{"id":"https://openalex.org/W7166175090","doi":"https://doi.org/10.48550/arxiv.2606.26155","title":"Detecting and Controlling Sycophancy with Cascading Linear Features","display_name":"Detecting and Controlling Sycophancy with Cascading Linear Features","publication_year":2026,"publication_date":"2026-06-23","ids":{"openalex":"https://openalex.org/W7166175090","doi":"https://doi.org/10.48550/arxiv.2606.26155"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.26155","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26155","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.2606.26155","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134932095","display_name":"Maty Bohacek","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bohacek, Maty","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102862305","display_name":"R. Praveen Jain","orcid":"https://orcid.org/0000-0002-6518-7879"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jain, Rishub","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139448866","display_name":"Nicholas Dufour","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dufour, Nicholas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139445466","display_name":"Thomas Leung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leung, Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109876070","display_name":"Chris Bregler","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bregler, Chris","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139437469","display_name":"Roma Patel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patel, Roma","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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.5144000053405762,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.5144000053405762,"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":0.06930000334978104,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.05860000103712082,"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/interpretability","display_name":"Interpretability","score":0.9279999732971191},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.545199990272522},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.515500009059906},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.503600001335144},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.48510000109672546},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4287000000476837},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.41510000824928284},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.41429999470710754}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9279999732971191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6474999785423279},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.545199990272522},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.515500009059906},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.503600001335144},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.48510000109672546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4293999969959259},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4287000000476837},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.41510000824928284},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.41429999470710754},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3928999900817871},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3686000108718872},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3677000105381012},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3395000100135803},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.31700000166893005},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29789999127388},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2896000146865845},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.28130000829696655},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.26155","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26155","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.2606.26155","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26155","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":[{"id":"https://metadata.un.org/sdg/10","score":0.4455167055130005,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Interpreting":[0],"and":[1,41,84,108,136,164,167,176,185],"controlling":[2],"model":[3,35,141],"behaviors":[4],"through":[5,129],"activation":[6],"steering":[7,109],"methods":[8],"requires":[9],"many":[10],"pairs":[11,24,81],"of":[12,82,91,102,116,140],"contrastive":[13],"samples":[14,87,131],"that":[15,64,88,93,125,143,169],"clearly":[16,145],"exhibit":[17],"desired":[18,149],"or":[19,49,173],"undesired":[20],"behavior.":[21,53,72],"These":[22],"data":[23,61],"determine":[25],"the":[26,43,114,148],"degree":[27],"to":[28,45,119,147,159],"which":[29],"interpretability":[30,187],"frameworks":[31],"can":[32],"reliably":[33],"detect":[34],"features":[36,68,92,127],"responsible":[37,69],"for":[38,70,99,138],"a":[39,71],"behavior,":[40,97],"therefore":[42],"ability":[44,158],"steer":[46],"models":[47,118],"toward":[48],"away":[50,110],"from":[51,111],"such":[52],"In":[54],"this":[55],"work,":[56],"we":[57,74],"present":[58],"an":[59],"iterative":[60],"generation":[62],"pipeline":[63],"isolates":[65],"cascading":[66,130],"linear":[67],"Specifically,":[73],"show":[75,89],"how":[76],"moving":[77],"beyond":[78],"simple":[79],"binary":[80],"samples,":[83],"instead":[85],"isolating":[86],"degrees":[90],"scale":[94],"linearly":[95,133],"with":[96],"allows":[98],"better":[100],"disentanglement":[101],"features.":[103],"We":[104,123,154],"focus":[105],"on":[106],"detecting":[107],"sycophancy":[112,126],"--":[113],"tendency":[115],"language":[117],"prioritize":[120],"user":[121],"validation.":[122],"demonstrate":[124],"discovered":[128],"form":[132],"separable":[134],"subspaces,":[135],"allow":[137],"selection":[139],"activations":[142],"more":[144,186],"correspond":[146],"behavior":[150],"than":[151],"baseline":[152],"approaches.":[153],"also":[155],"evaluate":[156],"their":[157],"enable":[160],"detection,":[161],"deterministic":[162],"scoring,":[163],"robust":[165],"steering,":[166],"see":[168],"they":[170],"either":[171],"match":[172],"outperform":[174],"LLM-as-a-judge":[175],"system":[177],"prompting":[178],"baselines":[179],"while":[180],"providing":[181],"lower":[182],"computational":[183],"demand":[184],"guarantees.":[188],"Code":[189],"&":[190],"Data:":[191],"https://cascading-feats.github.io/":[192]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-27T00:00:00"}