{"id":"https://openalex.org/W7138420589","doi":"https://doi.org/10.1609/aaai.v40i5.37360","title":"ReACT: Reward-informed Autoregressive Decision CAD Transformer","display_name":"ReACT: Reward-informed Autoregressive Decision CAD Transformer","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138420589","doi":"https://doi.org/10.1609/aaai.v40i5.37360"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i5.37360","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37360","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.v40i5.37360","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129709859","display_name":"Yijie Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yijie Ding","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129734632","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-5553-3646"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129714828","display_name":"Haobo Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haobo Jiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129668438","display_name":"Jianmin Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianmin Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.55026455,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"5","first_page":"3614","last_page":"3622"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.746399998664856,"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":0.746399998664856,"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/T11159","display_name":"Manufacturing Process and Optimization","score":0.10830000042915344,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.05260000005364418,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.8260999917984009},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5127000212669373},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5033000111579895},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.39719998836517334},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.35339999198913574},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.33390000462532043},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.32499998807907104},{"id":"https://openalex.org/keywords/computer-aided-design","display_name":"Computer Aided Design","score":0.30880001187324524},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.3041999936103821}],"concepts":[{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.8260999917984009},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5767999887466431},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5127000212669373},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5033000111579895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47049999237060547},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4187000095844269},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.39719998836517334},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.35339999198913574},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33390000462532043},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C119823426","wikidata":"https://www.wikidata.org/wiki/Q184793","display_name":"Computer Aided Design","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.30090001225471497},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2842999994754791},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.28299999237060547},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28110000491142273},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.27459999918937683},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.2728999853134155},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26190000772476196},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i5.37360","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37360","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"},{"id":"pmh:oai:ojs.aaai.org:article/37360","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/37360","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/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i5.37360","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37360","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":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reconstructing":[0],"precise":[1],"CAD":[2,26,47,61,94,104,120,133,193],"modeling":[3],"sequences":[4],"from":[5],"point":[6,146],"clouds":[7],"remains":[8],"a":[9,30,37,64,123,130],"challenging":[10],"task,":[11],"especially":[12],"for":[13,45,152,175,197],"objects":[14,198],"with":[15,141,199],"complex":[16,200],"geometry":[17],"and":[18,68,110,172,184],"topology.":[19],"In":[20,126],"this":[21],"paper,":[22],"by":[23],"formulating":[24],"the":[25,60,89,102,117,182],"sequence":[27,48],"reconstruction":[28,154,194],"as":[29],"Markov":[31],"decision":[32,41],"process,":[33],"we":[34,128],"introduce":[35],"ReACT,":[36],"novel":[38,131],"Reward-informed":[39],"Autoregressive":[40],"Cad":[42],"Transformer":[43,62],"architecture":[44],"robust":[46],"prediction.":[49,155],"Beyond":[50],"previous":[51],"imitation-only":[52],"approaches,":[53],"our":[54,75],"key":[55],"innovation":[56],"is":[57,165],"to":[58,80,87,167],"frame":[59],"under":[63],"reinforcement":[65],"learning":[66,73],"paradigm":[67],"thereby":[69],"integrate":[70],"reward-inspired":[71],"heuristic":[72],"into":[74],"architecture.":[76],"This":[77],"allows":[78],"ReACT":[79,114,189],"effectively":[81],"leverage":[82],"shape-aware":[83],"long-term":[84],"reward":[85,163,177],"feedback":[86],"guide":[88],"inference":[90],"of":[91],"(nearly)":[92],"optimal":[93],"commands.":[95],"Specifically,":[96],"conditioned":[97],"on":[98,181],"past":[99],"tokens,":[100],"comprising":[101],"historical":[103],"states,":[105],"sketch-extrude":[106],"commands":[107,121],"(i.e.,":[108],"actions)":[109],"associated":[111],"geometric":[112,150],"rewards,":[113],"autoregressively":[115],"outputs":[116],"most":[118],"promising":[119],"in":[122],"causal":[124],"manner.":[125],"particular,":[127],"develop":[129],"scaffold-aware":[132],"state":[134],"representation":[135],"that":[136,188],"integrates":[137],"global":[138],"point-command":[139],"features":[140],"an":[142,157],"incrementally":[143],"constructed":[144],"surface":[145,170],"scaffold,":[147],"enabling":[148],"fine-grained":[149],"reasoning":[151],"subsequent":[153],"Moreover,":[156],"effective":[158],"local":[159],"barrel":[160],"points-guided":[161],"dense":[162],"function":[164],"designed":[166],"jointly":[168],"evaluate":[169],"fidelity":[171],"command":[173],"efficiency":[174],"reliable":[176],"guidance.":[178],"Extensive":[179],"evaluations":[180],"DeepCAD":[183],"Fusion360":[185],"benchmarks":[186],"demonstrate":[187],"can":[190],"achieve":[191],"superior":[192],"quality,":[195],"even":[196],"shapes.":[201]},"counts_by_year":[],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2026-03-18T00:00:00"}