{"id":"https://openalex.org/W4408354210","doi":"https://doi.org/10.1109/icassp49660.2025.10888381","title":"Improving Robustness of Post-hoc Calibration Against Common Corruptions By Learnable Augmentation","display_name":"Improving Robustness of Post-hoc Calibration Against Common Corruptions By Learnable Augmentation","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408354210","doi":"https://doi.org/10.1109/icassp49660.2025.10888381"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10888381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888381","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/A5007781850","display_name":"Jun Jason Zhang","orcid":"https://orcid.org/0000-0001-6908-2671"},"institutions":[{"id":"https://openalex.org/I4210158522","display_name":"PLA Academy of Military Science","ror":"https://ror.org/05ct4s596","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210158522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["Center of Information Research, AMS,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Information Research, AMS,Beijing,China","institution_ids":["https://openalex.org/I4210158522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101814775","display_name":"Minghao Hu","orcid":"https://orcid.org/0000-0002-8573-7110"},"institutions":[{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghao Hu","raw_affiliation_strings":["Advanced Institute of Big Data,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Institute of Big Data,Beijing,China","institution_ids":["https://openalex.org/I4210096250"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101037209","display_name":"Zhunchen Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhunchen Luo","raw_affiliation_strings":["Information Research Center of Military Science,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Research Center of Military Science,Beijing,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090419741","display_name":"Wei Luo","orcid":"https://orcid.org/0000-0002-4711-7543"},"institutions":[{"id":"https://openalex.org/I4210158522","display_name":"PLA Academy of Military Science","ror":"https://ror.org/05ct4s596","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210158522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Luo","raw_affiliation_strings":["Center of Information Research, AMS,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Information Research, AMS,Beijing,China","institution_ids":["https://openalex.org/I4210158522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070742322","display_name":"Guotong Geng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158522","display_name":"PLA Academy of Military Science","ror":"https://ror.org/05ct4s596","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210158522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guotong Geng","raw_affiliation_strings":["Center of Information Research, AMS,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Information Research, AMS,Beijing,China","institution_ids":["https://openalex.org/I4210158522"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102780884","display_name":"Xiaoyin Bai","orcid":"https://orcid.org/0000-0002-6625-5052"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoyin Bai","raw_affiliation_strings":["AIBD,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AIBD,Beijing,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.8069000244140625,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.8069000244140625,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.7742000222206116,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.7087000012397766,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/robustness","display_name":"Robustness (evolution)","score":0.8079855442047119},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6217149496078491},{"id":"https://openalex.org/keywords/post-hoc","display_name":"Post hoc","score":0.6184098124504089},{"id":"https://openalex.org/keywords/post-hoc-analysis","display_name":"Post-hoc analysis","score":0.49761179089546204},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3332849144935608},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21636849641799927},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1691194474697113},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.11459341645240784},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.047955483198165894}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8079855442047119},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6217149496078491},{"id":"https://openalex.org/C2992886853","wikidata":"https://www.wikidata.org/wiki/Q18381816","display_name":"Post hoc","level":2,"score":0.6184098124504089},{"id":"https://openalex.org/C67761136","wikidata":"https://www.wikidata.org/wiki/Q2105849","display_name":"Post-hoc analysis","level":2,"score":0.49761179089546204},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3332849144935608},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21636849641799927},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1691194474697113},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.11459341645240784},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.047955483198165894},{"id":"https://openalex.org/C199343813","wikidata":"https://www.wikidata.org/wiki/Q12128","display_name":"Dentistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10888381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888381","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":[{"id":"https://metadata.un.org/sdg/16","score":0.7799999713897705,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2051434435","https://openalex.org/W2108598243","https://openalex.org/W2160815625","https://openalex.org/W2194775991","https://openalex.org/W2254249950","https://openalex.org/W2581082771","https://openalex.org/W2964003311","https://openalex.org/W2964059111","https://openalex.org/W3037492894","https://openalex.org/W3175506488","https://openalex.org/W4391446036","https://openalex.org/W6637373629","https://openalex.org/W6684809622","https://openalex.org/W6730042731","https://openalex.org/W6739651123","https://openalex.org/W6739901393","https://openalex.org/W6751754606","https://openalex.org/W6757555829","https://openalex.org/W6763087592","https://openalex.org/W6786212429","https://openalex.org/W6787972765","https://openalex.org/W6799319297"],"related_works":["https://openalex.org/W2182025991","https://openalex.org/W4391247400","https://openalex.org/W1973035946","https://openalex.org/W2087491399","https://openalex.org/W2111390454","https://openalex.org/W4383421632","https://openalex.org/W3014788916","https://openalex.org/W2995377144","https://openalex.org/W4378639993","https://openalex.org/W4383382866"],"abstract_inverted_index":{"Various":[0],"research":[1],"has":[2,44],"addressed":[3],"the":[4,12,22,27,38,63,69,90,96],"overconfidence":[5],"problem,":[6],"and":[7,82,99,110],"we":[8,60],"focus":[9],"on":[10,68,104],"improving":[11],"robustness":[13],"of":[14,107],"post-hoc":[15],"calibration":[16,53,118],"(e.g.,":[17],"temperature":[18],"scaling,":[19],"TS)":[20],"when":[21],"test":[23,101],"set":[24,29,71],"shifts":[25,121],"from":[26],"training":[28],"by":[30,37,48,58],"image":[31],"corruption.":[32],"TS":[33,74,85],"is":[34],"greatly":[35],"affected":[36],"validation":[39,70,98],"set,":[40],"which":[41,88],"previous":[42],"work":[43],"proposed":[45,79],"to":[46,51],"perturb":[47],"Gaussian":[49],"noise":[50],"improve":[52,117],"under":[54,75,119],"domain":[55],"drift.":[56],"Inspired":[57],"this,":[59],"discovered":[61],"that":[62,113],"same":[64],"or":[65],"similar":[66],"augmentation":[67],"substantially":[72],"improved":[73],"corrupted":[76,100,105,120],"shift.":[77],"We":[78],"a":[80],"learnable":[81],"dynamic":[83],"augmentation-based":[84],"method,":[86],"AugTS,":[87],"minimizes":[89],"maximum":[91],"mean":[92],"discrepancy":[93],"(MMD)":[94],"between":[95],"augmented":[97],"set.":[102],"Experiments":[103],"versions":[106],"CIFAR-10,":[108],"CIFAR-100,":[109],"TinyImageNet":[111],"show":[112],"AugTS":[114],"can":[115],"significantly":[116],"compared":[122],"with":[123],"competitive":[124],"baselines.":[125]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
