{"id":"https://openalex.org/W7162106269","doi":"https://doi.org/10.48550/arxiv.2605.21822","title":"Implicit Safety Alignment from Crowd Preferences","display_name":"Implicit Safety Alignment from Crowd Preferences","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7162106269","doi":"https://doi.org/10.48550/arxiv.2605.21822"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.21822","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21822","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.21822","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136759251","display_name":"Qian Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Qian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136758501","display_name":"Daniel S. Brown","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brown, Daniel S.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.569599986076355,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.569599986076355,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.062300000339746475,"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":0.05700000002980232,"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/task","display_name":"Task (project management)","score":0.7128000259399414},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.6653000116348267},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5171999931335449},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4652999937534332},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.44749999046325684},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.4011000096797943}],"concepts":[{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7128000259399414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6851000189781189},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.6653000116348267},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5171999931335449},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.40400001406669617},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.37689998745918274},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26969999074935913},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.26660001277923584},{"id":"https://openalex.org/C142944206","wikidata":"https://www.wikidata.org/wiki/Q1786137","display_name":"Proactivity","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.2549000084400177},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.25099998712539673},{"id":"https://openalex.org/C2777488183","wikidata":"https://www.wikidata.org/wiki/Q6900510","display_name":"Safety monitoring","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.21822","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21822","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.21822","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21822","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6039025783538818,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reinforcement":[0],"Learning":[1],"from":[2,56,108],"Human":[3],"Feedback":[4],"(RLHF)":[5],"can":[6],"reveal":[7],"implicit":[8],"objectives":[9],"such":[10],"as":[11],"safety":[12,27,46,54,139,147,153,166],"considerations":[13],"that":[14,77,104,142],"go":[15],"beyond":[16],"task":[17,88,132,157],"completion.":[18],"In":[19],"this":[20],"work,":[21],"we":[22,95],"focus":[23],"on":[24],"the":[25],"common":[26],"criteria":[28,55],"embedded":[29],"in":[30],"crowd":[31,57,109],"preference":[32],"datasets,":[33],"where":[34],"different":[35],"users":[36],"may":[37],"express":[38],"distinct":[39],"preferences":[40,58,110],"or":[41],"objectives,":[42],"yet":[43],"follow":[44],"similar":[45],"principles.":[47],"Our":[48],"aim":[49],"is":[50],"to":[51,63,67,118,151,160],"discover":[52],"shared":[53,138],"and":[59,71,111,128,137],"then":[60],"transfer":[61],"them":[62,113],"downstream":[64,87,121],"RL":[65,126],"tasks":[66],"regularize":[68],"agent":[69],"behavior":[70],"enforce":[72],"safety.":[73],"We":[74],"first":[75],"show":[76],"direct":[78],"reward":[79,83],"combination-optimizing":[80],"a":[81,101,115,129],"preference-learned":[82],"model":[84],"together":[85],"with":[86,133,164],"rewards-has":[89],"inherent":[90],"limitations.":[91],"Motivated":[92],"by":[93],"this,":[94],"propose":[96],"Safe":[97],"Crowd":[98],"Preference-based":[99],"RL,":[100],"hierarchical":[102],"framework":[103],"extracts":[105],"safety-aligned":[106],"skills":[107],"composes":[112],"via":[114],"high-level":[116],"policy":[117],"safely":[119],"solve":[120],"tasks.":[122],"Experiments":[123],"across":[124],"safe":[125],"environments":[127],"preliminary":[130],"LLM-style":[131],"diverse":[134],"user":[135],"goals":[136],"constraints":[140],"demonstrate":[141],"our":[143],"approach":[144],"substantially":[145],"lowers":[146],"costs":[148],"without":[149],"access":[150],"explicit":[152],"rewards,":[154],"while":[155],"achieving":[156],"performance":[158],"comparable":[159],"oracle":[161],"methods":[162],"trained":[163],"ground-truth":[165],"signals.":[167]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-23T00:00:00"}
