{"id":"https://openalex.org/W7133363494","doi":"https://doi.org/10.48550/arxiv.2603.01926","title":"MealRec: Multi-granularity Sequential Modeling via Hierarchical Diffusion Models for Micro-Video Recommendation","display_name":"MealRec: Multi-granularity Sequential Modeling via Hierarchical Diffusion Models for Micro-Video Recommendation","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133363494","doi":"https://doi.org/10.48550/arxiv.2603.01926"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01926","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01926","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.2603.01926","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101230092","display_name":"Xinxin Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Xinxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006833163","display_name":"Haokai Ma","orcid":"https://orcid.org/0000-0002-4621-5213"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Haokai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018130955","display_name":"Yuze Zheng","orcid":"https://orcid.org/0009-0003-5718-8366"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Yuze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065702080","display_name":"Yongfu Zha","orcid":"https://orcid.org/0000-0002-3053-8640"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zha, Yongfu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127931583","display_name":"Yonghui Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yonghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127997739","display_name":"Xiaodong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiaodong","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/T10203","display_name":"Recommender Systems and Techniques","score":0.6177999973297119,"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":0.6177999973297119,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.0681999996304512,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.05939999967813492,"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/robustness","display_name":"Robustness (evolution)","score":0.6169999837875366},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.6152999997138977},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5426999926567078},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.47780001163482666},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.45350000262260437},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.42800000309944153},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.41780000925064087},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3578999936580658}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.805400013923645},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6169999837875366},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.6152999997138977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5454000234603882},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5426999926567078},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.47780001163482666},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.45350000262260437},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.42800000309944153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41999998688697815},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3847000002861023},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3578999936580658},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3476000130176544},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.34209999442100525},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.33090001344680786},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3021000027656555},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.30000001192092896},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01926","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01926","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.2603.01926","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01926","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Micro-video":[0],"recommendation":[1],"aims":[2],"to":[3,68,120,132,154],"capture":[4],"user":[5,157],"preferences":[6,158],"from":[7,107,159,174],"the":[8,14,19,28,40,141,149,163,178,188],"collaborative":[9,130],"and":[10,34,44,58,76,109,128,168,181,195,200],"context":[11],"information":[12],"of":[13,183,191],"interacted":[15],"micro-videos,":[16],"thereby":[17],"predicting":[18],"appropriate":[20],"videos.":[21],"This":[22],"target":[23],"is":[24],"often":[25],"hindered":[26],"by":[27],"inherent":[29,77],"noise":[30],"within":[31],"multimodal":[32,60],"content":[33,135],"unreliable":[35],"implicit":[36],"feedback,":[37],"which":[38,99],"weakens":[39],"correspondence":[41],"between":[42],"behaviors":[43],"underlying":[45],"interests.":[46],"While":[47],"conventional":[48],"works":[49],"have":[50],"predominantly":[51],"approached":[52],"such":[53],"scenario":[54],"through":[55],"behavior-augmented":[56],"modeling":[57,89,106],"content-centric":[59],"analysis,":[61],"these":[62,82],"paradigms":[63],"can":[64],"inadvertently":[65],"give":[66],"rise":[67],"two":[69,175],"non-trivial":[70],"challenges:":[71],"preference-irrelative":[72],"video":[73,122],"representation":[74],"extraction":[75],"modality":[78],"conflicts.":[79],"To":[80,139],"address":[81],"issues,":[83],"we":[84,113,146],"propose":[85,115],"a":[86],"Multi-granularity":[87],"sequential":[88],"method":[90],"via":[91],"hierarchical":[92],"diffusion":[93],"models":[94],"for":[95],"micro-video":[96,172],"Recommendation":[97],"(MealRec),":[98],"simultaneously":[100],"considers":[101],"temporal":[102,126],"correlations":[103],"during":[104],"preference":[105,144],"intra-":[108],"inter-video":[110],"perspectives.":[111],"Specifically,":[112],"first":[114],"Temporal-guided":[116],"Content":[117],"Diffusion":[118],"(TCD)":[119],"refine":[121],"representations":[123],"under":[124,162],"intra-video":[125],"guidance":[127],"personalized":[129],"signals":[131],"emphasize":[133],"salient":[134],"while":[136],"suppressing":[137],"redundancy.":[138],"achieve":[140],"semantically":[142],"coherent":[143],"modeling,":[145],"further":[147,186],"design":[148],"Noise-unconditional":[150],"Preference":[151],"Denoising":[152],"(NPD)":[153],"recovers":[155],"informative":[156],"corrupted":[160],"states":[161],"blind":[164],"denoising.":[165],"Extensive":[166],"experiments":[167],"analyses":[169],"on":[170],"four":[171],"datasets":[173],"platforms":[176],"demonstrate":[177],"effectiveness,":[179],"universality,":[180],"robustness":[182],"our":[184,192],"MealRec,":[185],"uncovering":[187],"effective":[189],"mechanism":[190],"proposed":[193],"TCD":[194],"NPD.":[196],"The":[197],"source":[198],"code":[199],"corresponding":[201],"dataset":[202],"will":[203],"be":[204],"available":[205],"upon":[206],"acceptance.":[207]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-04T00:00:00"}