{"id":"https://openalex.org/W7137976708","doi":"https://doi.org/10.1609/aaai.v40i17.38503","title":"Multimodal Graph Representation Learning with Dynamic Information Pathways","display_name":"Multimodal Graph Representation Learning with Dynamic Information Pathways","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137976708","doi":"https://doi.org/10.1609/aaai.v40i17.38503"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i17.38503","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i17.38503","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38503/42465","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":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38503/42465","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129673077","display_name":"Xiaobin Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobin Hong","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101068353","display_name":"Mingkai Lin","orcid":"https://orcid.org/0000-0003-4911-6218"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingkai Lin","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129641703","display_name":"Xiaoli Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]},{"id":"https://openalex.org/I4210090357","display_name":"Nanjing Forest Police College","ror":"https://ror.org/00adax290","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210090357"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoli Wang","raw_affiliation_strings":["Nanjing Forest University, College of Information Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Forest University, College of Information Science and Technology","institution_ids":["https://openalex.org/I167027274","https://openalex.org/I4210090357"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129682187","display_name":"Chaoqun Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210152155","display_name":"Yunnan Investment Group (China)","ror":"https://ror.org/04zh2hd39","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210152155"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoqun Wang","raw_affiliation_strings":["Zhejiang Provincial Seaport Investment & Operation Group Co. Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Provincial Seaport Investment & Operation Group Co. Ltd","institution_ids":["https://openalex.org/I4210152155"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129714803","display_name":"Wenzhong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhong Li","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17331434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"17","first_page":"14829","last_page":"14837"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9909999966621399,"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":0.9909999966621399,"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":0.001500000013038516,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.0013000000035390258,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5909000039100647},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5458999872207642},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5157999992370605},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.504800021648407},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.44839999079704285},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.424699991941452},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.40220001339912415}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7925000190734863},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5909000039100647},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5458999872207642},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5157999992370605},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.504800021648407},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48980000615119934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48170000314712524},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.44839999079704285},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.424699991941452},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.40220001339912415},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.38029998540878296},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36480000615119934},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27379998564720154}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i17.38503","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i17.38503","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38503/42465","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"},{"id":"pmh:oai:ojs.aaai.org:article/38503","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/38503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i17.38503","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i17.38503","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38503/42465","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":[{"id":"https://openalex.org/G165146268","display_name":null,"funder_award_id":"BK20222003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4647006287","display_name":null,"funder_award_id":"BK20222003","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7137976708.pdf","grobid_xml":"https://content.openalex.org/works/W7137976708.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"graphs,":[1],"where":[2],"nodes":[3],"contain":[4],"heterogeneous":[5],"features":[6],"such":[7,21],"as":[8],"images":[9],"and":[10,29,49,60,99,117,131,138],"text,":[11],"are":[12,41],"increasingly":[13],"common":[14],"in":[15,107],"real-world":[16],"applications.":[17],"Effectively":[18],"learning":[19,40,75],"on":[20,51],"graphs":[22],"requires":[23],"both":[24],"adaptive":[25],"intra-modal":[26],"message":[27,90,119],"passing":[28],"efficient":[30,104],"inter-modal":[31],"aggregation.":[32],"However,":[33],"most":[34],"existing":[35],"approaches":[36],"to":[37,135],"multimodal":[38,72],"graph":[39,46,73],"typically":[42],"extended":[43],"from":[44],"conventional":[45],"neural":[47],"networks":[48],"rely":[50],"static":[52],"structures":[53],"or":[54],"dense":[55],"attention,":[56],"which":[57],"limit":[58],"flexibility":[59],"expressive":[61],"node":[62,132],"embedding":[63],"learning.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68],"propose":[69],"a":[70,108],"novel":[71],"representation":[74],"framework":[76],"with":[77,123],"Dynamic":[78],"information":[79,105],"Pathways":[80],"(DiP).":[81],"By":[82],"introducing":[83],"modality-specific":[84],"pseudo":[85],"nodes,":[86],"DiP":[87,151],"enables":[88],"dynamic":[89],"routing":[91],"within":[92],"each":[93],"modality":[94],"via":[95],"proximity-guided":[96],"pseudo-node":[97],"interactions":[98],"captures":[100],"inter-modality":[101],"dependence":[102],"through":[103],"pathways":[106],"shared":[109],"state":[110],"space.":[111],"This":[112],"design":[113],"achieves":[114],"adaptive,":[115],"expressive,":[116],"sparse":[118],"propagation":[120],"across":[121,146],"modalities":[122],"linear":[124],"complexity.":[125],"We":[126],"conduct":[127],"the":[128],"link":[129],"prediction":[130],"classification":[133],"tasks":[134],"evaluate":[136],"performance":[137],"carry":[139],"out":[140],"full":[141],"experimental":[142],"analyses.":[143],"Extensive":[144],"experiments":[145],"multiple":[147],"benchmarks":[148],"demonstrate":[149],"that":[150],"consistently":[152],"outperforms":[153],"baselines.":[154]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-18T00:00:00"}