{"id":"https://openalex.org/W7161289155","doi":"https://doi.org/10.48550/arxiv.2605.14746","title":"Selective Safety Steering via Value-Filtered Decoding","display_name":"Selective Safety Steering via Value-Filtered Decoding","publication_year":2026,"publication_date":"2026-05-14","ids":{"openalex":"https://openalex.org/W7161289155","doi":"https://doi.org/10.48550/arxiv.2605.14746"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.14746","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14746","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":null,"license_id":null,"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.2605.14746","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053551032","display_name":"Bat-Sheva Einbinder","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Einbinder, Bat-Sheva","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119967943","display_name":"Hen Davidov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Davidov, Hen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136260572","display_name":"Yee Whye Teh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Teh, Yee Whye","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029186201","display_name":"Yarin Gal","orcid":"https://orcid.org/0000-0002-2733-2078"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gal, Yarin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136234671","display_name":"Yaniv Romano","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Romano, Yaniv","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.19910000264644623,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.19910000264644623,"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":0.18250000476837158,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.1225999966263771,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.8100000023841858},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6183000206947327},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4918000102043152},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.3917999863624573},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.3625999987125397},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.3587000072002411},{"id":"https://openalex.org/keywords/psychological-intervention","display_name":"Psychological intervention","score":0.3416000008583069},{"id":"https://openalex.org/keywords/system-safety","display_name":"System safety","score":0.33379998803138733}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.8100000023841858},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6775000095367432},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6183000206947327},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4918000102043152},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3917999863624573},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3625999987125397},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.3587000072002411},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3513000011444092},{"id":"https://openalex.org/C27415008","wikidata":"https://www.wikidata.org/wiki/Q7256382","display_name":"Psychological intervention","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C132835097","wikidata":"https://www.wikidata.org/wiki/Q7663745","display_name":"System safety","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C193969084","wikidata":"https://www.wikidata.org/wiki/Q7452500","display_name":"Sequential decoding","level":4,"score":0.3086000084877014},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2890999913215637},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.2833000123500824},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2818000018596649},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26969999074935913},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.14746","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14746","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.14746","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14746","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":null,"license_id":null,"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":{"While":[0],"large":[1],"language":[2],"models":[3],"(LLMs)":[4],"are":[5,62],"trained":[6],"to":[7,89,130,165],"align":[8],"with":[9],"human":[10],"values,":[11],"their":[12],"generations":[13,49],"may":[14],"still":[15],"violate":[16],"safety":[17,38,97,108],"constraints.":[18],"A":[19,121],"growing":[20],"line":[21],"of":[22,70,98,118,135],"work":[23],"addresses":[24],"this":[25,126],"problem":[26],"by":[27],"modifying":[28,48],"the":[29,56,71,96,116,166],"model's":[30],"sampling":[31],"policy":[32],"at":[33],"decoding":[34,152],"time":[35],"using":[36,105],"a":[37,83,106],"reward.":[39],"However,":[40],"existing":[41,155],"decoding-time":[42],"steering":[43,86],"methods":[44],"often":[45],"intervene":[46],"unnecessarily,":[47],"that":[50,149],"would":[51],"have":[52],"been":[53],"safe":[54],"under":[55],"base":[57,72,167],"model.":[58,168],"Such":[59],"unnecessary":[60,92,136],"interventions":[61,93],"undesirable,":[63],"as":[64,75],"they":[65],"can":[66],"distort":[67],"key":[68],"properties":[69],"model":[73],"such":[74,91],"helpfulness,":[76,162],"fluency,":[77],"style,":[78],"and":[79,110,145,163],"coherence.":[80],"We":[81],"propose":[82],"new":[84],"test-time":[85],"method":[87,153],"designed":[88],"reduce":[90],"while":[94],"improving":[95],"unsafe":[99],"responses.":[100],"Our":[101],"approach":[102],"filters":[103],"tokens":[104],"value-based":[107],"criterion":[109],"provides":[111],"an":[112],"explicit":[113],"bound":[114],"on":[115],"probability":[117],"false":[119],"interventions.":[120],"single":[122],"threshold":[123],"hyperparameter":[124],"controls":[125],"bound,":[127],"allowing":[128],"practitioners":[129],"trade":[131],"off":[132],"higher":[133],"rates":[134],"intervention":[137],"for":[138],"better":[139,158],"output":[140],"safety.":[141],"Across":[142],"multiple":[143],"datasets":[144],"experiments,":[146],"we":[147],"show":[148],"our":[150],"value-filtered":[151],"outperforms":[154],"baselines,":[156],"achieving":[157],"trade-offs":[159],"between":[160],"safety,":[161],"similarity":[164]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-16T00:00:00"}
