{"id":"https://openalex.org/W7161063287","doi":"https://doi.org/10.48550/arxiv.2605.11887","title":"Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models","display_name":"Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7161063287","doi":"https://doi.org/10.48550/arxiv.2605.11887"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.11887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11887","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.2605.11887","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114107429","display_name":"Boyi Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Boyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136003355","display_name":"Xu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091844821","display_name":"Yao Wang","orcid":"https://orcid.org/0009-0008-0571-4463"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yaoning","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031253591","display_name":"Yu Wan","orcid":"https://orcid.org/0000-0003-1649-9611"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136070580","display_name":"Yubo Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Yubo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133581226","display_name":"Baosong Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Baosong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136079503","display_name":"Haoran Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136012231","display_name":"Jialong Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Jialong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102405148","display_name":"Huan Lin","orcid":"https://orcid.org/0000-0002-8205-5739"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Huan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136021034","display_name":"Ruize Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Ruize","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136062236","display_name":"Tianhao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Tianhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136006946","display_name":"Qian Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Qian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049239373","display_name":"Xuancheng Ren","orcid":"https://orcid.org/0000-0002-6994-2114"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Xuancheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077242351","display_name":"Xiaodong Deng","orcid":"https://orcid.org/0000-0002-6938-1214"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Xiaodong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136046664","display_name":"An Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, An","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136058614","display_name":"Fei Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Fei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136005038","display_name":"Dayiheng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Dayiheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136052645","display_name":"Jingren Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Jingren","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":0.7710999846458435,"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":0.7710999846458435,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.03449999913573265,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.02889999933540821,"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/feature","display_name":"Feature (linguistics)","score":0.5210000276565552},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.5120000243186951},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.48969998955726624},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4724999964237213},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.37059998512268066},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3643999993801117},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.35589998960494995},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.34599998593330383}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.724399983882904},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5210000276565552},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.5120000243186951},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4909000098705292},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.48969998955726624},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4724999964237213},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4350999891757965},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3643999993801117},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.34599998593330383},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.27730000019073486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27219998836517334},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C2776542497","wikidata":"https://www.wikidata.org/wiki/Q5266672","display_name":"Development (topology)","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.11887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11887","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.2605.11887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11887","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":[{"score":0.7623510956764221,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1,220],"models":[2],"have":[3],"achieved":[4],"remarkable":[5],"capabilities":[6],"across":[7,79],"diverse":[8],"tasks,":[9],"yet":[10],"their":[11],"internal":[12],"decision-making":[13],"processes":[14],"remain":[15],"largely":[16],"opaque,":[17],"limiting":[18],"our":[19],"ability":[20],"to":[21,110,184,227,239],"inspect,":[22],"control,":[23],"and":[24,86,92,131,151,164,168,180,191,217,231],"systematically":[25],"improve":[26],"them.":[27],"This":[28],"opacity":[29],"motivates":[30],"a":[31,145],"growing":[32],"body":[33],"of":[34,46,66,77,98],"research":[35,230],"in":[36],"mechanistic":[37,229],"interpretability,":[38],"with":[39],"sparse":[40],"autoencoders":[41],"(SAEs)":[42],"emerging":[43],"as":[44,112,189,203,209],"one":[45],"the":[47,70,84],"most":[48],"promising":[49],"tools":[50],"for":[51,115,148,213],"decomposing":[52],"model":[53,72,81,116,135,237],"activations":[54],"into":[55,177],"sparse,":[56],"interpretable":[57],"feature":[58,126],"representations.":[59],"We":[60],"introduce":[61],"Qwen-Scope,":[62,224],"an":[63],"open-source":[64],"suite":[65],"SAEs":[67,78,104,198],"built":[68],"on":[69,96],"Qwen":[71],"family,":[73],"comprising":[74],"14":[75],"groups":[76],"7":[80],"variants":[82],"from":[83],"Qwen3":[85],"Qwen3.5":[87],"series,":[88],"covering":[89],"both":[90],"dense":[91],"mixture-of-expert":[93],"architectures.":[94],"Built":[95],"top":[97],"these":[99,194],"SAEs,":[100],"we":[101,225],"show":[102],"that":[103,197,235],"can":[105,199],"go":[106],"beyond":[107],"post-hoc":[108,204],"analysis":[109,205],"serve":[111,200],"practical":[113,233],"interfaces":[114,212],"development":[117],"along":[118],"four":[119],"directions:":[120],"(i)":[121],"inference-time":[122],"steering,":[123],"where":[124,140,157,172],"SAE":[125,142,158],"directions":[127],"control":[128],"language,":[129],"concepts,":[130],"preferences":[132],"without":[133],"modifying":[134],"weights;":[136],"(ii)":[137],"evaluation":[138],"analysis,":[139],"activated":[141],"features":[143,159],"provide":[144],"representation-level":[146,211],"proxy":[147],"benchmark":[149],"redundancy":[150],"capability":[152],"coverage;":[153],"(iii)":[154],"data-centric":[155],"workflows,":[156],"support":[160,228],"multilingual":[161],"toxicity":[162],"classification":[163],"safety-oriented":[165],"data":[166],"synthesis;":[167],"(iv)":[169],"post-training":[170],"optimization,":[171],"SAE-derived":[173],"signals":[174],"are":[175],"incorporated":[176],"supervised":[178],"fine-tuning":[179],"reinforcement":[181],"learning":[182],"objectives":[183],"mitigate":[185],"undesirable":[186],"behaviors":[187],"such":[188],"code-switching":[190],"repetition.":[192],"Together,":[193],"results":[195],"demonstrate":[196],"not":[201],"only":[202],"tools,":[206],"but":[207],"also":[208],"reusable":[210],"diagnosing,":[214],"controlling,":[215],"evaluating,":[216],"improving":[218],"large":[219],"models.":[221],"By":[222],"open-sourcing":[223],"aim":[226],"accelerate":[232],"workflows":[234],"connect":[236],"internals":[238],"downstream":[240],"behavior.":[241]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-14T00:00:00"}