{"id":"https://openalex.org/W7159679665","doi":"https://doi.org/10.48550/arxiv.2604.28182","title":"Exploration Hacking: Can LLMs Learn to Resist RL Training?","display_name":"Exploration Hacking: Can LLMs Learn to Resist RL Training?","publication_year":2026,"publication_date":"2026-04-30","ids":{"openalex":"https://openalex.org/W7159679665","doi":"https://doi.org/10.48550/arxiv.2604.28182"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.28182","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.28182","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.2604.28182","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128038265","display_name":"Eyon Jang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jang, Eyon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073889108","display_name":"Damon Falck","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Falck, Damon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134943822","display_name":"Joschka Braun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Braun, Joschka","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120380988","display_name":"Nathalie Kirch","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kirch, Nathalie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134960105","display_name":"Achu Menon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Menon, Achu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134933948","display_name":"Perusha Moodley","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moodley, Perusha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051005226","display_name":"Scott Emmons","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Emmons, Scott","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102706612","display_name":"R. Zimmermann","orcid":"https://orcid.org/0000-0001-8790-1618"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zimmermann, Roland S.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134941045","display_name":"David Lindner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lindner, David","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/T10028","display_name":"Topic Modeling","score":0.1298000067472458,"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/T10028","display_name":"Topic Modeling","score":0.1298000067472458,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.1225999966263771,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1023000031709671,"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/variety","display_name":"Variety (cybernetics)","score":0.6003999710083008},{"id":"https://openalex.org/keywords/biosecurity","display_name":"Biosecurity","score":0.5777999758720398},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5756000280380249},{"id":"https://openalex.org/keywords/resistance","display_name":"Resistance (ecology)","score":0.43970000743865967},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.35190001130104065},{"id":"https://openalex.org/keywords/hacker","display_name":"Hacker","score":0.30630001425743103}],"concepts":[{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6003999710083008},{"id":"https://openalex.org/C2781368420","wikidata":"https://www.wikidata.org/wiki/Q803874","display_name":"Biosecurity","level":2,"score":0.5777999758720398},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5756000280380249},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.5230000019073486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5194000005722046},{"id":"https://openalex.org/C57473165","wikidata":"https://www.wikidata.org/wiki/Q7315604","display_name":"Resistance (ecology)","level":2,"score":0.43970000743865967},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39899998903274536},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C86844869","wikidata":"https://www.wikidata.org/wiki/Q2798820","display_name":"Hacker","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C2778571376","wikidata":"https://www.wikidata.org/wiki/Q1355821","display_name":"Frontier","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28870001435279846},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2784999907016754},{"id":"https://openalex.org/C113336015","wikidata":"https://www.wikidata.org/wiki/Q574010","display_name":"Complete information","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.25839999318122864}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.28182","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.28182","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.2604.28182","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.28182","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reinforcement":[0],"learning":[1],"(RL)":[2],"has":[3],"become":[4],"essential":[5],"to":[6,49,77,110],"the":[7,30,51,157],"post-training":[8],"of":[9,26,70,170],"large":[10],"language":[11],"models":[12,83,129],"(LLMs)":[13],"for":[14],"reasoning,":[15],"agentic":[16,92],"capabilities":[17],"and":[18,94,113,120],"alignment.":[19],"Successful":[20],"RL":[21,72,171],"relies":[22],"on":[23,101,172],"sufficient":[24,141],"exploration":[25,46,63,137,163],"diverse":[27],"actions":[28],"by":[29,74],"model":[31,41,68,108],"during":[32,47],"training,":[33],"which":[34],"creates":[35],"a":[36,40,166],"potential":[37],"failure":[38,168],"mode:":[39],"could":[42],"strategically":[43],"alter":[44],"its":[45],"training":[48,53,145],"influence":[50],"subsequent":[52],"outcome.":[54],"In":[55],"this":[56,60,151],"paper":[57],"we":[58,66,124],"study":[59],"behavior,":[61],"called":[62],"hacking.":[64],"First,":[65],"create":[67],"organisms":[69,109],"selective":[71],"resistance":[73],"fine-tuning":[75],"LLMs":[76],"follow":[78],"specific":[79],"underperformance":[80],"strategies;":[81],"these":[82],"can":[84,130],"successfully":[85],"resist":[86],"our":[87,107,160],"RL-based":[88],"capability":[89],"elicitation":[90],"in":[91],"biosecurity":[93],"AI":[95],"R&D":[96],"environments":[97],"while":[98],"maintaining":[99],"performance":[100],"related":[102],"tasks.":[103],"We":[104],"then":[105],"use":[106],"evaluate":[111],"detection":[112],"mitigation":[114],"strategies,":[115],"including":[116],"monitoring,":[117],"weight":[118],"noising,":[119],"SFT-based":[121],"elicitation.":[122],"Finally,":[123],"show":[125],"that":[126],"current":[127],"frontier":[128],"exhibit":[131],"explicit":[132],"reasoning":[133],"about":[134,143],"suppressing":[135],"their":[136,144],"when":[138,150],"provided":[139],"with":[140,147],"information":[142,152],"context,":[146],"higher":[148],"rates":[149],"is":[153,165],"acquired":[154],"indirectly":[155],"through":[156],"environment.":[158],"Together,":[159],"results":[161],"suggest":[162],"hacking":[164],"possible":[167],"mode":[169],"sufficiently":[173],"capable":[174],"LLMs.":[175]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-02T00:00:00"}