{"id":"https://openalex.org/W7160331938","doi":"https://doi.org/10.1109/wacv61042.2026.00180","title":"HumanGuideNet: Adapter-Based Alignment of Deep Neural Networks with Human Similarity Judgments","display_name":"HumanGuideNet: Adapter-Based Alignment of Deep Neural Networks with Human Similarity Judgments","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160331938","doi":"https://doi.org/10.1109/wacv61042.2026.00180"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079087887","display_name":"Xufu Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xufu Liu","raw_affiliation_strings":["The Pennsylvania State University,PA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University,PA,USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101859853","display_name":"Yifan Yang","orcid":"https://orcid.org/0000-0001-5384-5072"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifan Yang","raw_affiliation_strings":["The Pennsylvania State University,PA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University,PA,USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009797301","display_name":"Z L Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengxin Zhang","raw_affiliation_strings":["Cornell University,Ithaca,NY,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University,Ithaca,NY,USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"1798","last_page":"1808"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.13079999387264252,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.13079999387264252,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.12120000272989273,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.10090000182390213,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.531499981880188},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44200000166893005},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4077000021934509},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3212999999523163},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.31940001249313354}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.699999988079071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5952000021934509},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44200000166893005},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4077000021934509},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.31940001249313354},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2809000015258789},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.24690000712871552}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1978469956","https://openalex.org/W2017814585","https://openalex.org/W2047643928","https://openalex.org/W2069059150","https://openalex.org/W2108598243","https://openalex.org/W2160654481","https://openalex.org/W2791091755","https://openalex.org/W2795373741","https://openalex.org/W2804935296","https://openalex.org/W2921125453","https://openalex.org/W2952760759","https://openalex.org/W2955639361","https://openalex.org/W2962707369","https://openalex.org/W2963072899","https://openalex.org/W2963305465","https://openalex.org/W2980938713","https://openalex.org/W3002093512","https://openalex.org/W3005295611","https://openalex.org/W3016970897","https://openalex.org/W3092472394","https://openalex.org/W3115894062","https://openalex.org/W3175716777","https://openalex.org/W4214642259","https://openalex.org/W4246066915","https://openalex.org/W4312884055","https://openalex.org/W4313175608","https://openalex.org/W4322494696","https://openalex.org/W4386790226","https://openalex.org/W4390873054","https://openalex.org/W4391021820","https://openalex.org/W7133219196","https://openalex.org/W7133250524"],"related_works":[],"abstract_inverted_index":{"Aligning":[0],"deep":[1],"neural":[2],"network":[3],"(DNN)":[4],"representations":[5,55,79,94],"with":[6,35,56,77],"human":[7,47,57,97,142],"perceptual":[8,87],"structure":[9],"is":[10],"an":[11,32],"important":[12],"direction":[13],"for":[14],"cognitively":[15],"grounded":[16],"AI,":[17],"and":[18,46,73,102,111,120,153],"emerging":[19],"evidence":[20],"suggests":[21],"that":[22,91,107,140],"human-aligned":[23,37,75,158],"models":[24],"can":[25,144],"exhibit":[26],"improved":[27],"robustness.":[28,112],"We":[29,89],"introduce":[30],"HumanGuideNet,":[31],"adapter-based":[33],"architecture":[34],"a":[36,125,151],"branch\u2014HumReg\u2014trained":[38],"jointly":[39],"on":[40,65],"standard":[41],"class":[42],"labels":[43],"(e.g.,":[44],"ImageNet-1k)":[45],"similarity":[48,58,99],"judgments":[49],"(THINGs":[50],"data)":[51],"to":[52,80,104,133,156],"align":[53],"model":[54],"structure.":[59],"Unlike":[60],"traditional":[61],"alignment":[62,143],"methods":[63],"based":[64],"linear":[66],"transforms,":[67],"HumanGuideNet":[68],"preserves":[69],"the":[70,92,114],"pretrained":[71,148],"backbone":[72,78],"fuses":[74],"features":[76,106,116],"retain":[81],"general":[82],"visual":[83,159],"knowledge":[84],"while":[85,129],"injecting":[86],"alignment.":[88],"show":[90,139],"HumReg":[93],"better":[95],"capture":[96],"representational":[98],"matrices":[100],"(RSMs)":[101],"lead":[103],"fused":[105,115],"significantly":[108],"improve":[109],"generalization":[110],"Specifically,":[113],"boost":[117],"few-shot":[118],"classification":[119],"anomaly":[121],"detection":[122],"accuracy":[123],"across":[124],"range":[126],"of":[127],"datasets,":[128],"also":[130],"exhibiting":[131],"robustness":[132],"natural":[134],"image":[135],"corruptions.":[136],"Our":[137],"results":[138],"modular":[141],"effectively":[145],"enhance":[146],"large":[147],"models,":[149],"providing":[150],"scalable":[152],"interpretable":[154],"approach":[155],"building":[157],"intelligence.":[160]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-05-06T00:00:00"}
