{"id":"https://openalex.org/W7155785313","doi":"https://doi.org/10.1145/3774904.3792435","title":"Heterophily-Agnostic Hypergraph Neural Networks with Riemannian Local Exchanger","display_name":"Heterophily-Agnostic Hypergraph Neural Networks with Riemannian Local Exchanger","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7155785313","doi":"https://doi.org/10.1145/3774904.3792435"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792435","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792435","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774904.3792435","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134710275","display_name":"Li Sun","orcid":"https://orcid.org/0000-0003-4562-2279"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Sun","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4562-2279","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447306","display_name":"Ming Zhang","orcid":"https://orcid.org/0000-0002-9372-4926"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhang","raw_affiliation_strings":["North China Electric Power University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-5003-7252","affiliations":[{"raw_affiliation_string":"North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109375874","display_name":"Wenxin Jin","orcid":"https://orcid.org/0009-0005-8253-4843"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Jin","raw_affiliation_strings":["North China Electric Power University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-8253-4843","affiliations":[{"raw_affiliation_string":"North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083169271","display_name":"Zhongtian Sun","orcid":"https://orcid.org/0000-0003-0489-5203"},"institutions":[{"id":"https://openalex.org/I20581793","display_name":"University of Kent","ror":"https://ror.org/00xkeyj56","country_code":"GB","type":"education","lineage":["https://openalex.org/I20581793"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhongtian Sun","raw_affiliation_strings":["University of Kent, Canterbury, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0003-0489-5203","affiliations":[{"raw_affiliation_string":"University of Kent, Canterbury, United Kingdom","institution_ids":["https://openalex.org/I20581793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016322367","display_name":"Zhenhao Huang","orcid":"https://orcid.org/0009-0007-8944-0385"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhao Huang","raw_affiliation_strings":["North China Electric Power University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-8944-0385","affiliations":[{"raw_affiliation_string":"North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100740622","display_name":"Hao Peng","orcid":"https://orcid.org/0000-0003-0458-5977"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Peng","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0458-5977","affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036865453","display_name":"Sen Su","orcid":"https://orcid.org/0000-0003-4266-7527"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Su","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4266-7527","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"institutions":[{"id":"https://openalex.org/I36053171","display_name":"California State University, Chico","ror":"https://ror.org/027bzz146","country_code":"US","type":"education","lineage":["https://openalex.org/I36053171"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Yu","raw_affiliation_strings":["University of Illinois, Chicgao, USA"],"raw_orcid":"https://orcid.org/0000-0002-3491-5968","affiliations":[{"raw_affiliation_string":"University of Illinois, Chicgao, USA","institution_ids":["https://openalex.org/I36053171"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.63479947,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1092","last_page":"1103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9706000089645386,"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":0.9706000089645386,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.006800000090152025,"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.003800000064074993,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/hypergraph","display_name":"Hypergraph","score":0.862500011920929},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.6344000101089478},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5618000030517578},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.49129998683929443},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47870001196861267},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.4733999967575073},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4325000047683716}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.862500011920929},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.6344000101089478},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5618000030517578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5611000061035156},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5586000084877014},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.49129998683929443},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47870001196861267},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.4733999967575073},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.387800008058548},{"id":"https://openalex.org/C2779593128","wikidata":"https://www.wikidata.org/wiki/Q632814","display_name":"Riemannian manifold","level":2,"score":0.36550000309944153},{"id":"https://openalex.org/C2779812341","wikidata":"https://www.wikidata.org/wiki/Q5891525","display_name":"Homophily","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3547999858856201},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3154999911785126},{"id":"https://openalex.org/C13355873","wikidata":"https://www.wikidata.org/wiki/Q2920850","display_name":"Connection (principal bundle)","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29600000381469727},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.289000004529953}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774904.3792435","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792435","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774904.3792435","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792435","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2021122545","https://openalex.org/W2233017936","https://openalex.org/W2892880750","https://openalex.org/W3006296570","https://openalex.org/W3007652077","https://openalex.org/W3085990079","https://openalex.org/W3117562715","https://openalex.org/W3128531206","https://openalex.org/W3175597370","https://openalex.org/W4225778021","https://openalex.org/W4294002162","https://openalex.org/W4381613464","https://openalex.org/W4391528858","https://openalex.org/W4401284358","https://openalex.org/W4401863422","https://openalex.org/W4409347622","https://openalex.org/W4409364135","https://openalex.org/W4409364207","https://openalex.org/W4409657087","https://openalex.org/W4411549710"],"related_works":[],"abstract_inverted_index":{"Hypergraphs":[0],"are":[1,34],"the":[2,25,43,50,63,67,71,82,88,120,126,133,137,149,157,169,175,184,188,199,204,209,251,269],"natural":[3],"description":[4],"of":[5,84,122,128,159,172,177,183,190,253],"higher-order":[6],"interactions":[7],"among":[8],"objects,":[9],"widely":[10],"applied":[11],"in":[12,87,141,148,250],"social":[13],"network":[14],"analysis,":[15],"cross-modal":[16],"retrieval,":[17],"etc.":[18],"Hypergraph":[19,237],"Neural":[20,238],"Networks":[21],"(HGNNs)":[22],"have":[23],"become":[24],"dominant":[26],"solution":[27],"for":[28,56,236],"learning":[29],"on":[30,165,224,259],"hypergraphs.":[31],"Traditional":[32],"HGNNs":[33],"extended":[35],"from":[36],"message":[37,64,138,218],"passing":[38,139,219],"graph":[39],"neural":[40],"networks,":[41],"following":[42],"homophily":[44],"assumption,":[45],"and":[46,74,112,153,207,255,262],"thus":[47],"struggle":[48],"with":[49,220,233,247],"prevalent":[51],"heterophilic":[52,113,263],"hypergraphs":[53],"that":[54,106,266],"call":[55],"long-range":[57,76,201],"dependence":[58],"modeling.":[59],"Existing":[60],"solutions":[61],"enlarge":[62],"flow":[65],"through":[66,125],"hypergraph":[68,154],"bottleneck,":[69],"mitigating":[70],"oversquashing":[72,152],"issue":[73],"capturing":[75],"dependence.":[77],"However,":[78],"they":[79],"often":[80],"accelerate":[81],"loss":[83],"representation":[85,210],"distinguishability":[86,211],"repeated":[89],"aggregations,":[90],"leading":[91],"to":[92,109,135],"oversmoothing.":[93],"This":[94],"dilemma":[95],"motivates":[96],"an":[97,191],"interesting":[98],"question:":[99],"Can":[100],"we":[101,118,167,228],"develop":[102],"a":[103,230,243],"unified":[104],"mechanism":[105,186],"is":[107,187],"agnostic":[108],"both":[110,123,260],"homophilic":[111,261],"hypergraphs?":[114],"In":[115],"this":[116,225],"paper,":[117],"achieve":[119],"best":[121],"worlds":[124],"lens":[127],"Riemannian":[129,160],"geometry,":[130],"which":[131],"provides":[132],"potential":[134],"adjust":[136],"behavior":[140],"different":[142,178],"regions.":[143],"The":[144,180],"key":[145],"insight":[146],"lies":[147],"connection":[150],"between":[151],"bottleneck":[155],"within":[156],"framework":[158],"manifold":[161],"heat":[162],"flow.":[163],"Building":[164],"this,":[166],"propose":[168],"novel":[170,231],"idea":[171],"locally":[173],"adapting":[174],"bottlenecks":[176],"subhypergraphs.":[179],"core":[181],"innovation":[182],"proposed":[185],"design":[189],"adaptive":[192],"local":[193],"(heat)":[194],"exchanger.":[195],"Specifically,":[196],"it":[197],"captures":[198],"rich":[200],"dependencies":[202],"via":[203,212],"Robin":[205],"condition,":[206],"preserves":[208],"source":[213],"terms,":[214],"thereby":[215],"enabling":[216],"heterophily-agnostic":[217],"theoretical":[221,226],"guarantees.":[222],"Based":[223],"foundation,":[227],"present":[229],"Heat-Exchanger":[232],"Adaptive":[234],"Locality":[235],"Network":[239],"(HealHGNN),":[240],"designed":[241],"as":[242],"node-hyperedge":[244],"bidirectional":[245],"systems":[246],"linear":[248],"complexity":[249],"number":[252],"nodes":[254],"hyperedges.":[256],"Extensive":[257],"experiments":[258],"cases":[264],"show":[265],"HealHGNN":[267],"achieves":[268],"state-of-the-art":[270],"performance.":[271]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-28T00:00:00"}
