{"id":"https://openalex.org/W7138072261","doi":"https://doi.org/10.1609/aaai.v40i26.39351","title":"SemanticNN: Compressive and Error-Resilient Semantic Offloading for Extremely Weak Devices","display_name":"SemanticNN: Compressive and Error-Resilient Semantic Offloading for Extremely Weak Devices","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138072261","doi":"https://doi.org/10.1609/aaai.v40i26.39351"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i26.39351","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i26.39351","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39351/43312","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39351/43312","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129652849","display_name":"Jiaming Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaming Huang","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129676371","display_name":"Yi Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Gao","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129739108","display_name":"Fuchang Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuchang Pan","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070287035","display_name":"Renjie Li","orcid":"https://orcid.org/0009-0003-6917-2935"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renjie Li","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129670582","display_name":"Wei Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Dong","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"26","first_page":"21975","last_page":"21983"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.5422000288963318,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.5422000288963318,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.163100004196167,"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/T13553","display_name":"Age of Information Optimization","score":0.04650000110268593,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/encoder","display_name":"Encoder","score":0.579800009727478},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.47679999470710754},{"id":"https://openalex.org/keywords/codec","display_name":"Codec","score":0.4731999933719635},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47200000286102295},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.45910000801086426},{"id":"https://openalex.org/keywords/data-transmission","display_name":"Data transmission","score":0.38519999384880066},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.3788999915122986},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.3763999938964844}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.840499997138977},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.579800009727478},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.47679999470710754},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.4731999933719635},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47200000286102295},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.45910000801086426},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3978999853134155},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.3788999915122986},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.3718999922275543},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3668999969959259},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3440000116825104},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.2944999933242798},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2703999876976013},{"id":"https://openalex.org/C101722063","wikidata":"https://www.wikidata.org/wiki/Q218825","display_name":"Random access","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i26.39351","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i26.39351","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39351/43312","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i26.39351","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i26.39351","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39351/43312","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138072261.pdf","grobid_xml":"https://content.openalex.org/works/W7138072261.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,5,32],"rapid":[2],"growth":[3],"of":[4,7,35,76],"Internet":[6],"Things":[8],"(IoT),":[9],"integrating":[10],"artificial":[11],"intelligence":[12],"(AI)":[13],"on":[14,50,117,154],"extremely":[15],"weak":[16],"embedded":[17],"devices":[18,37],"has":[19],"garnered":[20],"significant":[21],"attention,":[22],"enabling":[23,79],"improved":[24],"real-time":[25],"performance":[26],"and":[27,38,81,89,106,159,165],"enhanced":[28],"data":[29],"privacy.":[30],"However,":[31],"resource":[33],"limitations":[34],"such":[36],"unreliable":[39],"network":[40],"conditions":[41,105],"necessitate":[42],"error-resilient":[43],"device-edge":[44],"collaboration":[45],"systems.":[46],"Traditional":[47],"approaches":[48],"focus":[49],"bit-level":[51,72],"transmission":[52,175,182],"correctness,":[53,78],"which":[54],"can":[55],"be":[56],"inefficient":[57],"under":[58,86,173],"dynamic":[59,103],"channel":[60,104],"conditions.":[61],"In":[62],"contrast,":[63],"we":[64,120,140],"propose":[65,141],"SemanticNN,":[66],"a":[67,94,107,124],"semantic":[68,148],"codec":[69],"that":[70,100,128],"tolerates":[71],"errors":[73],"in":[74],"pursuit":[75],"semantic-level":[77],"compressive":[80],"resilient":[82],"collaborative":[83],"inference":[84,189],"offloading":[85,130],"strict":[87],"computational":[88],"communication":[90],"constraints.":[91],"It":[92],"incorporates":[93],"Bit":[95],"Error":[96],"Rate":[97],"(BER)-aware":[98],"decoder":[99],"adapts":[101],"to":[102,112,145],"Soft":[108],"Quantization":[109],"(SQ)-based":[110],"encoder":[111],"learn":[113],"compact":[114],"representations.":[115],"Building":[116],"this":[118],"architecture,":[119],"introduce":[121],"Feature-augmentation":[122],"Learning,":[123],"novel":[125],"training":[126],"strategy":[127],"enhances":[129],"efficiency.":[131],"To":[132],"address":[133],"encoder-decoder":[134],"capability":[135],"mismatches":[136],"from":[137],"asymmetric":[138],"resources,":[139],"XAI-based":[142],"Asymmetry":[143],"Compensation":[144],"enhance":[146],"decoding":[147],"fidelity.":[149],"We":[150],"conduct":[151],"extensive":[152],"experiments":[153],"STM32":[155],"using":[156],"three":[157],"models":[158],"six":[160],"datasets":[161],"across":[162],"image":[163],"classification":[164],"object":[166],"detection":[167],"tasks.":[168],"Experimental":[169],"results":[170],"demonstrate":[171],"that,":[172],"varying":[174],"error":[176],"rates,":[177],"SemanticNN":[178],"significantly":[179],"reduces":[180],"feature":[181],"volume":[183],"by":[184],"56.82\u2013344.83\u00d7":[185],"while":[186],"maintaining":[187],"superior":[188],"accuracy.":[190]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}
