{"id":"https://openalex.org/W4414360376","doi":"https://doi.org/10.24963/ijcai.2025/569","title":"HiTuner: Hierarchical Semantic Fusion Model Fine-Tuning on Text-Attributed Graphs","display_name":"HiTuner: Hierarchical Semantic Fusion Model Fine-Tuning on Text-Attributed Graphs","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360376","doi":"https://doi.org/10.24963/ijcai.2025/569"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/569","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062894864","display_name":"Zihan Fang","orcid":"https://orcid.org/0000-0003-2009-9039"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zihan Fang","raw_affiliation_strings":["Fuzhou University"],"affiliations":[{"raw_affiliation_string":"Fuzhou University","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100939081","display_name":"Zhiling Cai","orcid":"https://orcid.org/0000-0002-7856-862X"},"institutions":[{"id":"https://openalex.org/I61057504","display_name":"Fujian Agriculture and Forestry University","ror":"https://ror.org/04kx2sy84","country_code":"CN","type":"education","lineage":["https://openalex.org/I61057504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiling Cai","raw_affiliation_strings":["Fujian Agriculture and Forestry University"],"affiliations":[{"raw_affiliation_string":"Fujian Agriculture and Forestry University","institution_ids":["https://openalex.org/I61057504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055771541","display_name":"Yuxuan Zheng","orcid":"https://orcid.org/0000-0001-5096-8915"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Zheng","raw_affiliation_strings":["Fuzhou University"],"affiliations":[{"raw_affiliation_string":"Fuzhou University","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091188575","display_name":"Shide Du","orcid":"https://orcid.org/0000-0002-6354-4705"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shide Du","raw_affiliation_strings":["Fuzhou University"],"affiliations":[{"raw_affiliation_string":"Fuzhou University","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083137715","display_name":"Yanchao Tan","orcid":"https://orcid.org/0000-0002-3526-6859"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanchao Tan","raw_affiliation_strings":["Fuzhou University"],"affiliations":[{"raw_affiliation_string":"Fuzhou University","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100604233","display_name":"Shiping Wang","orcid":"https://orcid.org/0009-0009-9153-8415"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiping Wang","raw_affiliation_strings":["Fuzhou University"],"affiliations":[{"raw_affiliation_string":"Fuzhou University","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5062894864"],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13997143,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5110","last_page":"5117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8745999932289124,"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/T10028","display_name":"Topic Modeling","score":0.8745999932289124,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.8101999759674072,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.7864000201225281,"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/benchmark","display_name":"Benchmark (surveying)","score":0.48260000348091125},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4636000096797943},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46050000190734863},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.4586000144481659},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4528000056743622},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.428600013256073},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.42489999532699585},{"id":"https://openalex.org/keywords/interdependence","display_name":"Interdependence","score":0.41530001163482666},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.40220001339912415}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.744700014591217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.597000002861023},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4636000096797943},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46050000190734863},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.4586000144481659},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4528000056743622},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44110000133514404},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.428600013256073},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.42489999532699585},{"id":"https://openalex.org/C185874996","wikidata":"https://www.wikidata.org/wiki/Q269699","display_name":"Interdependence","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.40220001339912415},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3772999942302704},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37549999356269836},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.36719998717308044},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3402999937534332},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/569","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Text-Attributed":[0],"Graphs":[1],"(TAGs)":[2],"are":[3,181],"vital":[4],"for":[5,18,42,64,101,125],"modeling":[6,102],"entity":[7],"relationships":[8],"across":[9,166],"various":[10,170],"domains.":[11],"Graph":[12],"Neural":[13],"Networks":[14],"have":[15],"become":[16],"cornerstone":[17],"processing":[19],"graph":[20],"structures,":[21],"while":[22],"the":[23,73,96,126,139,149,161,173,176],"integration":[24],"of":[25,34,112,118,143,148,175],"text":[26],"attributes":[27],"remains":[28],"a":[29,79,116,131,155],"prominent":[30],"research.":[31],"The":[32],"development":[33],"Large":[35],"Language":[36,86],"Models":[37,87],"(LLMs)":[38],"provides":[39],"new":[40],"opportunities":[41],"advancing":[43],"textual":[44],"encoding":[45],"in":[46,52],"TAGs.":[47,103],"However,":[48],"LLMs":[49,144],"face":[50],"challenges":[51],"specialized":[53],"domains":[54,171],"due":[55],"to":[56,94,114,137,158],"their":[57],"limited":[58],"task-specific":[59,146],"knowledge,":[60],"and":[61,120],"fine-tuning":[62],"them":[63],"specific":[65],"tasks":[66],"demands":[67],"significant":[68],"resources.":[69],"To":[70],"cope":[71],"with":[72,89,145],"above":[74],"challenges,":[75],"we":[76,105],"propose":[77],"HiTuner,":[78],"novel":[80],"framework":[81],"that":[82],"leverages":[83],"fine-tuned":[84,150],"Pre-trained":[85],"(PLMs)":[88],"domain":[90],"expertise":[91],"as":[92,123],"tuner":[93],"enhance":[95],"hierarchical":[97,109],"LLM":[98,113],"contextualized":[99],"representations":[100],"Specifically,":[104],"first":[106],"strategically":[107],"select":[108],"hidden":[110],"states":[111],"form":[115],"set":[117],"diverse":[119],"complementary":[121],"descriptions":[122],"input":[124],"sparse":[127],"projection":[128],"operator.":[129],"Concurrently,":[130],"hybrid":[132],"representation":[133],"learning":[134],"is":[135],"developed":[136],"amalgamate":[138],"broad":[140],"linguistic":[141],"comprehension":[142],"insights":[147],"PLMs.":[151],"Finally,":[152],"HiTuner":[153],"employs":[154],"confidence":[156],"network":[157],"adaptively":[159],"fuse":[160],"semantically-augmented":[162],"representations.":[163],"Empirical":[164],"results":[165],"benchmark":[167],"datasets":[168],"spanning":[169],"validate":[172],"effectiveness":[174],"proposed":[177],"framework.":[178],"Our":[179],"codes":[180],"available":[182],"at:":[183],"https://github.com/ZihanFang11/HiTuner":[184]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
