{"id":"https://openalex.org/W7163412896","doi":"https://doi.org/10.48550/arxiv.2606.03131","title":"HARVE: Hacking-Aware Reward-Head Vector Editing for Robust Reward Models","display_name":"HARVE: Hacking-Aware Reward-Head Vector Editing for Robust Reward Models","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163412896","doi":"https://doi.org/10.48550/arxiv.2606.03131"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.03131","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03131","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.2606.03131","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137721113","display_name":"Shuang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Shuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137728562","display_name":"Yuxuan Bo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo, Yuxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134459886","display_name":"Qiuyang Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Qiuyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104252976","display_name":"Caiyue Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Caiyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137748133","display_name":"Xiaorong Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xiaorong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137729544","display_name":"Yanguang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yanguang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137742532","display_name":"Mengnan Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Mengnan","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":0.3343999981880188,"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":0.3343999981880188,"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":0.07339999824762344,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.07270000129938126,"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/set","display_name":"Set (abstract data type)","score":0.5954999923706055},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.45879998803138733},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.40470001101493835},{"id":"https://openalex.org/keywords/hacker","display_name":"Hacker","score":0.39480000734329224},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.39480000734329224},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.36469998955726624},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.3395000100135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7026000022888184},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5954999923706055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5376999974250793},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.45879998803138733},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.40470001101493835},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3968000113964081},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.39480000734329224},{"id":"https://openalex.org/C86844869","wikidata":"https://www.wikidata.org/wiki/Q2798820","display_name":"Hacker","level":2,"score":0.39480000734329224},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C64948172","wikidata":"https://www.wikidata.org/wiki/Q1653277","display_name":"Brain stimulation reward","level":4,"score":0.3012000024318695},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28940001130104065},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.25360000133514404},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.03131","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03131","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.2606.03131","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03131","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reward":[0],"models":[1,126],"are":[2],"central":[3],"to":[4,14,104],"large":[5],"language":[6],"model":[7],"(LLM)":[8],"alignment,":[9],"but":[10],"they":[11],"remain":[12],"vulnerable":[13],"reward":[15,46,62,68,101,125,145],"hacking.":[16],"To":[17,48],"evaluate":[18],"reward-model":[19],"robustness,":[20,132],"we":[21,37,52],"introduce":[22],"RewardHackBench":[23],"containing":[24],"13":[25],"reward-hacking":[26],"patterns":[27],"covering":[28],"real":[29],"life":[30],"high-stakes":[31],"domains":[32],"and":[33,36,85,136],"general":[34,139],"settings,":[35],"find":[38],"severe":[39],"failures":[40],"on":[41],"specific":[42],"subcategories":[43],"across":[44,123],"eight":[45,124],"models.":[47,63],"mitigate":[49],"these":[50],"failures,":[51],"propose":[53],"HARVE,":[54],"a":[55,72,109,151],"training-free":[56],"reward-head":[57,91],"editing":[58],"method":[59],"for":[60],"scalar":[61],"Instead":[64],"of":[65,89,112],"fine-tuning":[66,134],"the":[67,87,90,100],"model,":[69],"HARVE":[70],"identifies":[71],"multi-directional":[73],"hacking":[74,83,131,146],"subspace":[75],"from":[76],"residual":[77],"stream":[78],"directions":[79],"associated":[80],"with":[81,94],"selected":[82],"subcategories,":[84],"removes":[86],"component":[88],"vector":[92],"aligned":[93],"that":[95,128,144],"subspace.":[96],"This":[97],"directly":[98],"reduces":[99],"head's":[102],"sensitivity":[103],"hacking-related":[105],"features":[106],"using":[107],"only":[108],"small":[110],"set":[111],"contrastive":[113],"gold-hacked":[114],"examples,":[115],"without":[116],"gradient":[117],"updates":[118],"or":[119],"fine-tuning.":[120],"Comprehensive":[121],"experiments":[122],"indicates":[127],"\\model":[129],"improves":[130],"outperforms":[133],"baselines,":[135],"preserves":[137],"reward-models'":[138],"capability.":[140],"Further":[141],"analyses":[142],"suggest":[143],"is":[147],"better":[148],"captured":[149],"as":[150],"multidimensional":[152],"residual-space":[153],"structure":[154],"than":[155],"by":[156],"isolated":[157],"surface":[158],"cues.":[159]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-04T00:00:00"}
