{"id":"https://openalex.org/W7161237666","doi":"https://doi.org/10.48550/arxiv.2605.14301","title":"Language-Induced Priors for Domain Adaptation","display_name":"Language-Induced Priors for Domain Adaptation","publication_year":2026,"publication_date":"2026-05-14","ids":{"openalex":"https://openalex.org/W7161237666","doi":"https://doi.org/10.48550/arxiv.2605.14301"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.14301","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14301","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.14301","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136195871","display_name":"Qiyuan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Qiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136241260","display_name":"Jiayu Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Jiayu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5075324117","display_name":"Raed Al Kontar","orcid":"https://orcid.org/0000-0002-4546-324X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kontar, Raed Al","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":false,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.47699999809265137,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.47699999809265137,"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/T12380","display_name":"Authorship Attribution and Profiling","score":0.10109999775886536,"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/T10028","display_name":"Topic Modeling","score":0.08250000327825546,"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/prior-probability","display_name":"Prior probability","score":0.618399977684021},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.5479000210762024},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.539900004863739},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5291000008583069},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4740000069141388},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4674000144004822},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4634999930858612},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4174000024795532},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.3785000145435333},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.37709999084472656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7145000100135803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6549000144004822},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.618399977684021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5501000285148621},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5479000210762024},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.539900004863739},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5291000008583069},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4740000069141388},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4634999930858612},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4174000024795532},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3785000145435333},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.37709999084472656},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.3691999912261963},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34540000557899475},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.32899999618530273},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.28290000557899475},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25699999928474426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.14301","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14301","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.14301","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14301","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Domain":[0],"adaptation":[1],"faces":[2],"a":[3,48,58,67,71,80,109,149,169,173,178],"fundamental":[4],"paradox":[5],"in":[6],"the":[7,45,77,115,119,140,158,161,166],"cold-start":[8,146],"regime.":[9],"When":[10],"target":[11,46,124],"data":[12],"is":[13,51,88,102,111],"scarce,":[14],"statistical":[15],"methods":[16],"fail":[17],"to":[18,29,95,117],"distinguish":[19],"relevant":[20],"source":[21,97],"domains":[22],"from":[23,79],"irrelevant":[24],"ones,":[25],"which":[26],"often":[27,52],"leads":[28],"negative":[30],"transfer.":[31],"In":[32],"this":[33,37,100],"paper,":[34],"we":[35,137,164],"address":[36],"challenge":[38],"by":[39],"leveraging":[40],"expert":[41],"textual":[42],"descriptions":[43,65],"of":[44,121,157,160],"domain,":[47],"resource":[49],"that":[50,61,75,139],"available":[53],"but":[54],"overlooked.":[55],"We":[56],"propose":[57],"probabilistic":[59],"framework":[60,101,167],"translates":[62],"these":[63,131],"semantic":[64],"into":[66,91],"choice":[68],"model,":[69],"namely":[70],"Language-Induced":[72],"Prior":[73],"(LIP),":[74],"learns":[76],"preferences":[78],"pretrained":[81],"Large":[82],"Language":[83],"Model":[84],"(LLM).":[85],"The":[86],"LIP":[87,116],"then":[89],"integrated":[90],"an":[92,144],"Expectation-Maximization":[93],"algorithm":[94],"identify":[96],"relevance.":[98],"Methodologically,":[99],"compatible":[103],"with":[104],"any":[105],"parametric":[106],"model":[107],"where":[108],"likelihood":[110],"available.":[112],"It":[113],"allows":[114],"guide":[118],"selection":[120],"sources":[122],"when":[123],"signals":[125],"are":[126],"weak,":[127],"while":[128,152],"gradually":[129],"refining":[130],"choices":[132],"as":[133],"samples":[134],"accumulate.":[135],"Theoretically,":[136],"prove":[138],"estimator":[141],"roughly":[142],"matches":[143],"oracle":[145],"MSE":[147],"under":[148],"correct":[150],"prior,":[151],"remaining":[153],"asymptotically":[154],"consistent":[155],"regardless":[156],"quality":[159],"LIP.":[162],"Empirically,":[163],"validated":[165],"on":[168],"descriptive":[170],"(Gaussian":[171],"estimation),":[172],"predictive":[174],"(C-MAPSS":[175],"dataset),":[176],"and":[177],"prescriptive":[179],"task":[180],"(MuJoCo":[181],"hopper).":[182]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-16T00:00:00"}
