{"id":"https://openalex.org/W7128738903","doi":"https://doi.org/10.48550/arxiv.2602.11022","title":"Information Abstraction for Data Transmission Networks based on Large Language Models","display_name":"Information Abstraction for Data Transmission Networks based on Large Language Models","publication_year":2026,"publication_date":"2026-02-11","ids":{"openalex":"https://openalex.org/W7128738903","doi":"https://doi.org/10.48550/arxiv.2602.11022"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.11022","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.11022","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2602.11022","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041440508","display_name":"Haoyuan Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Haoyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125717882","display_name":"Haonan Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Haonan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125760954","display_name":"Jie Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jie","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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.3774999976158142,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.3774999976158142,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.09430000185966492,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14347","display_name":"Big Data and Digital Economy","score":0.06870000064373016,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/abstraction","display_name":"Abstraction","score":0.8296999931335449},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.531000018119812},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.49480000138282776},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4733999967575073},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.41920000314712524},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.3871999979019165},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.36399999260902405},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.34869998693466187},{"id":"https://openalex.org/keywords/information-theory","display_name":"Information theory","score":0.34139999747276306}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8425999879837036},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.8296999931335449},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.531000018119812},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5174000263214111},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.49480000138282776},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4733999967575073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45890000462532043},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.41920000314712524},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.3871999979019165},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C2983568541","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Information transmission","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.2962000072002411},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.295199990272522},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C87868495","wikidata":"https://www.wikidata.org/wiki/Q750843","display_name":"Information processing","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C147358964","wikidata":"https://www.wikidata.org/wiki/Q1200992","display_name":"Abstraction layer","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.11022","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.11022","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.11022","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.11022","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8994256258010864,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Biological":[0],"systems,":[1],"particularly":[2],"the":[3,58],"human":[4],"brain,":[5],"achieve":[6],"remarkable":[7],"energy":[8,28,135],"efficiency":[9],"by":[10,118],"abstracting":[11],"information":[12,49,92,137],"across":[13],"multiple":[14],"hierarchical":[15],"levels.":[16],"In":[17,53],"contrast,":[18],"modern":[19],"artificial":[20],"intelligence":[21],"and":[22,45,88,136,141,153],"communication":[23],"systems":[24,140],"often":[25],"consume":[26],"significant":[27],"overheads":[29],"in":[30,138,145],"transmitting":[31],"low-level":[32],"data,":[33],"with":[34],"limited":[35],"emphasis":[36],"on":[37],"abstraction.":[38],"Despite":[39],"its":[40],"implicit":[41],"importance,":[42],"a":[43,64,71,82,90,96,103,130],"formal":[44],"computational":[46],"theory":[47],"of":[48,60,86],"abstraction":[50,93],"remains":[51],"absent.":[52],"this":[54],"work,":[55],"we":[56,99],"introduce":[57],"Degree":[59],"Information":[61],"Abstraction":[62],"(DIA),":[63],"general":[65],"metric":[66],"that":[67,127],"quantifies":[68],"how":[69],"well":[70],"representation":[72],"compresses":[73],"input":[74],"data":[75],"while":[76,120],"preserving":[77],"task-relevant":[78],"semantics.":[79],"We":[80],"derive":[81],"tractable":[83],"information-theoretic":[84],"formulation":[85],"DIA":[87,101,128],"propose":[89],"DIA-based":[91],"framework.":[94],"As":[95],"case":[97],"study,":[98],"apply":[100],"to":[102],"large":[104],"language":[105],"model":[106],"(LLM)-guided":[107],"video":[108],"transmission":[109,116],"task,":[110],"where":[111],"abstraction-aware":[112],"encoding":[113],"significantly":[114],"reduces":[115],"volume":[117],"$99.75\\%$,":[119],"maintaining":[121],"semantic":[122,151],"fidelity.":[123],"Our":[124],"results":[125],"suggest":[126],"offers":[129],"principled":[131],"tool":[132],"for":[133],"rebalancing":[134],"intelligent":[139],"opens":[142],"new":[143],"directions":[144],"neural":[146],"network":[147],"design,":[148],"neuromorphic":[149],"computing,":[150],"communication,":[152],"joint":[154],"sensing-communication":[155],"architectures.":[156]},"counts_by_year":[],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2026-02-13T00:00:00"}
