{"id":"https://openalex.org/W4290874975","doi":"https://doi.org/10.1145/3534678.3539206","title":"GradMask","display_name":"GradMask","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4290874975","doi":"https://doi.org/10.1145/3534678.3539206"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539206","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539206","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5051378764","display_name":"Han Cheol Moon","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Han Cheol Moon","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005443526","display_name":"Shafiq Joty","orcid":"https://orcid.org/0000-0002-9222-2641"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shafiq Joty","raw_affiliation_strings":["Nanyang Technological University &amp; Salesforce Research, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University &amp; Salesforce Research, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031630884","display_name":"Xu Chi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]},{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xu Chi","raw_affiliation_strings":["Nanyang Technological University &amp; Singapore Institute of Manufacturing Technology, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University &amp; Singapore Institute of Manufacturing Technology, Singapore, Singapore","institution_ids":["https://openalex.org/I4210091207","https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051378764"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.6263,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.67445805,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3603","last_page":"3613"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"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":0.9979000091552734,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9926999807357788,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9866999983787537,"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":0.850519061088562},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7047700881958008},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6529110074043274},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5751793384552002},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5705196857452393},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5587719082832336},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5374358892440796},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4992358684539795},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.48317375779151917},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4361759126186371},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42799150943756104},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.41521376371383667},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09992817044258118}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.850519061088562},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7047700881958008},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6529110074043274},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5751793384552002},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5705196857452393},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5587719082832336},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5374358892440796},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4992358684539795},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.48317375779151917},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4361759126186371},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42799150943756104},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.41521376371383667},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09992817044258118},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534678.3539206","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539206","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1490960179","https://openalex.org/W1583837637","https://openalex.org/W2038721957","https://openalex.org/W2163455955","https://openalex.org/W2559655401","https://openalex.org/W2560674852","https://openalex.org/W2612690371","https://openalex.org/W2750779823","https://openalex.org/W2799194071","https://openalex.org/W2949128310","https://openalex.org/W2962718684","https://openalex.org/W2963846996","https://openalex.org/W2964159778","https://openalex.org/W2982756474","https://openalex.org/W3014773921","https://openalex.org/W3015001695","https://openalex.org/W3023553115","https://openalex.org/W3035441470","https://openalex.org/W3099126561","https://openalex.org/W3101118213","https://openalex.org/W3104423855","https://openalex.org/W3155936402","https://openalex.org/W3173596483","https://openalex.org/W3176143090","https://openalex.org/W3176703834","https://openalex.org/W4212774754","https://openalex.org/W4238846128","https://openalex.org/W4239019441"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W2482350142","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W3089357417"],"abstract_inverted_index":{"We":[0],"present":[1],"GradMask,":[2],"a":[3,33,54,67],"simple":[4],"adversarial":[5],"example":[6],"detection":[7,45,80],"scheme":[8],"for":[9],"natural":[10],"language":[11],"processing":[12],"(NLP)":[13],"models.":[14],"It":[15],"uses":[16],"gradient":[17],"signals":[18],"to":[19],"detect":[20],"adversarially":[21],"perturbed":[22],"tokens":[23,31],"in":[24],"an":[25,48],"input":[26],"sequence":[27],"and":[28,47,70,93,98],"occludes":[29],"such":[30],"by":[32],"masking":[34],"process.":[35],"GradMask":[36],"provides":[37],"several":[38],"advantages":[39],"over":[40],"existing":[41],"methods":[42],"including":[43],"improved":[44],"performance":[46],"interpretation":[49],"of":[50,95],"its":[51],"decision":[52],"with":[53],"only":[55],"moderate":[56],"computational":[57],"cost.":[58],"Its":[59],"approximated":[60],"inference":[61],"cost":[62],"is":[63],"no":[64],"more":[65],"than":[66],"single":[68],"forward-":[69],"back-propagation":[71],"through":[72],"the":[73,91],"target":[74],"model":[75],"without":[76],"requiring":[77],"any":[78],"additional":[79],"module.":[81],"Extensive":[82],"evaluation":[83],"on":[84],"widely":[85],"adopted":[86],"NLP":[87],"benchmark":[88],"datasets":[89],"demonstrates":[90],"efficiency":[92],"effectiveness":[94],"GradMask.":[96],"Code":[97],"models":[99],"are":[100],"available":[101],"at":[102],"https://github.com/Han8931/grad_mask_detection":[103]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2022-08-12T00:00:00"}
