{"id":"https://openalex.org/W4415538410","doi":"https://doi.org/10.1145/3746027.3755773","title":"Formula Spotting Based on Synergy Perception and Representation Mining","display_name":"Formula Spotting Based on Synergy Perception and Representation Mining","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415538410","doi":"https://doi.org/10.1145/3746027.3755773"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755773","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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/A5101975457","display_name":"Gang Pan","orcid":"https://orcid.org/0000-0003-2155-4689"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gang Pan","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029277121","display_name":"Hongen Liu","orcid":"https://orcid.org/0000-0002-7978-9424"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongen Liu","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101797290","display_name":"Di Sun","orcid":"https://orcid.org/0000-0003-2793-7066"},"institutions":[{"id":"https://openalex.org/I132369690","display_name":"Tianjin University of Science and Technology","ror":"https://ror.org/018rbtf37","country_code":"CN","type":"education","lineage":["https://openalex.org/I132369690"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Sun","raw_affiliation_strings":["College of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, China","institution_ids":["https://openalex.org/I132369690"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101975457"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17067329,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5160","last_page":"5168"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9879999756813049,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9879999756813049,"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/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.9854999780654907,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.983299970626831,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5131000280380249},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4869000017642975},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.4823000133037567},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.47049999237060547},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4586000144481659},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4584999978542328},{"id":"https://openalex.org/keywords/spotting","display_name":"Spotting","score":0.42010000348091125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39969998598098755},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.3709000051021576}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7271000146865845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6021999716758728},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5131000280380249},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4869000017642975},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.4823000133037567},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.47049999237060547},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4586000144481659},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4584999978542328},{"id":"https://openalex.org/C2779506182","wikidata":"https://www.wikidata.org/wiki/Q7580141","display_name":"Spotting","level":2,"score":0.42010000348091125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39969998598098755},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38920000195503235},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3686000108718872},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.3424000144004822},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3296000063419342},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.3262999951839447},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2791999876499176},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2703999876976013},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755773","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2072449446","https://openalex.org/W2170570264","https://openalex.org/W3044568500","https://openalex.org/W4200635795","https://openalex.org/W4387968009","https://openalex.org/W4402961917"],"related_works":[],"abstract_inverted_index":{"Formula":[0,119],"spotting":[1,205],"aims":[2],"to":[3,95,103,131,150,165],"simultaneously":[4,170],"detect":[5,27],"and":[6,20,28,51,66,83,112,138,190,211,216],"recognize":[7,30],"formulas":[8,111],"in":[9,14,99,171,183],"documents,":[10],"with":[11],"broad":[12],"applications":[13],"intelligent":[15],"document":[16],"parsing,":[17],"mathematical":[18],"reasoning,":[19],"more.":[21],"Although":[22],"existing":[23],"methods":[24],"that":[25],"first":[26,203],"then":[29],"have":[31],"achieved":[32],"prominent":[33],"results,":[34],"they":[35,200],"still":[36],"suffer":[37],"from":[38,41,47,54],"semantic":[39,45,85,136],"confusion":[40],"similar":[42,100],"character":[43,108],"structures,":[44],"loss":[46],"bounding":[48],"box":[49],"perturbation,":[50],"visual":[52,93,116,139],"interference":[53],"non-formula":[55],"regions.":[56],"To":[57,176,194],"address":[58],"these":[59],"issues,":[60],"we":[61,157],"propose":[62,158],"a":[63,118,133,159,172],"Synergy":[64],"Perception":[65],"Representation":[67,120],"Mining":[68,121],"Network.":[69],"This":[70,125],"network":[71,164],"facilitates":[72],"explicit":[73],"interaction":[74],"between":[75,135],"the":[76,80,84,88,106,143,147,152,163,178,195,202,214,219],"RoI":[77],"features":[78,86],"of":[79,87,110,146,154,180,197,218],"detection":[81],"module":[82,122,126],"recognition":[89],"module,":[90],"leveraging":[91],"additional":[92],"priors":[94,145],"distinguish":[96],"subtle":[97],"differences":[98],"characters.":[101],"Moreover,":[102],"better":[104],"perceive":[105],"boundary":[107],"structure":[109],"filter":[113],"out":[114],"irrelevant":[115],"interference,":[117],"is":[123,223],"proposed.":[124],"employs":[127],"progressive":[128],"attention":[129],"mining":[130],"achieve":[132],"complementarity":[134],"information":[137],"context":[140],"without":[141],"disrupting":[142],"linguistic":[144],"formulas.":[148],"Additionally,":[149],"enhance":[151],"efficiency":[153],"formula":[155,184,204],"decoding,":[156],"parallel":[160],"mask,":[161],"allowing":[162],"output":[166],"multiple":[167],"LaTeX":[168],"tokens":[169],"single":[173],"prediction":[174],"step.":[175],"evaluate":[177],"effectiveness":[179,217],"our":[181,198],"method":[182],"spotting,":[185],"two":[186],"novel":[187],"datasets:":[188],"Formula-7K":[189,210],"Exam-1K":[191,212],"are":[192,201],"established.":[193],"best":[196],"knowledge,":[199],"datasets.":[206],"Experimental":[207],"results":[208],"on":[209],"validate":[213],"generality":[215],"proposed":[220],"method.":[221],"Code":[222],"available":[224],"at":[225],"https://github.com/hongen123/SynRMFormer.":[226]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-25T00:00:00"}
