{"id":"https://openalex.org/W7166670729","doi":"https://doi.org/10.48550/arxiv.2606.29441","title":"Closing the Activation-Cone Blind Spot: Response-Time Probing and Unified Defense","display_name":"Closing the Activation-Cone Blind Spot: Response-Time Probing and Unified Defense","publication_year":2026,"publication_date":"2026-06-28","ids":{"openalex":"https://openalex.org/W7166670729","doi":"https://doi.org/10.48550/arxiv.2606.29441"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.29441","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29441","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.29441","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139689815","display_name":"Subhadip Mitra","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mitra, Subhadip","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5139689815"],"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":0.7879999876022339,"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":0.7879999876022339,"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":0.08100000023841858,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.014600000344216824,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/guard","display_name":"Guard (computer science)","score":0.7390000224113464},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.6456000208854675},{"id":"https://openalex.org/keywords/closing","display_name":"Closing (real estate)","score":0.5971999764442444},{"id":"https://openalex.org/keywords/constructive","display_name":"Constructive","score":0.4968999922275543},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.45410001277923584},{"id":"https://openalex.org/keywords/false-accusation","display_name":"False accusation","score":0.33169999718666077}],"concepts":[{"id":"https://openalex.org/C141141315","wikidata":"https://www.wikidata.org/wiki/Q2379942","display_name":"Guard (computer science)","level":2,"score":0.7390000224113464},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.6456000208854675},{"id":"https://openalex.org/C2778775528","wikidata":"https://www.wikidata.org/wiki/Q5135432","display_name":"Closing (real estate)","level":2,"score":0.5971999764442444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5848000049591064},{"id":"https://openalex.org/C2778701210","wikidata":"https://www.wikidata.org/wiki/Q28130034","display_name":"Constructive","level":3,"score":0.4968999922275543},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.47600001096725464},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.45410001277923584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4406000077724457},{"id":"https://openalex.org/C59577422","wikidata":"https://www.wikidata.org/wiki/Q10265143","display_name":"False accusation","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C112789634","wikidata":"https://www.wikidata.org/wiki/Q18207010","display_name":"False positives and false negatives","level":3,"score":0.32170000672340393},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2888000011444092}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.29441","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29441","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.29441","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29441","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8482747077941895}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Inference-time":[0],"safety":[1],"methods":[2],"for":[3],"large":[4],"language":[5],"models":[6,29],"have":[7],"proliferated,":[8],"yet":[9],"no":[10],"systematic":[11],"comparison":[12],"exists.":[13],"We":[14,68,211],"evaluate":[15],"five":[16,32],"defense":[17,73,198],"paradigms":[18],"(no":[19],"defense,":[20],"static":[21],"steering,":[22],"CAST,":[23],"AlphaSteer,":[24],"probe-gated)":[25],"across":[26,135],"seven":[27,137],"instruction-tuned":[28],"(7-31B)":[30],"and":[31,61,203,207,231,250],"attack":[33,56,146],"types":[34],"(GCG,":[35],"AutoDAN,":[36,60],"DeepInception,":[37],"prefilling,":[38,192],"intent":[39,62],"laundering).":[40],"Our":[41],"central":[42],"finding:":[43],"prompt-time":[44],"activation":[45,81],"defenses":[46],"are":[47,254],"structurally":[48],"blind":[49,92],"to":[50,93,98,148,173,216,243],"prefilling":[51,145],"attacks.":[52],"AlphaSteer":[53,193],"achieves":[54],"0%":[55,154],"success":[57,147,199],"on":[58,66,77,122,150,165,201,205],"GCG,":[59],"laundering":[63],"but":[64],"50%":[65],"prefilling.":[67],"prove":[69],"a":[70,78,84,119,141],"corollary:":[71],"any":[72],"that":[74,95,101,232],"gates":[75],"intervention":[76],"single":[79],"layer's":[80],"alignment":[82],"with":[83,132,140,153,181],"benign":[85,155],"reference":[86],"(cone,":[87],"subspace,":[88],"or":[89,108],"null-space)":[90],"is":[91],"attacks":[94],"craft":[96],"activations":[97],"lie":[99],"inside":[100],"reference,":[102],"whether":[103],"checked":[104],"at":[105,127],"prompt":[106,253],"time":[107],"per":[109],"token.":[110],"As":[111],"its":[112],"constructive":[113],"contrapositive":[114],"we":[115,169],"introduce":[116],"response-time":[117],"probing:":[118],"linear":[120],"probe":[121,166,238],"the":[123,128,171,174,179,251],"model's":[124],"hidden":[125],"state":[126],"first":[129],"generated":[130],"tokens,":[131],"AUROC":[133],"0.97-1.00":[134],"all":[136],"models.":[138],"Combined":[139],"halt,":[142],"it":[143],"cuts":[144],"0/40":[149],"every":[151],"model":[152],"false":[156,239],"positives,":[157],"outperforming":[158],"Llama":[159,206],"Guard":[160],"3.":[161],"Cross-template":[162],"generalisation":[163],"depends":[164],"depth,":[167],"so":[168],"scope":[170],"claim":[172],"canonical":[175],"prefilling-template":[176],"family.":[177],"Composing":[178],"response-halt":[180],"AlphaSteer's":[182],"null-space":[183],"steering":[184],"gives":[185],"an":[186],"orthogonal":[187],"split":[188],"(the":[189],"halt":[190],"catches":[191,194],"semantic":[195],"attacks),":[196],"reaching":[197],"0.983":[200],"Mistral":[202],"0.994":[204],"dominating":[208],"both":[209],"components.":[210],"further":[212],"show":[213],"MMLU":[214],"fails":[215],"capture":[217],"steering's":[218],"true":[219],"utility":[220],"cost,":[221],"which":[222],"appears":[223],"as":[224],"behavioral":[225],"hedging":[226],"rather":[227],"than":[228],"factual":[229],"loss,":[230],"diverse":[233],"negative":[234],"training":[235],"sets":[236],"cut":[237],"positives":[240],"from":[241],"80-100%":[242],"near":[244],"zero.":[245],"Code,":[246],"attacks,":[247],"per-sample":[248],"results,":[249],"judge":[252],"released.":[255]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-01T00:00:00"}