{"id":"https://openalex.org/W7129229316","doi":"https://doi.org/10.48550/arxiv.2602.13669","title":"EchoTorrent: Towards Swift, Sustained, and Streaming Multi-Modal Video Generation","display_name":"EchoTorrent: Towards Swift, Sustained, and Streaming Multi-Modal Video Generation","publication_year":2026,"publication_date":"2026-02-14","ids":{"openalex":"https://openalex.org/W7129229316","doi":"https://doi.org/10.48550/arxiv.2602.13669"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.13669","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126232470","display_name":"Rang Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Meng, Rang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yin, Yingjie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Yingjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Li, Yuming","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yuming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Ma, Chenguang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Chenguang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5126232470"],"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7139999866485596,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7139999866485596,"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/T10860","display_name":"Speech and Audio Processing","score":0.1429000049829483,"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/T11448","display_name":"Face recognition and analysis","score":0.02290000021457672,"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/inference","display_name":"Inference","score":0.609000027179718},{"id":"https://openalex.org/keywords/on-the-fly","display_name":"On the fly","score":0.5784000158309937},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.5457000136375427},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.5044999718666077},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.44929999113082886},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.39430001378059387},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.392300009727478},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.3837999999523163},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.3528999984264374}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8149999976158142},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.609000027179718},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.5784000158309937},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.5457000136375427},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5044999718666077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47679999470710754},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.39430001378059387},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.392300009727478},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.3837999999523163},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.364300012588501},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3528999984264374},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34700000286102295},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.33980000019073486},{"id":"https://openalex.org/C134652429","wikidata":"https://www.wikidata.org/wiki/Q1052698","display_name":"Jitter","level":2,"score":0.3384000062942505},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30820000171661377},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25850000977516174},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C3018907156","wikidata":"https://www.wikidata.org/wiki/Q7785058","display_name":"Third generation","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.13669","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.13669","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.13669","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.13669","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"multi-modal":[1],"video":[2],"generation":[3,177],"models":[4],"have":[5],"achieved":[6],"high":[7],"visual":[8],"quality,":[9],"but":[10],"their":[11],"prohibitive":[12],"latency":[13],"and":[14,37,107,147,169,185],"limited":[15],"temporal":[16,35,181],"stability":[17],"hinder":[18],"real-time":[19],"deployment.":[20],"Streaming":[21],"inference":[22,110],"exacerbates":[23],"these":[24],"issues,":[25],"leading":[26],"to":[27,70,80,144,159],"pronounced":[28],"multimodal":[29],"degradation,":[30],"such":[31],"as":[32],"spatial":[33],"blurring,":[34],"drift,":[36],"lip":[38],"desynchronization,":[39],"which":[40,75,89,118],"creates":[41],"an":[42],"unresolved":[43],"efficiency-performance":[44],"trade-off.":[45],"To":[46],"this":[47],"end,":[48],"we":[49],"propose":[50],"EchoTorrent,":[51],"a":[52,56,63,81,99,130],"novel":[53],"schema":[54],"with":[55,178],"fourfold":[57],"design:":[58],"(1)":[59],"Multi-Teacher":[60],"Training":[61],"fine-tunes":[62],"pre-trained":[64],"model":[65],"on":[66,122],"distinct":[67],"preference":[68],"domains":[69],"obtain":[71],"specialized":[72],"domain":[73],"experts,":[74],"sequentially":[76],"transfer":[77],"domain-specific":[78],"knowledge":[79],"student":[82],"model;":[83],"(2)":[84],"Adaptive":[85],"CFG":[86,93,105],"Calibration":[87],"(ACC-DMD),":[88],"calibrates":[90],"the":[91,156],"audio":[92],"augmentation":[94],"errors":[95],"in":[96,138],"DMD":[97],"via":[98,129],"phased":[100],"spatiotemporal":[101,136],"schedule,":[102],"eliminating":[103],"redundant":[104],"computations":[106],"enabling":[108],"single-pass":[109],"per":[111],"step;":[112],"(3)":[113],"Hybrid":[114],"Long":[115],"Tail":[116],"Forcing,":[117],"enforces":[119],"alignment":[120],"exclusively":[121],"tail":[123],"frames":[124],"during":[125],"long-horizon":[126],"self-rollout":[127],"training":[128],"causal-bidirectional":[131],"hybrid":[132],"architecture,":[133],"effectively":[134],"mitigates":[135],"degradation":[137],"streaming":[139],"mode":[140],"while":[141,163],"enhancing":[142],"fidelity":[143],"reference":[145],"frames;":[146],"(4)":[148],"VAE":[149,157],"Decoder":[150],"Refiner":[151],"through":[152],"pixel-domain":[153],"optimization":[154],"of":[155],"decoder":[158],"recover":[160],"high-frequency":[161],"details":[162],"circumventing":[164],"latent-space":[165],"ambiguities.":[166],"Extensive":[167],"experiments":[168],"analysis":[170],"demonstrate":[171],"that":[172],"EchoTorrent":[173],"achieves":[174],"few-pass":[175],"autoregressive":[176],"substantially":[179],"extended":[180],"consistency,":[182],"identity":[183],"preservation,":[184],"audio-lip":[186],"synchronization.":[187]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-18T00:00:00"}