{"id":"https://openalex.org/W7152706455","doi":"https://doi.org/10.48550/arxiv.2604.07239","title":"Efficient Learned Data Compression via Dual-Stream Feature Decoupling","display_name":"Efficient Learned Data Compression via Dual-Stream Feature Decoupling","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7152706455","doi":"https://doi.org/10.48550/arxiv.2604.07239"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.07239","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07239","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.07239","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101194582","display_name":"Huidong Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Huidong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133257726","display_name":"Xinyan Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Xinyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133238078","display_name":"Hui Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Hui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103146935","display_name":"Xiaofei Yue","orcid":"https://orcid.org/0009-0003-3106-586X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yue, Xiaofei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123472635","display_name":"xiaoguang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xiaoguang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133252718","display_name":"Gang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Gang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5123485502","display_name":"Wentong Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Wentong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.4081999957561493,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.4081999957561493,"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/T11269","display_name":"Algorithms and Data Compression","score":0.33570000529289246,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.049300000071525574,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/decoupling","display_name":"Decoupling (probability)","score":0.65420001745224},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5789999961853027},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5716000199317932},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4957999885082245},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4765999913215637},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.45820000767707825},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.40639999508857727},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.3756999969482422}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7950999736785889},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.65420001745224},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5789999961853027},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5716000199317932},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4957999885082245},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4765999913215637},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.45820000767707825},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.40639999508857727},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38029998540878296},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3767000138759613},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3732999861240387},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.36399999260902405},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3601999878883362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31869998574256897},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3066999912261963},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C27163531","wikidata":"https://www.wikidata.org/wiki/Q7454694","display_name":"Serial memory processing","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.26899999380111694},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2572999894618988},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.2506999969482422},{"id":"https://openalex.org/C51707140","wikidata":"https://www.wikidata.org/wiki/Q518280","display_name":"Serial communication","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.07239","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07239","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":"doi:10.48550/arxiv.2604.07239","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07239","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":"article"},"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":{"While":[0],"Learned":[1],"Data":[2],"Compression":[3],"(LDC)":[4],"has":[5],"achieved":[6],"superior":[7],"compression":[8,123],"ratios,":[9],"balancing":[10],"precise":[11,94],"probability":[12,95],"modeling":[13],"with":[14,79],"system":[15],"efficiency":[16],"remains":[17],"challenging.":[18],"Crucially,":[19],"uniform":[20],"single-stream":[21],"architectures":[22],"struggle":[23],"to":[24,56,74,108],"simultaneously":[25],"capture":[26],"micro-syntactic":[27],"and":[28,71,83,93,125,132],"macro-semantic":[29],"features,":[30],"necessitating":[31],"deep":[32,76],"serial":[33,57,77],"stacking":[34],"that":[35,68,115],"exacerbates":[36],"latency.":[37],"Compounding":[38],"this,":[39],"heterogeneous":[40],"systems":[41],"are":[42],"constrained":[43],"by":[44,52],"device":[45],"speed":[46],"mismatches,":[47],"where":[48],"throughput":[49],"is":[50,137],"capped":[51],"Amdahl's":[53],"Law":[54],"due":[55],"processing.":[58],"To":[59],"this":[60],"end,":[61],"we":[62,98],"propose":[63],"a":[64,85,100],"Dual-Stream":[65],"Multi-Scale":[66],"Decoupler":[67],"disentangles":[69],"local":[70],"global":[72],"contexts":[73],"replace":[75],"processing":[78],"shallow":[80],"parallel":[81],"streams,":[82],"incorporate":[84],"Hierarchical":[86],"Gated":[87],"Refiner":[88],"for":[89],"adaptive":[90],"feature":[91],"refinement":[92],"modeling.":[96],"Furthermore,":[97],"design":[99],"Concurrent":[101],"Stream-Parallel":[102],"Pipeline,":[103],"which":[104],"overcomes":[105],"systemic":[106],"bottlenecks":[107],"achieve":[109],"full-pipeline":[110],"parallelism.":[111],"Extensive":[112],"experiments":[113],"demonstrate":[114],"our":[116],"method":[117],"achieves":[118],"state-of-the-art":[119],"performance":[120],"in":[121],"both":[122],"ratio":[124],"throughput,":[126],"while":[127],"maintaining":[128],"the":[129],"lowest":[130],"latency":[131],"memory":[133],"usage.":[134],"The":[135],"code":[136],"available":[138],"at":[139],"https://github.com/huidong-ma/FADE.":[140]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-10T00:00:00"}