{"id":"https://openalex.org/W4399356123","doi":"https://doi.org/10.48550/arxiv.2406.00426","title":"InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation","display_name":"InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation","publication_year":2024,"publication_date":"2024-06-01","ids":{"openalex":"https://openalex.org/W4399356123","doi":"https://doi.org/10.48550/arxiv.2406.00426"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2406.00426","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.00426","pdf_url":"https://arxiv.org/pdf/2406.00426","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2406.00426","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102682283","display_name":"Jacob Si","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Si, Jacob","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111220707","display_name":"Wendy Yusi Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Wendy Yusi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102937998","display_name":"Michael Cooper","orcid":"https://orcid.org/0000-0002-4176-0570"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cooper, Michael","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5073514348","display_name":"Rahul G. Krishnan","orcid":"https://orcid.org/0000-0002-7955-3956"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Krishnan, Rahul G.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102682283"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10320","display_name":"Neural Networks and Applications","score":0.5794000029563904,"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/T10320","display_name":"Neural Networks and Applications","score":0.5794000029563904,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.5723000168800354,"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/salient","display_name":"Salient","score":0.7938348650932312},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.6538417339324951},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5610663890838623},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5499897599220276},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46583738923072815},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4165472388267517},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38457489013671875},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07747942209243774},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.06807518005371094},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.047103673219680786}],"concepts":[{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.7938348650932312},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.6538417339324951},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5610663890838623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5499897599220276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46583738923072815},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4165472388267517},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38457489013671875},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07747942209243774},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.06807518005371094},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.047103673219680786}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2406.00426","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.00426","pdf_url":"https://arxiv.org/pdf/2406.00426","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2406.00426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2406.00426","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":"pmh:oai:arXiv.org:2406.00426","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.00426","pdf_url":"https://arxiv.org/pdf/2406.00426","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309949","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95"},{"id":"https://openalex.org/F4320322015","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087"},{"id":"https://openalex.org/F4320334506","display_name":"Canadian Institutes of Health Research","ror":"https://ror.org/01gavpb45"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399356123.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W4313320911","https://openalex.org/W4327743144","https://openalex.org/W2369710579","https://openalex.org/W4245077728","https://openalex.org/W4388913932","https://openalex.org/W4309130263","https://openalex.org/W4386159726"],"abstract_inverted_index":{"Tabular":[0],"data":[1,13,174],"are":[2,35],"omnipresent":[3],"in":[4,87,123],"various":[5],"sectors":[6],"of":[7,58,126],"industries.":[8],"Neural":[9],"networks":[10],"for":[11,28,171],"tabular":[12,173],"such":[14],"as":[15,67],"TabNet":[16,60],"have":[17],"been":[18],"proposed":[19],"to":[20,41,79,83,112,143],"make":[21],"predictions":[22],"while":[23,175],"leveraging":[24],"the":[25,31,47,59,64,81,88,106,114,119,124,146,155],"attention":[26,33,65,89],"mechanism":[27,66],"interpretability.":[29],"However,":[30],"inferred":[32],"masks":[34,90],"often":[36],"dense,":[37],"making":[38],"it":[39],"challenging":[40],"come":[42],"up":[43],"with":[44],"rationales":[45],"about":[46],"predictive":[48],"signal.":[49,157],"To":[50,121],"remedy":[51],"this,":[52],"we":[53,132,164],"propose":[54],"InterpreTabNet,":[55],"a":[56,68,73,92,134],"variant":[57],"model":[61,82,137],"that":[62,166],"models":[63],"latent":[69],"variable":[70],"sampled":[71],"from":[72,129,145],"Gumbel-Softmax":[74],"distribution.":[75],"This":[76],"enables":[77],"us":[78],"regularize":[80],"learn":[84],"distinct":[85],"concepts":[86],"via":[91],"KL":[93],"Divergence":[94],"regularizer.":[95],"It":[96],"prevents":[97],"overlapping":[98],"feature":[99,127,148],"selection":[100],"by":[101],"promoting":[102],"sparsity":[103],"which":[104],"maximizes":[105],"model's":[107],"efficacy":[108],"and":[109,139],"improves":[110],"interpretability":[111],"determine":[113],"important":[115],"features":[116],"when":[117],"predicting":[118],"outcome.":[120],"assist":[122],"interpretation":[125],"interdependencies":[128],"our":[130],"model,":[131],"employ":[133],"large":[135],"language":[136,152],"(GPT-4)":[138],"use":[140],"prompt":[141],"engineering":[142],"map":[144],"learned":[147,156],"mask":[149],"onto":[150],"natural":[151],"text":[153],"describing":[154],"Through":[158],"comprehensive":[159],"experiments":[160],"on":[161],"real-world":[162],"datasets,":[163],"demonstrate":[165],"InterpreTabNet":[167],"outperforms":[168],"previous":[169],"methods":[170],"interpreting":[172],"attaining":[176],"competitive":[177],"accuracy.":[178]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}