{"id":"https://openalex.org/W4417466219","doi":"https://doi.org/10.1145/3774904.3792907","title":"DTRec: Learning Dynamic Reasoning Trajectories for Sequential Recommendation","display_name":"DTRec: Learning Dynamic Reasoning Trajectories for Sequential Recommendation","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W4417466219","doi":"https://doi.org/10.1145/3774904.3792907"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792907","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792907","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774904.3792907","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yifan Shao","orcid":"https://orcid.org/0009-0001-5745-7621"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yifan Shao","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0009-0001-5745-7621","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Peilin Zhou","orcid":"https://orcid.org/0000-0001-6763-5236"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peilin Zhou","raw_affiliation_strings":["Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6763-5236","affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082317196","display_name":"Shoujin Wang","orcid":"https://orcid.org/0000-0003-1133-9379"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shoujin Wang","raw_affiliation_strings":["University of Technology Sydney, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0003-1133-9379","affiliations":[{"raw_affiliation_string":"University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Weizhi Zhang","orcid":"https://orcid.org/0000-0003-4067-7588"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weizhi Zhang","raw_affiliation_strings":["University of Illinois Chicago, Chicago, Illinois, USA"],"raw_orcid":"https://orcid.org/0000-0003-4067-7588","affiliations":[{"raw_affiliation_string":"University of Illinois Chicago, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sunghun Kim","orcid":"https://orcid.org/0000-0003-4478-9720"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sunghun Kim","raw_affiliation_strings":["Hong Kong University of Science and Technology, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0003-4478-9720","affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology, Hong Kong, China","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xu Cai","orcid":"https://orcid.org/0009-0000-5477-4931"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Cai","raw_affiliation_strings":["Jilin University, Changchun, China"],"raw_orcid":"https://orcid.org/0009-0000-5477-4931","affiliations":[{"raw_affiliation_string":"Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8549","last_page":"8552"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.8690999746322632,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.8690999746322632,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.02810000069439411,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.013399999588727951,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5552999973297119},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5313000082969666},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.3840000033378601},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.3806000053882599},{"id":"https://openalex.org/keywords/case-based-reasoning","display_name":"Case-based reasoning","score":0.3801000118255615},{"id":"https://openalex.org/keywords/model-based-reasoning","display_name":"Model-based reasoning","score":0.3646000027656555}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8130000233650208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5763999819755554},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5552999973297119},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5313000082969666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46779999136924744},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3840000033378601},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.3801000118255615},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.3646000027656555},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.3303999900817871},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.2775999903678894}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3774904.3792907","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792907","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2512.14036","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.14036","pdf_url":"https://arxiv.org/pdf/2512.14036","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.14036","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.14036","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1145/3774904.3792907","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792907","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Inspired":[0],"by":[1,27,163,195],"advances":[2],"in":[3],"LLMs,":[4],"reasoning-enhanced":[5],"sequential":[6],"recommendation":[7],"performs":[8],"multi-step":[9],"deliberation":[10],"before":[11],"making":[12],"final":[13],"predictions,":[14],"unlocking":[15],"greater":[16],"potential":[17],"for":[18,34,110],"capturing":[19],"user":[20,39],"preferences.":[21],"However,":[22],"current":[23],"methods":[24],"are":[25,32],"constrained":[26],"static":[28,49],"reasoning":[29,50,66,108,161],"trajectories":[30],"that":[31,104,155],"ill-suited":[33],"the":[35,71,106,120,135,145,149,158,175],"diverse":[36],"complexity":[37],"of":[38,79,139,160,177],"behaviors.":[40],"They":[41],"suffer":[42],"from":[43],"two":[44],"key":[45],"limitations:":[46],"(1)":[47],"a":[48,64,99,183],"direction,":[51,121],"which":[52,68,128],"uses":[53],"flat":[54],"supervision":[55],"signals":[56,132],"misaligned":[57],"with":[58],"human-like":[59],"hierarchical":[60],"reasoning,":[61],"and":[62,88,101,116],"(2)":[63],"fixed":[65],"depth,":[67,146],"inefficiently":[69],"applies":[70],"same":[72],"computational":[73,90,193],"effort":[74],"to":[75,85,133,182,197],"all":[76],"users,":[77],"regardless":[78],"pattern":[80],"complexity.":[81],"These":[82],"rigidity":[83],"lead":[84],"suboptimal":[86],"performance":[87,185],"significant":[89],"waste.":[91],"To":[92,118,143],"overcome":[93],"these":[94],"challenges,":[95],"we":[96,122,147],"propose":[97],"DTRec,":[98],"novel":[100],"effective":[102],"framework":[103],"explores":[105],"Dynamic":[107],"Trajectory":[109],"Sequential":[111],"Recommendation":[112],"along":[113],"both":[114],"direction":[115],"depth.":[117],"guide":[119],"develop":[123],"Hierarchical":[124],"Process":[125],"Supervision":[126],"(HPS),":[127],"provides":[129],"coarse-to-fine":[130],"supervisory":[131],"emulate":[134],"natural,":[136],"progressive":[137],"refinement":[138],"human":[140],"cognitive":[141],"processes.":[142],"optimize":[144],"introduce":[148],"Adaptive":[150],"Reasoning":[151],"Halting":[152],"(ARH)":[153],"mechanism":[154],"dynamically":[156],"adjusts":[157],"number":[159],"steps":[162],"jointly":[164],"monitoring":[165],"three":[166,171],"indicators.":[167],"Extensive":[168],"experiments":[169],"on":[170],"real-world":[172],"datasets":[173],"demonstrate":[174],"superiority":[176],"our":[178],"approach,":[179],"achieving":[180],"up":[181,196],"24.5%":[184],"improvement":[186],"over":[187],"strong":[188],"baselines":[189],"while":[190],"simultaneously":[191],"reducing":[192],"cost":[194],"41.6%.":[198]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-12-18T00:00:00"}