{"id":"https://openalex.org/W7157345726","doi":"https://doi.org/10.48550/arxiv.2604.23829","title":"Domain-Filtered Knowledge Graphs from Sparse Autoencoder Features","display_name":"Domain-Filtered Knowledge Graphs from Sparse Autoencoder Features","publication_year":2026,"publication_date":"2026-04-26","ids":{"openalex":"https://openalex.org/W7157345726","doi":"https://doi.org/10.48550/arxiv.2604.23829"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.23829","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23829","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.23829","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026229334","display_name":"John Winnicki","orcid":"https://orcid.org/0009-0003-8512-1708"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Winnicki, John","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090912313","display_name":"Abeynaya Gnanasekaran","orcid":"https://orcid.org/0000-0001-7088-9261"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gnanasekaran, Abeynaya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5061822097","display_name":"Eric Darve","orcid":"https://orcid.org/0000-0002-1938-3836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Darve, Eric","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026229334"],"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":0.34779998660087585,"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":0.34779998660087585,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.27619999647140503,"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":0.07180000096559525,"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":0.7886000275611877},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5478000044822693},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5428000092506409},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5073999762535095},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.39250001311302185},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.38260000944137573},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.3549000024795532},{"id":"https://openalex.org/keywords/dense-graph","display_name":"Dense graph","score":0.32089999318122864}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7886000275611877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6381999850273132},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5548999905586243},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5478000044822693},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5073999762535095},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.39250001311302185},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37869998812675476},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C13251829","wikidata":"https://www.wikidata.org/wiki/Q3085841","display_name":"Dense graph","level":5,"score":0.32089999318122864},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3151000142097473},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31029999256134033},{"id":"https://openalex.org/C558772884","wikidata":"https://www.wikidata.org/wiki/Q1508564","display_name":"Graph rewriting","level":3,"score":0.2768000066280365},{"id":"https://openalex.org/C234837","wikidata":"https://www.wikidata.org/wiki/Q1420493","display_name":"Conceptual graph","level":3,"score":0.27630001306533813},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C179372163","wikidata":"https://www.wikidata.org/wiki/Q1406181","display_name":"Scene graph","level":3,"score":0.2669000029563904},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2624000012874603},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C112953755","wikidata":"https://www.wikidata.org/wiki/Q739462","display_name":"Graph drawing","level":3,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.23829","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23829","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.23829","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23829","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":"article"},"sustainable_development_goals":[{"score":0.46066340804100037,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Sparse":[0],"autoencoders":[1],"(SAEs)":[2],"extract":[3],"millions":[4],"of":[5,95,157,190,196],"interpretable":[6],"features":[7,107,158],"from":[8,60],"a":[9,55,61,69,84,98,129,133,173,187],"language":[10],"model,":[11],"but":[12],"flat":[13,174],"feature":[14],"inventories":[15],"aren't":[16],"very":[17],"useful":[18],"on":[19,80,132],"their":[20],"own.":[21],"Domain":[22],"concepts":[23,145],"get":[24],"mixed":[25],"with":[26],"generic":[27],"and":[28,40,68,97,105,141,150,193],"weakly":[29],"grounded":[30],"features,":[31],"while":[32],"related":[33],"ideas":[34],"are":[35],"scattered":[36],"across":[37],"many":[38],"units,":[39],"there's":[41],"no":[42],"way":[43],"to":[44],"understand":[45],"relationships":[46],"between":[47],"features.":[48],"We":[49],"address":[50],"this":[51,171],"by":[52],"first":[53],"constructing":[54],"strict":[56],"domain-specific":[57],"concept":[58],"universe":[59],"large":[62],"SAE":[63,175],"inventory":[64,176],"using":[65],"contrastive":[66],"activations":[67],"multi-stage":[70],"filtering":[71],"process.":[72],"Next,":[73],"we":[74],"build":[75],"two":[76],"aligned":[77],"graph":[78,86,101,118,181],"views":[79,119,162],"the":[81,165],"filtered":[82],"set:":[83],"co-occurrence":[85],"for":[87],"corpus-level":[88],"conceptual":[89],"structure,":[90,143],"organized":[91],"at":[92],"multiple":[93],"levels":[94],"granularity,":[96],"transcoder-based":[99],"mechanism":[100],"that":[102,146,163,182],"links":[103],"source-layer":[104],"target-layer":[106],"through":[108],"sparse":[109],"latent":[110],"pathways.":[111],"Automated":[112],"edge":[113],"labeling":[114],"then":[115],"turns":[116],"these":[117,136],"into":[120,159,186],"readable":[121,161],"knowledge":[122,180,192],"graphs":[123,137],"rather":[124],"than":[125],"unlabeled":[126],"layouts.":[127],"In":[128],"case":[130],"study":[131],"biology":[134],"textbook,":[135],"recover":[138],"coherent":[139],"chapter":[140],"subchapter-level":[142],"reveal":[144],"bridge":[147],"neighboring":[148],"topics,":[149],"transform":[151],"messy":[152],"sentence-level":[153],"activity":[154],"containing":[155],"thousands":[156],"compact,":[160],"illustrate":[164],"model's":[166],"local":[167],"activity.":[168],"Taken":[169],"together,":[170],"reframes":[172],"as":[177],"an":[178],"internal":[179],"converts":[183],"feature-level":[184],"interpretability":[185],"global":[188],"map":[189],"model":[191],"enables":[194],"audits":[195],"reasoning":[197],"faithfulness.":[198]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-04-29T00:00:00"}
