{"id":"https://openalex.org/W7157192524","doi":"https://doi.org/10.48550/arxiv.2604.23578","title":"LLMs Reading the Rhythms of Daily Life: Aligned Understanding for Behavior Prediction and Generation","display_name":"LLMs Reading the Rhythms of Daily Life: Aligned Understanding for Behavior Prediction and Generation","publication_year":2026,"publication_date":"2026-04-26","ids":{"openalex":"https://openalex.org/W7157192524","doi":"https://doi.org/10.48550/arxiv.2604.23578"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.23578","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23578","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":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.2604.23578","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088412858","display_name":"Fanjin Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meng, Fanjin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134766980","display_name":"Jingtao Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Jingtao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134795254","display_name":"Nian Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Nian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134801856","display_name":"Yizhou Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Yizhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134749770","display_name":"Yong Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yong","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/T10028","display_name":"Topic Modeling","score":0.21930000185966492,"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/T10028","display_name":"Topic Modeling","score":0.21930000185966492,"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":0.16349999606609344,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.09139999747276306,"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/flexibility","display_name":"Flexibility (engineering)","score":0.6444000005722046},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.5855000019073486},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5741000175476074},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48910000920295715},{"id":"https://openalex.org/keywords/human-behavior","display_name":"Human behavior","score":0.44859999418258667},{"id":"https://openalex.org/keywords/behavioral-pattern","display_name":"Behavioral pattern","score":0.4108999967575073},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.3831000030040741},{"id":"https://openalex.org/keywords/behavior-change","display_name":"Behavior change","score":0.3824000060558319},{"id":"https://openalex.org/keywords/pearl","display_name":"Pearl","score":0.3653999865055084}],"concepts":[{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6444000005722046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6295999884605408},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.5855000019073486},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5741000175476074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5618000030517578},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48910000920295715},{"id":"https://openalex.org/C117035363","wikidata":"https://www.wikidata.org/wiki/Q3769299","display_name":"Human behavior","level":2,"score":0.44859999418258667},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.415800005197525},{"id":"https://openalex.org/C83804111","wikidata":"https://www.wikidata.org/wiki/Q1063558","display_name":"Behavioral pattern","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C14262774","wikidata":"https://www.wikidata.org/wiki/Q4880695","display_name":"Behavior change","level":2,"score":0.3824000060558319},{"id":"https://openalex.org/C2779251273","wikidata":"https://www.wikidata.org/wiki/Q43436","display_name":"Pearl","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.3628999888896942},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3621000051498413},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.34049999713897705},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33559998869895935},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3230000138282776},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3163999915122986},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C2989277270","wikidata":"https://www.wikidata.org/wiki/Q168338","display_name":"Behavioral analysis","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C2776230583","wikidata":"https://www.wikidata.org/wiki/Q1322198","display_name":"Spoken language","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2761000096797943},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2648000121116638},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2639000117778778},{"id":"https://openalex.org/C135343436","wikidata":"https://www.wikidata.org/wiki/Q170406","display_name":"Rhythm","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.23578","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23578","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:10.48550/arxiv.2604.23578","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23578","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.8496819138526917,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Human":[0],"daily":[1],"behavior":[2,36,40,113,127,176],"unfolds":[3],"as":[4,23,129],"complex":[5,174],"sequences":[6],"shaped":[7],"by":[8],"intentions,":[9],"preferences,":[10],"and":[11,26,35,51,74,80,86,132,147,168],"context.":[12],"Effectively":[13],"modeling":[14,114],"these":[15],"behaviors":[16],"is":[17],"crucial":[18],"for":[19],"intelligent":[20],"systems":[21],"such":[22],"personal":[24],"assistants":[25],"recommendation":[27],"engines.":[28],"While":[29],"recent":[30],"advances":[31],"in":[32,45,162,170],"deep":[33],"learning":[34,119],"pre-training":[37],"have":[38],"improved":[39],"prediction,":[41],"key":[42],"challenges":[43],"remain--particularly":[44],"handling":[46],"long-tail":[47],"behaviors,":[48],"enhancing":[49],"interpretability,":[50,73],"supporting":[52],"multiple":[53],"tasks":[54],"within":[55],"a":[56,64,105,116,137,141],"unified":[57],"framework.":[58],"Large":[59],"language":[60,88],"models":[61,128],"(LLMs)":[62],"offer":[63],"promising":[65],"direction":[66],"due":[67],"to":[68,173],"their":[69],"semantic":[70],"richness,":[71],"strong":[72],"generative":[75],"capabilities.":[76,149],"However,":[77],"the":[78,90,134],"structural":[79],"modal":[81],"differences":[82],"between":[83],"behavioral":[84],"data":[85],"natural":[87],"limit":[89],"direct":[91],"applicability":[92],"of":[93],"LLMs.":[94],"To":[95],"address":[96],"this":[97],"gap,":[98],"we":[99],"propose":[100],"Behavior":[101],"Understanding":[102],"Alignment":[103],"(BUA),":[104],"novel":[106],"framework":[107],"that":[108,156],"integrates":[109],"LLMs":[110,172],"into":[111],"human":[112,175],"through":[115,136],"structured":[117],"curriculum":[118],"process.":[120],"BUA":[121,157],"employs":[122],"sequence":[123],"embeddings":[124],"from":[125],"pretrained":[126],"alignment":[130],"anchors":[131],"guides":[133],"LLM":[135],"three-stage":[138],"curriculum,":[139],"while":[140],"multi-round":[142],"dialogue":[143],"setting":[144],"introduces":[145],"prediction":[146],"generation":[148],"Experiments":[150],"on":[151],"two":[152],"real-world":[153],"datasets":[154],"demonstrate":[155],"significantly":[158],"outperforms":[159],"existing":[160],"methods":[161],"both":[163],"tasks,":[164],"highlighting":[165],"its":[166],"effectiveness":[167],"flexibility":[169],"applying":[171],"modeling.":[177]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-29T00:00:00"}