{"id":"https://openalex.org/W7138351882","doi":"https://doi.org/10.1609/aaai.v40i32.39920","title":"Learning to Generate Structured Meshes with In-Context: Toward Generalization in Mesh Generation","display_name":"Learning to Generate Structured Meshes with In-Context: Toward Generalization in Mesh Generation","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138351882","doi":"https://doi.org/10.1609/aaai.v40i32.39920"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i32.39920","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i32.39920","pdf_url":null,"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://doi.org/10.1609/aaai.v40i32.39920","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129694621","display_name":"Jing Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jing Xiao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129670973","display_name":"Xinhai Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinhai Chen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129656989","display_name":"Jiaming Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiaming Peng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129648671","display_name":"Jie Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jie Liu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5129694621"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.76335878,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"32","first_page":"27064","last_page":"27072"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.8539999723434448,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.8539999723434448,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10996","display_name":"Computational Geometry and Mesh Generation","score":0.11069999635219574,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.00559999980032444,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/polygon-mesh","display_name":"Polygon mesh","score":0.6348999738693237},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6229000091552734},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5666999816894531},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5307000279426575},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5101000070571899},{"id":"https://openalex.org/keywords/structured-prediction","display_name":"Structured prediction","score":0.4896000027656555},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4187000095844269},{"id":"https://openalex.org/keywords/mesh-generation","display_name":"Mesh generation","score":0.3547999858856201}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7224000096321106},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.6348999738693237},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6229000091552734},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5666999816894531},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5307000279426575},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5101000070571899},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.4896000027656555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4375},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4302999973297119},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40860000252723694},{"id":"https://openalex.org/C181145010","wikidata":"https://www.wikidata.org/wiki/Q4418033","display_name":"Mesh generation","level":3,"score":0.3547999858856201},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C160403270","wikidata":"https://www.wikidata.org/wiki/Q7667943","display_name":"T-vertices","level":4,"score":0.32910001277923584},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C2779521785","wikidata":"https://www.wikidata.org/wiki/Q5535529","display_name":"Geometry processing","level":3,"score":0.31029999256134033},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30809998512268066},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C176032523","wikidata":"https://www.wikidata.org/wiki/Q753127","display_name":"Topological sorting","level":3,"score":0.27129998803138733},{"id":"https://openalex.org/C131053463","wikidata":"https://www.wikidata.org/wiki/Q4680751","display_name":"Adaptive mesh refinement","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i32.39920","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i32.39920","pdf_url":null,"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"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i32.39920","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i32.39920","pdf_url":null,"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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Structured":[0],"mesh":[1,72,145,149],"generation":[2,146],"serves":[3],"as":[4,16,79],"a":[5,17,62,84,122],"crucial":[6],"preprocessing":[7],"step":[8],"in":[9],"numerical":[10],"simulations":[11],"and":[12,41,82,93,126,139,151],"can":[13,140],"be":[14,141],"formulated":[15],"mapping":[18,31,78],"problem":[19],"from":[20,95],"geometry":[21],"to":[22,39,88,104,117,134,143],"structured":[23,71],"mesh.":[24],"Existing":[25],"approaches":[26],"typically":[27],"establish":[28],"an":[29],"isolated":[30],"for":[32,52,70],"each":[33,99],"geometry.":[34],"This":[35],"geometry-specific":[36],"paradigm":[37],"fails":[38],"capture":[40],"leverage":[42],"commonalities":[43,90],"across":[44,91],"geometries,":[45],"inevitably":[46],"requiring":[47],"recomputation":[48],"or":[49],"costly":[50],"retraining":[51],"new":[53],"geometries.":[54],"To":[55],"overcome":[56],"this":[57],"limitation,":[58],"we":[59],"propose":[60],"ICL-Mesh,":[61],"meta-learning":[63],"framework":[64],"based":[65],"on":[66],"in-context":[67,96,135],"learning":[68,76],"(ICL)":[69],"generation.":[73],"It":[74,130],"treats":[75],"one":[77,80],"task":[81],"trains":[83],"single":[85],"neural":[86],"network":[87],"extract":[89],"tasks":[92,106],"learn":[94],"examples":[97],"within":[98],"task,":[100],"enabling":[101],"rapid":[102],"generalization":[103],"unseen":[105],"without":[107,128],"parameter":[108],"updates.":[109],"Experimental":[110],"results":[111],"demonstrate":[112],"that":[113],"ICL-Mesh":[114],"effectively":[115],"generalizes":[116],"diverse":[118],"geometries":[119],"with":[120],"only":[121],"few":[123],"context":[124],"examples,":[125],"even":[127],"examples.":[129],"also":[131],"exhibits":[132],"robustness":[133],"example":[136],"order":[137],"sensitivity":[138],"extended":[142],"various":[144],"scenarios,":[147],"including":[148],"refinement":[150],"coarsening.":[152]},"counts_by_year":[],"updated_date":"2026-03-18T06:31:55.123368","created_date":"2026-03-18T00:00:00"}