{"id":"https://openalex.org/W7165651349","doi":"https://doi.org/10.48550/arxiv.2606.21670","title":"Improving Text-to-Music Generation with Human Preference Rewards","display_name":"Improving Text-to-Music Generation with Human Preference Rewards","publication_year":2026,"publication_date":"2026-06-19","ids":{"openalex":"https://openalex.org/W7165651349","doi":"https://doi.org/10.48550/arxiv.2606.21670"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.21670","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21670","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.2606.21670","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139172794","display_name":"Yonghyun Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Yonghyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139194363","display_name":"Junwon Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Junwon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068990851","display_name":"Haiwen Xia","orcid":"https://orcid.org/0000-0002-0396-5882"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Haiwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139136658","display_name":"Yinghao Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Yinghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5019674079","display_name":"Chris Donahue","orcid":"https://orcid.org/0009-0007-6825-6327"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Donahue, Chris","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/T11309","display_name":"Music and Audio Processing","score":0.623199999332428,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.623199999332428,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11349","display_name":"Music Technology and Sound Studies","score":0.09309999644756317,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.05860000103712082,"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/conditioning","display_name":"Conditioning","score":0.7608000040054321},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5791000127792358},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.42719998955726624},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.39579999446868896},{"id":"https://openalex.org/keywords/preference-learning","display_name":"Preference learning","score":0.3799999952316284},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.37940001487731934},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.32030001282691956},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.2939999997615814}],"concepts":[{"id":"https://openalex.org/C45262634","wikidata":"https://www.wikidata.org/wiki/Q5159291","display_name":"Conditioning","level":2,"score":0.7608000040054321},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5791000127792358},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5080000162124634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48420000076293945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45019999146461487},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.42719998955726624},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.39579999446868896},{"id":"https://openalex.org/C181204326","wikidata":"https://www.wikidata.org/wiki/Q7239820","display_name":"Preference learning","level":3,"score":0.3799999952316284},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.30970001220703125},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.30820000171661377},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3068999946117401},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.28839999437332153},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.27869999408721924},{"id":"https://openalex.org/C2778054375","wikidata":"https://www.wikidata.org/wiki/Q203973","display_name":"Conjoint analysis","level":3,"score":0.2718999981880188},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C2776543023","wikidata":"https://www.wikidata.org/wiki/Q2147046","display_name":"Rework","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C39617858","wikidata":"https://www.wikidata.org/wiki/Q212737","display_name":"Classical conditioning","level":3,"score":0.25209999084472656},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.21670","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21670","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.2606.21670","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21670","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":0.5912027955055237,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"describe":[1],"our":[2],"entry":[3],"to":[4],"the":[5,9,19,105,148,151,159,166,169],"efficiency":[6],"track":[7],"of":[8,168],"Academic":[10],"Text-to-Music":[11],"(ATTM)":[12],"Grand":[13],"Challenge":[14],"at":[15,69,74],"ICME":[16],"2026.":[17],"Beyond":[18],"challenge":[20],"protocol's":[21],"FAD-CLAP":[22],"and":[23,52,72,96,117,126,158],"CLAP":[24],"score,":[25],"we":[26],"add":[27],"a":[28,34,48,54,64,88,109,141],"learned":[29],"human-preference":[30],"reward":[31,44,78,138],"from":[32],"TuneJury,":[33],"twin":[35],"pairwise":[36],"ranker":[37],"trained":[38],"over":[39,90],"open":[40],"music-preference":[41],"datasets.":[42],"The":[43,57],"serves":[45],"both":[46],"as":[47,53,82,140,147],"training-time":[49,77,137],"conditioning":[50,79,139,143],"signal":[51],"sample-selection":[55],"criterion.":[56],"pipeline":[58],"combines":[59],"five":[60,91],"engineering":[61],"decisions":[62],"on":[63,104,131],"120M-parameter":[65],"FluxAudio-S":[66],"backbone,":[67],"four":[68],"training":[70,95],"time":[71],"one":[73],"inference:":[75],"(i)":[76],"that":[80],"doubles":[81],"an":[83],"inference-time":[84,160],"CFG":[85],"axis,":[86,144],"(ii)":[87],"sweep":[89],"score-conditioning":[92],"architectures,":[93],"where":[94],"inference":[97,119],"use":[98],"different":[99],"variants,":[100],"(iii)":[101],"expert":[102,145],"iteration":[103,146],"top":[106],"decile,":[107],"(iv)":[108],"short":[110],"preference-tuning":[111,152],"pass":[112,153],"(CRPO)":[113],"for":[114],"audio-text":[115],"alignment,":[116],"(v)":[118],"post-processing":[120],"via":[121],"joint":[122],"CFG,":[123],"source":[124],"separation,":[125],"loudness":[127],"normalization.":[128],"Per-stage":[129],"decomposition":[130],"100":[132],"Song":[133],"Describer":[134],"prompts":[135],"shows":[136],"functional":[142],"dominant":[149],"contributor,":[150],"adding":[154],"only":[155],"noise-level":[156],"gain,":[157],"score":[161],"scalar":[162],"already":[163],"saturated":[164],"by":[165],"end":[167],"chain.":[170]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}