{"id":"https://openalex.org/W7166666655","doi":"https://doi.org/10.48550/arxiv.2606.29970","title":"From Extraction to Navigation: Progressive Retrieval with Indirectly Infinite Depth","display_name":"From Extraction to Navigation: Progressive Retrieval with Indirectly Infinite Depth","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166666655","doi":"https://doi.org/10.48550/arxiv.2606.29970"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.29970","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29970","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.29970","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5099471492","display_name":"Linxiao Che","orcid":"https://orcid.org/0009-0001-5587-6427"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Che, Linxiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043900893","display_name":"Sicong Huang","orcid":"https://orcid.org/0000-0003-0854-4734"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Shanshan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029653356","display_name":"H\u00fcseyin Ozan \u04aairkino\u011flu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Haitao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122849802","display_name":"Yijia Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Yijia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139695566","display_name":"Qiang Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Qiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139710253","display_name":"Ruiming Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Ruiming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139682396","display_name":"Han Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Han","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139670035","display_name":"Kun Gai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gai, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139690901","display_name":"Guorui Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Guorui","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/T11273","display_name":"Advanced Graph Neural Networks","score":0.8335000276565552,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.8335000276565552,"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":0.039400000125169754,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.032999999821186066,"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/tree-traversal","display_name":"Tree traversal","score":0.6107000112533569},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5367000102996826},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5198000073432922},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.516700029373169},{"id":"https://openalex.org/keywords/stateful-firewall","display_name":"Stateful firewall","score":0.4124000072479248},{"id":"https://openalex.org/keywords/graph-traversal","display_name":"Graph traversal","score":0.37220001220703125},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.3517000079154968},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.3330000042915344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7523000240325928},{"id":"https://openalex.org/C140745168","wikidata":"https://www.wikidata.org/wiki/Q1210082","display_name":"Tree traversal","level":2,"score":0.6107000112533569},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5367000102996826},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5198000073432922},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.516700029373169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4343999922275543},{"id":"https://openalex.org/C22927095","wikidata":"https://www.wikidata.org/wiki/Q1784206","display_name":"Stateful firewall","level":3,"score":0.4124000072479248},{"id":"https://openalex.org/C96333769","wikidata":"https://www.wikidata.org/wiki/Q907955","display_name":"Graph traversal","level":3,"score":0.37220001220703125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3662000000476837},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32339999079704285},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3109000027179718},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C48903430","wikidata":"https://www.wikidata.org/wiki/Q491370","display_name":"Graph partition","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C551230270","wikidata":"https://www.wikidata.org/wiki/Q4368942","display_name":"Data retrieval","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27950000762939453},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C831591","wikidata":"https://www.wikidata.org/wiki/Q59750","display_name":"Bidirectional search","level":5,"score":0.2572000026702881},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.29970","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29970","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.29970","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29970","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":"Preprint"},"sustainable_development_goals":[{"score":0.5976564288139343,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"large-scale":[1],"recommender":[2],"retrieval":[3,16,41,74,155,177,183],"is":[4],"shifting":[5,59],"from":[6,43],"static":[7,49],"similarity":[8],"matching":[9],"to":[10,33,57,139],"dynamic":[11],"item":[12],"space":[13],"navigation,":[14],"framing":[15],"as":[17,75],"iterative":[18],"goal-driven":[19],"graph":[20,54,78,121,135],"traversal.":[21],"Conventional":[22],"item-to-item":[23],"(i2i)":[24],"methods":[25],"fall":[26],"into":[27],"the":[28,65],"\"interest":[29],"tunnel\"":[30],"and":[31,52,171],"fail":[32],"excavate":[34],"deep":[35,176],"user":[36,61],"interests,":[37],"while":[38],"existing":[39],"index-based":[40],"suffers":[42],"persistent":[44],"\"search":[45],"drift\",":[46],"caused":[47],"by":[48,98],"entry":[50],"nodes":[51],"fixed":[53],"topologies":[55],"unable":[56],"track":[58],"real-time":[60],"intent.":[62],"To":[63],"resolve":[64],"above":[66],"defects,":[67],"we":[68],"present":[69],"IID-Nav,":[70],"a":[71,99],"framework":[72],"modeling":[73],"stateful":[76],"autonomous":[77],"exploration":[79],"with":[80,93,134],"three":[81],"core":[82],"contributions:":[83],"(1)":[84],"A":[85,103,129],"goal-aware":[86],"navigation":[87,144],"policy":[88],"substituting":[89],"passive":[90],"neighborhood":[91],"expansion":[92],"active":[94],"intent":[95],"routing":[96],"supervised":[97],"target":[100],"discriminator;":[101],"(2)":[102],"recursive":[104],"state":[105,115],"evolution":[106],"mechanism":[107],"supporting":[108],"Indirectly":[109],"Infinite":[110],"Depth":[111],"(IID)":[112],"via":[113],"cross-request":[114],"reuse,":[116],"which":[117],"enables":[118],"logical":[119],"unlimited-depth":[120],"traversal":[122],"without":[123],"linearly":[124],"rising":[125],"inference":[126],"latency;":[127],"(3)":[128],"trajectory-aligned":[130],"training":[131],"paradigm":[132],"equipped":[133],"hard":[136],"negative":[137],"sampling":[138],"stabilize":[140],"optimization":[141],"over":[142],"full":[143],"paths.":[145],"Evaluations":[146],"on":[147],"billion-level":[148],"industrial":[149,186],"datasets":[150],"show":[151],"IID-Nav":[152],"surpasses":[153],"mainstream":[154],"baselines":[156],"under":[157],"strict":[158],"latency":[159],"budgets.":[160],"Empirical":[161],"results":[162],"verify":[163],"that":[164],"our":[165],"method":[166],"alleviates":[167],"search":[168],"drift":[169],"remarkably":[170],"retains":[172],"high":[173],"precision":[174],"for":[175,185],"paths,":[178],"offering":[179],"an":[180],"efficient,":[181],"robust":[182],"solution":[184],"recommendation":[187],"systems.":[188]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}