{"id":"https://openalex.org/W7163407145","doi":"https://doi.org/10.48550/arxiv.2606.03116","title":"AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following","display_name":"AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163407145","doi":"https://doi.org/10.48550/arxiv.2606.03116"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.03116","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03116","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.2606.03116","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137724049","display_name":"Haitao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haitao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101667381","display_name":"Tian Tan","orcid":"https://orcid.org/0000-0002-4723-0044"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Tian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137782019","display_name":"Yuguang Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yuguang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137745785","display_name":"Shan Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Shan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137750408","display_name":"Xie Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xie","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":0.21649999916553497,"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":0.21649999916553497,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.11079999804496765,"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/T11349","display_name":"Music Technology and Sound Studies","score":0.08160000294446945,"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/benchmark","display_name":"Benchmark (surveying)","score":0.800599992275238},{"id":"https://openalex.org/keywords/rubric","display_name":"Rubric","score":0.7250999808311462},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7196000218391418},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6044999957084656},{"id":"https://openalex.org/keywords/verifiable-secret-sharing","display_name":"Verifiable secret sharing","score":0.41429999470710754},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.38350000977516174},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.38269999623298645}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8155999779701233},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.800599992275238},{"id":"https://openalex.org/C111640148","wikidata":"https://www.wikidata.org/wiki/Q847349","display_name":"Rubric","level":2,"score":0.7250999808311462},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7196000218391418},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6044999957084656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.558899998664856},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47130000591278076},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.41429999470710754},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4025000035762787},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.38350000977516174},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.38269999623298645},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.373199999332428},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3361000120639801},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3314000070095062},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.3061000108718872},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.28189998865127563},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.26499998569488525}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.03116","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03116","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.2606.03116","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03116","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":0.7633618116378784,"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":{"The":[0],"rapid":[1],"advancement":[2],"of":[3,66,112],"instruction-guided":[4],"audio":[5,60,94,190],"generation":[6],"has":[7],"highlighted":[8],"the":[9,79,125,152],"critical":[10],"need":[11],"for":[12,189],"robust":[13],"alignment":[14,166,184],"evaluation.":[15],"Current":[16],"automated":[17],"evaluation":[18,54],"methods":[19],"heavily":[20],"rely":[21],"on":[22],"holistic":[23],"scoring":[24,154],"from":[25],"general-purpose":[26],"large":[27],"language":[28],"models,":[29],"which":[30],"struggle":[31],"to":[32,40,120,169],"decouple":[33],"complex":[34,59],"instructions,":[35],"lack":[36],"interpretability,":[37],"and":[38,99,138,176],"fail":[39],"capture":[41],"fine-grained":[42],"attribute":[43],"mismatches.":[44],"To":[45,72],"address":[46],"this,":[47],"we":[48,77,107],"introduce":[49],"a":[50,63,82,109,130],"novel":[51],"dynamic":[52],"rubric-based":[53,153],"paradigm":[55],"that":[56,133,159,180],"adaptively":[57],"decomposes":[58],"captions":[61],"into":[62],"variable":[64],"number":[65],"independent,":[67],"verifiable":[68],"binary":[69],"rubric":[70],"items.":[71],"rigorously":[73],"benchmark":[74,85],"this":[75],"capability,":[76],"propose":[78],"AnyAudio-Judge":[80,126,160],"Bench,":[81],"comprehensive,":[83],"bilingual":[84],"comprising":[86],"7,920":[87],"meticulously":[88],"curated":[89],"samples":[90,114],"across":[91],"four":[92],"diverse":[93],"domains":[95],"(speech,":[96],"sound,":[97],"music,":[98],"mixed),":[100],"featuring":[101],"deliberately":[102],"constructed":[103],"hard":[104],"negatives.":[105],"Furthermore,":[106],"construct":[108],"large-scale":[110],"corpus":[111],"105K":[113],"with":[115,151],"explicit":[116],"Chain-of-Thought":[117],"(CoT)":[118],"rationales":[119],"train":[121],"our":[122,144],"dedicated":[123],"evaluator,":[124],"model.":[127],"By":[128],"employing":[129],"training":[131],"pipeline":[132],"combines":[134],"Supervised":[135],"Fine-Tuning":[136],"(SFT)":[137],"Group":[139],"Relative":[140],"Policy":[141],"Optimization":[142],"(GRPO),":[143],"model":[145],"successfully":[146],"aligns":[147],"its":[148],"reasoning":[149],"paths":[150],"mechanism.":[155],"Extensive":[156],"experiments":[157],"demonstrate":[158],"not":[161],"only":[162],"significantly":[163],"enhances":[164],"zero-shot":[165],"detection":[167],"compared":[168],"state-of-the-art":[170],"baselines,":[171],"but":[172],"also":[173],"provides":[174],"precise":[175],"interpretable":[177],"reward":[178],"signals":[179],"substantially":[181],"improve":[182],"instruction":[183],"in":[185],"downstream":[186],"reinforcement":[187],"learning":[188],"generation.":[191]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-04T00:00:00"}