{"id":"https://openalex.org/W7152488006","doi":"https://doi.org/10.1145/3774904.3792727","title":"Token-level Collaborative Alignment for LLM-based Generative Recommendation","display_name":"Token-level Collaborative Alignment for LLM-based Generative Recommendation","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7152488006","doi":"https://doi.org/10.1145/3774904.3792727"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792727","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792727","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":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774904.3792727","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018111817","display_name":"Fake Lin","orcid":"https://orcid.org/0009-0003-1402-2358"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fake Lin","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0003-1402-2358","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076909486","display_name":"Binbin Hu","orcid":"https://orcid.org/0000-0002-2505-1619"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Binbin Hu","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2505-1619","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040762883","display_name":"Zhi Zheng","orcid":"https://orcid.org/0000-0001-7758-8904"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Zheng","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-7758-8904","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088880514","display_name":"X. Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xi Zhu","raw_affiliation_strings":["Rutgers University, New Brunswick, USA"],"raw_orcid":"https://orcid.org/0000-0003-3621-8493","affiliations":[{"raw_affiliation_string":"Rutgers University, New Brunswick, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114860377","display_name":"Ziqi Liu","orcid":"https://orcid.org/0000-0002-4112-3504"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziqi Liu","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4112-3504","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133308808","display_name":"Zhiqiang Zhang","orcid":"https://orcid.org/0000-0002-2321-7259"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiqiang Zhang","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2321-7259","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0001-6033-6102"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6033-6102","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025292786","display_name":"Tong Xu","orcid":"https://orcid.org/0000-0003-4246-5386"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Xu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-4246-5386","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33991016,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6909","last_page":"6919"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.6897000074386597,"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":0.6897000074386597,"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/T10028","display_name":"Topic Modeling","score":0.07039999961853027,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.02199999988079071,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.36169999837875366},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.34459999203681946},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.34049999713897705},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.2702000141143799},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.25850000977516174}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6480000019073486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49480000138282776},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27959999442100525},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.25850000977516174},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.24979999661445618},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.24899999797344208}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774904.3792727","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792727","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"}],"best_oa_location":{"id":"doi:10.1145/3774904.3792727","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792727","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":27,"referenced_works":["https://openalex.org/W2963341956","https://openalex.org/W2963367478","https://openalex.org/W2984100107","https://openalex.org/W3045200674","https://openalex.org/W3206310679","https://openalex.org/W4367694290","https://openalex.org/W4388093527","https://openalex.org/W4396606321","https://openalex.org/W4396723256","https://openalex.org/W4396758712","https://openalex.org/W4396758737","https://openalex.org/W4399794225","https://openalex.org/W4400480922","https://openalex.org/W4400525124","https://openalex.org/W4400909953","https://openalex.org/W4401834466","https://openalex.org/W4401863565","https://openalex.org/W4402502706","https://openalex.org/W4403577940","https://openalex.org/W4403814702","https://openalex.org/W4404313135","https://openalex.org/W4407571719","https://openalex.org/W4407953214","https://openalex.org/W4409671189","https://openalex.org/W4410309468","https://openalex.org/W4412394905","https://openalex.org/W4413591191"],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"demonstrated":[5],"strong":[6],"potential":[7],"for":[8,85],"generative":[9,149,200],"recommendation":[10,215],"by":[11],"leveraging":[12],"rich":[13],"semantic":[14,197],"knowledge.":[15],"However,":[16],"existing":[17],"LLM-based":[18,225],"recommender":[19,184,226],"systems":[20],"struggle":[21],"to":[22,30,61,64,72,139,192],"effectively":[23],"incorporate":[24],"collaborative":[25,156],"filtering":[26],"(CF)":[27],"signals,":[28],"due":[29],"a":[31,88,141,178,218],"fundamental":[32],"mismatch":[33],"between":[34,99],"item-level":[35,114],"preference":[36,161],"modeling":[37],"in":[38,46],"CF":[39,52,70,100,115,163,173,222],"and":[40,59,90,102,126,175,196,206,224],"token-level":[41,118],"next-token":[42],"prediction":[43],"(NTP)":[44],"optimization":[45],"LLMs.":[47],"Prior":[48],"approaches":[49],"typically":[50],"treat":[51],"as":[53],"contextual":[54],"hints":[55],"or":[56],"representation":[57],"bias,":[58],"resort":[60],"multi-stage":[62],"training":[63,153],"reduce":[65],"behavioral\u2013semantic":[66],"space":[67],"discrepancies,":[68],"leaving":[69],"unable":[71],"explicitly":[73],"regulate":[74],"LLM":[75,103,123,152,183],"generation.":[76,104],"In":[77],"this":[78],"work,":[79],"we":[80],"propose":[81],"Token-level":[82],"Collaborative":[83,109],"Alignment":[84],"Recommendation":[86],"(TCA4Rec),":[87],"model-agnostic":[89],"plug-and-play":[91],"framework":[92],"that":[93,202,211],"establishes":[94],"an":[95,189],"explicit":[96,190],"optimization-level":[97],"interface":[98],"supervision":[101,138],"TCA4Rec":[105,167,212],"consists":[106],"of":[107,151,162,181,221],"(i)":[108],"Tokenizer,":[110],"which":[111,131],"projects":[112],"raw":[113],"logits":[116],"into":[117],"distributions":[119,135],"aligned":[120],"with":[121,136,158,170],"the":[122,148],"token":[124],"space,":[125],"(ii)":[127],"Soft":[128],"Label":[129],"Alignment,":[130],"integrates":[132],"these":[133],"CF-informed":[134],"one-hot":[137],"optimize":[140],"soft":[142],"NTP":[143],"objective.":[144],"This":[145],"design":[146],"preserves":[147],"nature":[150],"while":[154],"enabling":[155],"alignment":[157,195],"essential":[159],"user":[160],"models.":[164],"We":[165],"highlight":[166],"is":[168,230],"compatible":[169],"arbitrary":[171],"traditional":[172],"models":[174,223],"generalizes":[176],"across":[177,217],"wide":[179],"range":[180],"decoder-based":[182],"architectures.":[185],"Moreover,":[186],"it":[187],"provides":[188],"mechanism":[191],"balance":[193],"behavioral":[194],"fluency,":[198],"yielding":[199],"recommendations":[201],"are":[203],"both":[204],"accurate":[205],"controllable.":[207],"Extensive":[208],"experiments":[209],"demonstrate":[210],"consistently":[213],"improves":[214],"performance":[216],"broad":[219],"spectrum":[220],"systems.":[227],"Our":[228],"code":[229],"available":[231],"at":[232],"https://github.com/critical88/TCA4Rec":[233]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-04-10T00:00:00"}
