927},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6463000178337097},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5385000109672546},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5227000117301941},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.49779999256134033},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.4674000144004822},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.46619999408721924},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.43709999322891235},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4239000082015991}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.758899986743927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7174999713897705},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6463000178337097},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5385000109672546},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5227000117301941},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.49779999256134033},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.46619999408721924},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.448199987411499},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.43709999322891235},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4239000082015991},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.41179999709129333},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4004000127315521},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.35530000925064087},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.35120001435279846},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3294000029563904},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.31279999017715454},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.299699991941452},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2793000042438507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.273499995470047},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.26159998774528503}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.10020","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10020","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.2605.10020","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10020","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":[{"score":0.8226101398468018,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generating":[0],"high-fidelity":[1],"synthetic":[2],"GPS":[3],"trajectories":[4,85],"is":[5,170],"increasingly":[6],"important":[7],"for":[8,97],"applications":[9],"in":[10],"transportation,":[11],"urban":[12],"planning,":[13],"and":[14,37,107,113,138,164],"what-if":[15],"scenario":[16],"simulation,":[17],"especially":[18],"as":[19,86,158],"privacy":[20],"concerns":[21],"limit":[22],"access":[23],"to":[24,39,110,132,162],"real-world":[25],"mobility":[26],"data.":[27],"Existing":[28],"trajectory":[29,70,166],"generation":[30,47,63,71],"models":[31,78,84],"face":[32],"a":[33,68,93,103,159],"trade-off":[34],"between":[35],"efficiency":[36],"faithfulness":[38],"road":[40,51,90,104],"network":[41,105],"topology:":[42],"continuous-space":[43],"methods":[44],"enable":[45],"fast":[46],"but":[48],"ignore":[49],"the":[50,152],"network,":[52],"while":[53,129],"topology-aware":[54,69,100],"approaches":[55],"rely":[56],"on":[57,74,124],"search-based":[58],"autoregressive":[59],"decoding":[60],"that":[61,79],"limits":[62],"speed.":[64],"We":[65],"propose":[66],"TrajDLM,":[67],"framework":[72],"based":[73],"block":[75,94],"diffusion":[76,95,157],"language":[77],"bridges":[80],"this":[81],"gap.":[82],"TrajDLM":[83,120],"sequences":[87],"of":[88,154],"discrete":[89,156],"segments,":[91],"combining":[92],"backbone":[96],"efficient":[98,165],"denoising,":[99],"embeddings":[101],"from":[102],"encoder,":[106],"topology-constrained":[108],"sampling":[109],"ensure":[111],"coherent":[112],"realistic":[114],"trajectories.":[115],"Across":[116],"three":[117],"city-scale":[118],"datasets,":[119],"achieves":[121],"strong":[122,140],"performance":[123],"fine-grained":[125],"local":[126],"similarity":[127],"metrics":[128],"being":[130],"up":[131],"$2.8\\times$":[133],"faster":[134],"than":[135],"prior":[136],"work,":[137],"demonstrates":[139],"zero-shot":[141],"transfer":[142],"across":[143],"domains,":[144],"including":[145],"unseen":[146],"transportation":[147],"modes.":[148],"These":[149],"results":[150],"highlight":[151],"effectiveness":[153],"block-wise":[155],"scalable":[160],"approach":[161],"accurate":[163],"generation.":[167],"Our":[168],"code":[169],"available":[171],"at":[172],"https://github.com/cruiseresearchgroup/TrajDLM/":[173]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-13T00:00:00"}
