{"id":"https://openalex.org/W7154731420","doi":"https://doi.org/10.48550/arxiv.2604.14806","title":"Listen, Pause, and Reason: Toward Perception-Grounded Hybrid Reasoning for Audio Understanding","display_name":"Listen, Pause, and Reason: Toward Perception-Grounded Hybrid Reasoning for Audio Understanding","publication_year":2026,"publication_date":"2026-04-16","ids":{"openalex":"https://openalex.org/W7154731420","doi":"https://doi.org/10.48550/arxiv.2604.14806"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.14806","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14806","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.2604.14806","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133903958","display_name":"Jieyi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jieyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133856088","display_name":"Yazhe Niu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niu, Yazhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133844155","display_name":"Dexuan Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Dexuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5011504177","display_name":"Zhongyu Wei","orcid":"https://orcid.org/0000-0003-3789-8507"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Zhongyu","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/T10860","display_name":"Speech and Audio Processing","score":0.3474000096321106,"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/T10860","display_name":"Speech and Audio Processing","score":0.3474000096321106,"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/T11309","display_name":"Music and Audio Processing","score":0.30820000171661377,"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":0.13989999890327454,"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/perception","display_name":"Perception","score":0.5806000232696533},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5609999895095825},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.3871000111103058},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.3817000091075897},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.3628999888896942},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.3571999967098236},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.30709999799728394},{"id":"https://openalex.org/keywords/mismatch-negativity","display_name":"Mismatch negativity","score":0.29739999771118164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.765999972820282},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5806000232696533},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5609999895095825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44350001215934753},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.3817000091075897},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3797000050544739},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3571999967098236},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34220001101493835},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.30709999799728394},{"id":"https://openalex.org/C21715850","wikidata":"https://www.wikidata.org/wiki/Q2720968","display_name":"Mismatch negativity","level":3,"score":0.29739999771118164},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C3020799230","wikidata":"https://www.wikidata.org/wiki/Q160289","display_name":"Auditory perception","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C2778263558","wikidata":"https://www.wikidata.org/wiki/Q46384","display_name":"Microphone","level":3,"score":0.25870001316070557},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.14806","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14806","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.2604.14806","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14806","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":{"Recent":[0],"Large":[1],"Audio":[2],"Language":[3],"Models":[4],"have":[5],"demonstrated":[6],"impressive":[7],"capabilities":[8],"in":[9,31,95],"audio":[10,21,165],"understanding.":[11,166],"However,":[12],"they":[13],"often":[14],"suffer":[15],"from":[16,58],"perceptual":[17,67,125],"errors,":[18],"while":[19],"reliable":[20],"reasoning":[22,68,130,160],"is":[23],"unattainable":[24],"without":[25],"first":[26,41],"grounding":[27],"the":[28,87,106,145,155],"model's":[29,107],"perception":[30],"structured":[32],"auditory":[33],"scenes.":[34],"Inspired":[35],"by":[36],"Auditory":[37],"Scene":[38],"Analysis,":[39],"we":[40,74,85,101],"introduce":[42,112],"a":[43,51,77],"Perception-Aware":[44],"Question":[45],"Answering":[46],"(PAQA)":[47],"dataset.":[48],"PAQA":[49,90],"implements":[50],"hierarchical":[52],"decoupling":[53],"strategy":[54],"that":[55,139],"separates":[56],"speech":[57],"environmental":[59],"sound":[60],"and":[61,123,163],"distinguishes":[62],"multiple":[63],"speakers,":[64],"providing":[65],"explicit":[66],"for":[69,161],"training.":[70],"Building":[71],"on":[72,89],"this,":[73],"propose":[75],"HyPeR,":[76],"two-stage":[78],"Hybrid":[79],"Perception-Reasoning":[80],"framework.":[81],"In":[82,98],"Stage":[83,99],"I,":[84],"finetune":[86],"model":[88],"to":[91,104,115,128,151],"perceive":[92],"acoustic":[93],"attributes":[94],"complex":[96],"audio.":[97,134],"II,":[100],"leverage":[102],"GRPO":[103],"refine":[105],"internal":[108],"deliberation.":[109],"We":[110],"also":[111],"PAUSE":[113],"tokens":[114],"facilitate":[116],"latent":[117],"computation":[118],"during":[119],"acoustically":[120],"ambiguous":[121],"phases":[122],"design":[124],"consistency":[126],"reward":[127],"align":[129],"rationales":[131],"with":[132,148],"raw":[133],"Experiments":[135],"across":[136],"benchmarks":[137],"demonstrate":[138],"HyPeR":[140],"achieves":[141],"absolute":[142],"improvements":[143],"over":[144],"base":[146],"model,":[147],"performance":[149],"comparable":[150],"large-scale":[152],"models,":[153],"stressing":[154],"effectiveness":[156],"of":[157],"hybrid":[158],"perception-grounded":[159],"robust":[162],"multi-speaker":[164]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-18T00:00:00"}
