{"id":"https://openalex.org/W4408352525","doi":"https://doi.org/10.1109/icassp49660.2025.10890013","title":"Enhancing Complex Formula Recognition with Hierarchical Detail-Focused Network","display_name":"Enhancing Complex Formula Recognition with Hierarchical Detail-Focused Network","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408352525","doi":"https://doi.org/10.1109/icassp49660.2025.10890013"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10890013","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890013","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5023838434","display_name":"Jiale Wang","orcid":"https://orcid.org/0009-0006-6413-8289"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiale Wang","raw_affiliation_strings":["360 AI Research Institute,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"360 AI Research Institute,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100755390","display_name":"Junhui Yu","orcid":"https://orcid.org/0000-0002-6685-0505"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junhui Yu","raw_affiliation_strings":["360 AI Research Institute,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"360 AI Research Institute,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000944156","display_name":"Huanyong Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huanyong Liu","raw_affiliation_strings":["360 AI Research Institute,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"360 AI Research Institute,China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Chenanran Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenanran Kong","raw_affiliation_strings":["Chinese University of Hong Kong (Shenzhen),China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese University of Hong Kong (Shenzhen),China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05760055,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.909600019454956,"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"}},"topics":[{"id":"https://openalex.org/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.909600019454956,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9020000100135803,"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/computer-science","display_name":"Computer science","score":0.7317937016487122},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3946497142314911}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7317937016487122},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3946497142314911}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10890013","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890013","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":14,"referenced_works":["https://openalex.org/W2005079280","https://openalex.org/W2037121285","https://openalex.org/W2623860192","https://openalex.org/W2971475692","https://openalex.org/W3004196288","https://openalex.org/W3108675651","https://openalex.org/W3159162875","https://openalex.org/W4200635795","https://openalex.org/W4221013561","https://openalex.org/W4312868947","https://openalex.org/W4402951581","https://openalex.org/W6739901393","https://openalex.org/W6784333009","https://openalex.org/W6864710712"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Hierarchical":[0,28,98],"and":[1,20,54],"complex":[2,71,83],"Mathematical":[3],"Expression":[4],"Recognition":[5,30,100],"(MER)":[6],"is":[7],"challenging":[8],"due":[9],"to":[10,38],"multiple":[11,68],"possible":[12],"interpretations":[13,69],"of":[14,44,70,82,117],"a":[15,45,108],"formula,":[16],"complicating":[17],"both":[18],"parsing":[19,81],"evaluation.":[21,78],"In":[22],"this":[23],"paper,":[24],"we":[25,95],"introduce":[26],"the":[27,33,63,80,97,114],"Detail-Focused":[29,99],"dataset":[31,35],"(HDR),":[32],"first":[34],"specifically":[36],"designed":[37],"address":[39,93],"these":[40],"issues.":[41],"It":[42],"consists":[43],"large-scale":[46],"training":[47,60],"set,":[48,65],"HDR-100M,":[49],"offering":[50],"an":[51,103],"unprecedented":[52],"scale":[53],"diversity":[55],"with":[56],"one":[57],"hundred":[58],"million":[59],"instances.":[61],"And":[62],"test":[64],"HDR-Test,":[66],"includes":[67],"hierarchical":[72,109],"formulas":[73,84],"for":[74],"comprehensive":[75],"model":[76],"performance":[77],"Additionally,":[79],"often":[85],"suffers":[86],"from":[87],"errors":[88],"in":[89],"fine-grained":[90],"details.":[91],"To":[92],"this,":[94],"propose":[96],"Network":[101],"(HDNet),":[102],"innovative":[104],"framework":[105],"that":[106,128],"incorporates":[107],"sub-formula":[110],"module,":[111],"focusing":[112],"on":[113],"precise":[115],"handling":[116],"formula":[118],"details,":[119],"thereby":[120],"significantly":[121],"enhancing":[122],"MER":[123,132],"performance.":[124],"Experimental":[125],"results":[126],"demonstrate":[127],"HDNet":[129],"outperforms":[130],"existing":[131],"models":[133],"across":[134],"various":[135],"datasets.":[136]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}