{"id":"https://openalex.org/W7125192585","doi":"https://doi.org/10.3389/fncom.2025.1731452","title":"F2-CommNet: Fourier\u2013Fractional neural networks with Lyapunov stability guarantees for hallucination-resistant community detection","display_name":"F2-CommNet: Fourier\u2013Fractional neural networks with Lyapunov stability guarantees for hallucination-resistant community detection","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7125192585","doi":"https://doi.org/10.3389/fncom.2025.1731452","pmid":"https://pubmed.ncbi.nlm.nih.gov/41647525"},"language":"en","primary_location":{"id":"doi:10.3389/fncom.2025.1731452","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fncom.2025.1731452","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2025.1731452/pdf","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://public-pages-files-2025.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2025.1731452/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029896002","display_name":"Daozheng Qu","orcid":"https://orcid.org/0000-0002-1950-2620"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Daozheng Qu","raw_affiliation_strings":["Department of Computer Science, University of Liverpool"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Liverpool","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122359940","display_name":"Yanfei Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I32907511","display_name":"Fairleigh Dickinson University","ror":"https://ror.org/04wkzvc75","country_code":"US","type":"education","lineage":["https://openalex.org/I32907511"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yanfei Ma","raw_affiliation_strings":["Department of Computer Science, Fairleigh Dickinson University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Fairleigh Dickinson University","institution_ids":["https://openalex.org/I32907511"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029896002","https://openalex.org/A5122359940"],"corresponding_institution_ids":["https://openalex.org/I146655781","https://openalex.org/I32907511"],"apc_list":{"value":2950,"currency":"USD","value_usd":2950},"apc_paid":{"value":2950,"currency":"USD","value_usd":2950},"fwci":22.4915,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.97892342,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"19","issue":null,"first_page":"1731452","last_page":"1731452"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8463000059127808,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8463000059127808,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.045899998396635056,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.026200000196695328,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6571000218391418},{"id":"https://openalex.org/keywords/lipschitz-continuity","display_name":"Lipschitz continuity","score":0.5817999839782715},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5497000217437744},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5109000205993652},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4934999942779541},{"id":"https://openalex.org/keywords/lyapunov-function","display_name":"Lyapunov function","score":0.47909998893737793},{"id":"https://openalex.org/keywords/lyapunov-stability","display_name":"Lyapunov stability","score":0.4683000147342682},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4278999865055084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6593000292778015},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6571000218391418},{"id":"https://openalex.org/C22324862","wikidata":"https://www.wikidata.org/wiki/Q652707","display_name":"Lipschitz continuity","level":2,"score":0.5817999839782715},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5497000217437744},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4934999942779541},{"id":"https://openalex.org/C60640748","wikidata":"https://www.wikidata.org/wiki/Q2337858","display_name":"Lyapunov function","level":3,"score":0.47909998893737793},{"id":"https://openalex.org/C2776829284","wikidata":"https://www.wikidata.org/wiki/Q1341651","display_name":"Lyapunov stability","level":3,"score":0.4683000147342682},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4278999865055084},{"id":"https://openalex.org/C2983668108","wikidata":"https://www.wikidata.org/wiki/Q280453","display_name":"Spectral analysis","level":3,"score":0.42160001397132874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40389999747276306},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.38839998841285706},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.37779998779296875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37119999527931213},{"id":"https://openalex.org/C2985906921","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Spectral properties","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.3483999967575073},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C167964875","wikidata":"https://www.wikidata.org/wiki/Q17011487","display_name":"Exponential stability","level":3,"score":0.3061999976634979},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.29910001158714294},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2596000134944916}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fncom.2025.1731452","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fncom.2025.1731452","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2025.1731452/pdf","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},{"id":"pmid:41647525","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41647525","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in computational neuroscience","raw_type":null},{"id":"pmh:oai:doaj.org/article:11f2cf25a247489195144d5841ad4111","is_oa":true,"landing_page_url":"https://doaj.org/article/11f2cf25a247489195144d5841ad4111","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Computational Neuroscience, Vol 19 (2026)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:11676257","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12868212","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3389/fncom.2025.1731452","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fncom.2025.1731452","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2025.1731452/pdf","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6230916380882263,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7125192585.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W2610034660","https://openalex.org/W2618648829","https://openalex.org/W2890659396","https://openalex.org/W2907492528","https://openalex.org/W2972317931","https://openalex.org/W2990045899","https://openalex.org/W2998313947","https://openalex.org/W3007134945","https://openalex.org/W3093053585","https://openalex.org/W4313349494","https://openalex.org/W4318962769","https://openalex.org/W4362671197","https://openalex.org/W4377293991","https://openalex.org/W4388822942","https://openalex.org/W4390278267","https://openalex.org/W4391168569","https://openalex.org/W4392781832","https://openalex.org/W4394931577","https://openalex.org/W4402788794","https://openalex.org/W4403827127","https://openalex.org/W4403965075","https://openalex.org/W4405220555","https://openalex.org/W4407945771","https://openalex.org/W4410290360","https://openalex.org/W4411801338","https://openalex.org/W4411866513","https://openalex.org/W4414270522"],"related_works":[],"abstract_inverted_index":{"Community":[0],"detection":[1],"is":[2],"a":[3,70,117,166],"crucial":[4],"task":[5],"in":[6,20,116,147],"network":[7,163],"research,":[8],"applicable":[9],"to":[10,40,48,101,149],"social":[11],"systems,":[12],"biology,":[13],"cybersecurity,":[14],"and":[15,35,52,80,112,128,143,161],"knowledge":[16],"graphs.":[17],"Recent":[18],"advancements":[19],"graph":[21,159],"neural":[22,72,162],"networks":[23,130],"(GNNs)":[24],"have":[25],"exhibited":[26],"significant":[27],"representational":[28],"capability;":[29],"yet,":[30],"they":[31],"frequently":[32],"experience":[33],"instability":[34],"erroneous":[36],"clustering,":[37],"often":[38],"referred":[39],"as":[41],"\u201dhallucinations.\u201d":[42],"These":[43],"artifacts":[44],"stem":[45],"from":[46],"sensitivity":[47],"high-frequency":[49],"eigenmodes,":[50],"over-parameterization,":[51],"noise":[53],"amplification,":[54],"undermining":[55],"the":[56,121],"robustness":[57],"of":[58,120],"learned":[59],"communities.":[60],"To":[61],"mitigate":[62],"these":[63],"constraints,":[64],"we":[65],"present":[66],"F":[67,133],"2":[68,134],"-CommNet,":[69],"Fourier\u2013Fractional":[71],"framework":[73],"that":[74,90,132],"incorporates":[75],"fractional-order":[76],"dynamics,":[77,164],"spectrum":[78],"filtering,":[79],"Lyapunov-based":[81],"stability":[82,107,141],"analysis.":[83],"The":[84],"fractional":[85,156],"operator":[86],"implements":[87],"long-memory":[88],"dampening":[89],"mitigates":[91],"oscillations,":[92],"whereas":[93],"Fourier":[94],"spectral":[95,158],"projections":[96],"selectively":[97],"attenuate":[98],"eigenmodes":[99],"susceptible":[100],"hallucination.":[102],"Theoretical":[103],"analysis":[104],"delineates":[105],"certain":[106],"criteria":[108],"under":[109],"Lipschitz":[110],"non-linearities":[111],"constrained":[113],"disturbances,":[114],"resulting":[115],"demonstrable":[118],"expansion":[119],"Lyapunov":[122],"margin.":[123],"Experimental":[124],"validation":[125],"on":[126],"synthetic":[127],"actual":[129],"indicates":[131],"-CommNet":[135],"reliably":[136],"diminishes":[137],"hallucination":[138],"indices,":[139],"enhances":[140],"margins,":[142],"produces":[144],"interpretable":[145],"communities":[146],"comparison":[148],"integer-order":[150],"GNN":[151],"baselines.":[152],"This":[153],"study":[154],"integrates":[155],"calculus,":[157],"theory,":[160],"providing":[165],"systematic":[167],"method":[168],"for":[169],"hallucination-resistant":[170],"community":[171],"discovery.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-30T09:04:40.226872","created_date":"2026-01-22T00:00:00"}
