{"id":"https://openalex.org/W4415329068","doi":"https://doi.org/10.48550/arxiv.2505.15547","title":"Oversmoothing, Oversquashing, Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning","display_name":"Oversmoothing, Oversquashing, Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning","publication_year":2025,"publication_date":"2025-05-21","ids":{"openalex":"https://openalex.org/W4415329068","doi":"https://doi.org/10.48550/arxiv.2505.15547"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2505.15547","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.15547","pdf_url":"https://arxiv.org/pdf/2505.15547","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2505.15547","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031106143","display_name":"Adri\u00e1n Arnaiz-Rodr\u00edguez","orcid":"https://orcid.org/0000-0001-5567-801X","observed_orcids":["https://orcid.org/0000-0001-5567-801X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arnaiz-Rodriguez, Adrian","raw_affiliation_strings":["NEC Laboratories Europe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Laboratories Europe","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084297425","display_name":"Federico Errica","orcid":"https://orcid.org/0000-0001-5181-2904","observed_orcids":["https://orcid.org/0000-0001-5181-2904"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Errica, Federico","raw_affiliation_strings":["NEC Laboratories Europe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Laboratories Europe","institution_ids":[]}]}],"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":true,"cited_by_count":21,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994999766349792,"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":0.9994999766349792,"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":9.999999747378752e-05,"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"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/graph-neural-networks","display_name":"graph neural networks","score":0.8149999976158142},{"id":"https://openalex.org/keywords/message-passing","display_name":"message passing","score":0.9210000038146973},{"id":"https://openalex.org/keywords/over-smoothing","display_name":"over-smoothing","score":0.9940000176429749},{"id":"https://openalex.org/keywords/heterophily","display_name":"heterophily","score":0.8289999961853027},{"id":"https://openalex.org/keywords/homophily","display_name":"homophily","score":0.9259999990463257},{"id":"https://openalex.org/keywords/counterexample","display_name":"counterexample","score":0.7229999899864197},{"id":"https://openalex.org/keywords/conceptual-clarification","display_name":"conceptual clarification","score":0.37299999594688416},{"id":"https://openalex.org/keywords/graph-learning","display_name":"graph learning","score":0.5550000071525574}],"concepts":[{"id":"https://openalex.org/C2779913896","wikidata":"https://www.wikidata.org/wiki/Q7063001","display_name":"Notice","level":2,"score":0.7264999747276306},{"id":"https://openalex.org/C2777526511","wikidata":"https://www.wikidata.org/wiki/Q691543","display_name":"Pace","level":2,"score":0.6047000288963318},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5960999727249146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.527999997138977},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.4564000070095062},{"id":"https://openalex.org/C43091099","wikidata":"https://www.wikidata.org/wiki/Q1067788","display_name":"Through-the-lens metering","level":3,"score":0.4099000096321106},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C52069626","wikidata":"https://www.wikidata.org/wiki/Q4692","display_name":"The Renaissance","level":2,"score":0.34929999709129333},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31290000677108765},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.29030001163482666},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.28279998898506165},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.28139999508857727},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.2759000062942505},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2505.15547","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.15547","pdf_url":"https://arxiv.org/pdf/2505.15547","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2505.15547","doi":"https://doi.org/10.48550/arxiv.2505.15547","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2505.15547","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,"listed_in":[],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2505.15547","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.15547","pdf_url":"https://arxiv.org/pdf/2505.15547","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415329068.pdf","grobid_xml":"https://content.openalex.org/works/W4415329068.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W3013034147","https://openalex.org/W3082217026","https://openalex.org/W3200726313","https://openalex.org/W4353007232","https://openalex.org/W4386556018","https://openalex.org/W4388685258","https://openalex.org/W4398795635","https://openalex.org/W4400141673","https://openalex.org/W4404988934","https://openalex.org/W4407091224","https://openalex.org/W4407309021","https://openalex.org/W4407684143","https://openalex.org/W4410291636","https://openalex.org/W4412591781","https://openalex.org/W4415271283"],"related_works":["https://openalex.org/W4226299420","https://openalex.org/W4311556018","https://openalex.org/W4390579897","https://openalex.org/W4390437281","https://openalex.org/W7156966263","https://openalex.org/W7125908379","https://openalex.org/W4415056896","https://openalex.org/W7163064152","https://openalex.org/W7133209134","https://openalex.org/W7123688595"],"abstract_inverted_index":{"After":[0],"a":[1,26,114],"renaissance":[2],"phase":[3],"in":[4],"which":[5],"researchers":[6,103,153],"revisited":[7],"the":[8,12,17,42,48,54,62,72,99],"message-passing":[9],"paradigm":[10],"through":[11],"lens":[13],"of":[14,31,45,50,64,74,117],"deep":[15],"learning,":[16],"graph":[18],"machine":[19],"learning":[20],"community":[21],"shifted":[22],"its":[23],"attention":[24],"towards":[25],"deeper":[27],"and":[28,34,52,57,68,107,128,158],"practical":[29],"understanding":[30],"message-passing's":[32],"benefits":[33],"limitations.":[35],"In":[36],"this":[37,93],"paper,":[38],"we":[39],"notice":[40],"how":[41],"fast":[43],"pace":[44],"progress":[46],"around":[47,98,132],"topics":[49],"oversmoothing":[51],"oversquashing,":[53],"homophily-heterophily":[55],"dichotomy,":[56],"long-range":[58],"tasks,":[59],"came":[60],"with":[61],"consolidation":[63],"commonly":[65],"accepted":[66],"beliefs":[67,126],"assumptions":[69],"--":[70,77],"under":[71],"form":[73],"universal":[75,136],"statements":[76,137],"that":[78,92],"are":[79],"not":[80],"always":[81],"true":[82],"nor":[83],"easy":[84],"to":[85,96,122,148],"distinguish":[86],"from":[87,104],"each":[88],"other.":[89],"We":[90],"argue":[91],"has":[94],"led":[95],"ambiguities":[97],"investigated":[100],"problems,":[101],"preventing":[102],"focusing":[105],"on":[106],"addressing":[108],"precise":[109],"research":[110],"questions":[111],"while":[112],"causing":[113],"good":[115],"amount":[116],"misunderstandings.":[118],"Our":[119],"contribution":[120],"is":[121,147],"make":[123],"such":[124],"common":[125],"explicit":[127],"encourage":[129],"critical":[130],"thinking":[131],"these":[133],"topics,":[134],"refuting":[135],"via":[138],"simple":[139],"yet":[140],"formally":[141],"sufficient":[142],"counterexamples.":[143],"The":[144],"end":[145],"goal":[146],"clarify":[149],"conceptual":[150],"differences,":[151],"helping":[152],"address":[154],"more":[155],"clearly":[156],"defined":[157],"targeted":[159],"problems.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":9}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-19T00:00:00"}