{"id":"https://openalex.org/W4414969892","doi":"https://doi.org/10.48550/arxiv.2510.03839","title":"Technical note on Sequential Test-Time Adaptation via Martingale-Driven Fisher Prompting","display_name":"Technical note on Sequential Test-Time Adaptation via Martingale-Driven Fisher Prompting","publication_year":2025,"publication_date":"2025-10-04","ids":{"openalex":"https://openalex.org/W4414969892","doi":"https://doi.org/10.48550/arxiv.2510.03839"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2510.03839","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2510.03839","pdf_url":"https://arxiv.org/pdf/2510.03839","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.03839","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085502049","display_name":"Behraj Khan","orcid":"https://orcid.org/0000-0003-0985-9543"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Behraj","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5004232654","display_name":"Tahir Syed","orcid":"https://orcid.org/0000-0003-0638-9689"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Syed, Tahir Qasim","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":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11236","display_name":"Control Systems and Identification","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9641000032424927,"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/kullback\u2013leibler-divergence","display_name":"Kullback\u2013Leibler divergence","score":0.5863000154495239},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5493000149726868},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5340999960899353},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.5259000062942505},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5253000259399414},{"id":"https://openalex.org/keywords/martingale","display_name":"Martingale (probability theory)","score":0.44839999079704285},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4262000024318695},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.39989998936653137},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.3953999876976013}],"concepts":[{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.5863000154495239},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5493000149726868},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5340999960899353},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.5259000062942505},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5253000259399414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49239999055862427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45820000767707825},{"id":"https://openalex.org/C48406656","wikidata":"https://www.wikidata.org/wiki/Q534112","display_name":"Martingale (probability theory)","level":2,"score":0.44839999079704285},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4262000024318695},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.39989998936653137},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.3953999876976013},{"id":"https://openalex.org/C55974624","wikidata":"https://www.wikidata.org/wiki/Q1188504","display_name":"Exponential family","level":2,"score":0.385699987411499},{"id":"https://openalex.org/C55350006","wikidata":"https://www.wikidata.org/wiki/Q237193","display_name":"Exponential distribution","level":2,"score":0.3837999999523163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37229999899864197},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.36730000376701355},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.34610000252723694},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3314000070095062},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3287000060081482},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C29406490","wikidata":"https://www.wikidata.org/wiki/Q1420659","display_name":"Fisher information","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C96608239","wikidata":"https://www.wikidata.org/wiki/Q1199823","display_name":"Statistical power","level":2,"score":0.2992999851703644},{"id":"https://openalex.org/C178518018","wikidata":"https://www.wikidata.org/wiki/Q1024555","display_name":"CUSUM","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2651999890804291}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2510.03839","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2510.03839","pdf_url":"https://arxiv.org/pdf/2510.03839","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2510.03839","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.03839","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.03839","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2510.03839","pdf_url":"https://arxiv.org/pdf/2510.03839","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414969892.pdf","grobid_xml":"https://content.openalex.org/works/W4414969892.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,7,113],"theoretical":[3],"framework":[4],"for":[5,9,116],"M-FISHER,":[6],"method":[8],"sequential":[10,125],"distribution":[11],"shift":[12],"detection":[13,57,70,119],"and":[14,30,104,120],"stable":[15,122],"adaptation":[16,123],"in":[17,124],"streaming":[18],"data.":[19],"For":[20,75],"detection,":[21],"we":[22,52,77],"construct":[23],"an":[24],"exponential":[25],"martingale":[26],"from":[27],"non-conformity":[28],"scores":[29],"apply":[31],"Ville's":[32],"inequality":[33],"to":[34,72],"obtain":[35],"time-uniform":[36],"guarantees":[37],"on":[38,89],"false":[39],"alarm":[40],"control,":[41],"ensuring":[42],"statistical":[43],"validity":[44],"at":[45],"any":[46],"stopping":[47],"time.":[48],"Under":[49],"sustained":[50],"shifts,":[51],"further":[53],"bound":[54],"the":[55,64,90],"expected":[56],"delay":[58],"as":[59,112],"$\\mathcal{O}(\\log(1/\u03b4)/\u0393)$,":[60],"where":[61],"$\u0393$":[62],"reflects":[63],"post-shift":[65],"information":[66],"gain,":[67],"thereby":[68],"linking":[69],"efficiency":[71],"distributional":[73,91],"divergence.":[74],"adaptation,":[76],"show":[78],"that":[79,97],"Fisher-preconditioned":[80],"updates":[81,96],"of":[82],"prompt":[83],"parameters":[84],"implement":[85],"natural":[86],"gradient":[87],"descent":[88],"manifold,":[92],"yielding":[93],"locally":[94],"optimal":[95],"minimize":[98],"KL":[99],"divergence":[100],"while":[101],"preserving":[102],"stability":[103],"parameterization":[105],"invariance.":[106],"Together,":[107],"these":[108],"results":[109],"establish":[110],"M-FISHER":[111],"principled":[114],"approach":[115],"robust,":[117],"anytime-valid":[118],"geometrically":[121],"decision-making":[126],"under":[127],"covariate":[128],"shift.":[129]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-09T00:00:00"}
