{"id":"https://openalex.org/W4284714439","doi":"https://doi.org/10.1145/3539813.3545129","title":"GazBy: Gaze-Based BERT Model to Incorporate Human Attention in Neural Information Retrieval","display_name":"GazBy: Gaze-Based BERT Model to Incorporate Human Attention in Neural Information Retrieval","publication_year":2022,"publication_date":"2022-08-23","ids":{"openalex":"https://openalex.org/W4284714439","doi":"https://doi.org/10.1145/3539813.3545129"},"language":"en","primary_location":{"id":"doi:10.1145/3539813.3545129","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539813.3545129","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 ACM SIGIR International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2207.01674","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032087834","display_name":"Sibo Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sibo Dong","raw_affiliation_strings":["Georgetown University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Georgetown University, Washington, DC, USA","institution_ids":["https://openalex.org/I184565670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063311615","display_name":"Justin Goldstein","orcid":"https://orcid.org/0000-0001-5414-9589"},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Justin Goldstein","raw_affiliation_strings":["Georgetown University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Georgetown University, Washington, DC, USA","institution_ids":["https://openalex.org/I184565670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002485529","display_name":"Grace Hui Yang","orcid":"https://orcid.org/0000-0001-6095-8358"},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Grace Hui Yang","raw_affiliation_strings":["Georgetown University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Georgetown University, Washington, DC, USA","institution_ids":["https://openalex.org/I184565670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032087834"],"corresponding_institution_ids":["https://openalex.org/I184565670"],"apc_list":null,"apc_paid":null,"fwci":0.2039,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.4685139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"182","last_page":"192"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9872999787330627,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9872999787330627,"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/T10028","display_name":"Topic Modeling","score":0.9869999885559082,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9843000173568726,"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/gaze","display_name":"Gaze","score":0.8517103791236877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8170713186264038},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6561867594718933},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5771574378013611},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5416747331619263},{"id":"https://openalex.org/keywords/fixation","display_name":"Fixation (population genetics)","score":0.4497867524623871},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42245206236839294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.361702024936676},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.34610801935195923},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3436090350151062},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08789819478988647}],"concepts":[{"id":"https://openalex.org/C2779916870","wikidata":"https://www.wikidata.org/wiki/Q14467155","display_name":"Gaze","level":2,"score":0.8517103791236877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8170713186264038},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6561867594718933},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5771574378013611},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5416747331619263},{"id":"https://openalex.org/C146249460","wikidata":"https://www.wikidata.org/wiki/Q2914991","display_name":"Fixation (population genetics)","level":3,"score":0.4497867524623871},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42245206236839294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.361702024936676},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.34610801935195923},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3436090350151062},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08789819478988647},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3539813.3545129","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539813.3545129","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 ACM SIGIR International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2207.01674","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.01674","pdf_url":"https://arxiv.org/pdf/2207.01674","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2207.01674","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.01674","pdf_url":"https://arxiv.org/pdf/2207.01674","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1910566948","https://openalex.org/W1982065914","https://openalex.org/W1998902231","https://openalex.org/W2079735306","https://openalex.org/W2100379672","https://openalex.org/W2104083296","https://openalex.org/W2136189984","https://openalex.org/W2150886314","https://openalex.org/W2250539671","https://openalex.org/W2407797316","https://openalex.org/W2518578398","https://openalex.org/W2536015822","https://openalex.org/W2648699835","https://openalex.org/W2759653627","https://openalex.org/W2766284073","https://openalex.org/W2771876412","https://openalex.org/W2783640434","https://openalex.org/W2799116636","https://openalex.org/W2799232306","https://openalex.org/W2890409747","https://openalex.org/W2892181857","https://openalex.org/W2896363972","https://openalex.org/W2897754576","https://openalex.org/W2898843412","https://openalex.org/W2930957955","https://openalex.org/W2949547800","https://openalex.org/W2951434086","https://openalex.org/W2962703144","https://openalex.org/W2962748230","https://openalex.org/W2962762462","https://openalex.org/W2970641574","https://openalex.org/W2985540049","https://openalex.org/W2998702515","https://openalex.org/W3021397474","https://openalex.org/W3021779606","https://openalex.org/W3035422918","https://openalex.org/W3098851962","https://openalex.org/W3099384026","https://openalex.org/W3099700870","https://openalex.org/W3102485638","https://openalex.org/W3103099263","https://openalex.org/W3103966943","https://openalex.org/W3154280800","https://openalex.org/W3154755316","https://openalex.org/W3155114168","https://openalex.org/W3168875417","https://openalex.org/W3171355829","https://openalex.org/W3173936365","https://openalex.org/W3208821253","https://openalex.org/W4206121183","https://openalex.org/W4251504464","https://openalex.org/W4252076394"],"related_works":["https://openalex.org/W1880689012","https://openalex.org/W3014378845","https://openalex.org/W4240909707","https://openalex.org/W2059546927","https://openalex.org/W3207760378","https://openalex.org/W4386072035","https://openalex.org/W2562758970","https://openalex.org/W1986970529","https://openalex.org/W1563178652","https://openalex.org/W2947492009"],"abstract_inverted_index":{"This":[0],"paper":[1],"is":[2],"interested":[3],"in":[4,147],"investigating":[5],"whether":[6],"human":[7,29,54,108,127],"gaze":[8,55,109,128,145],"signals":[9,146],"can":[10],"be":[11],"leveraged":[12],"to":[13,21,61,110],"improve":[14],"state-of-the-art":[15],"search":[16,150],"engine":[17],"performance":[18],"and":[19,90,98,102,123],"how":[20],"incorporate":[22],"this":[23,37,136],"new":[24],"input":[25],"signal":[26],"marked":[27],"by":[28],"attention":[30],"into":[31,58,72],"existing":[32],"neural":[33,114,149],"retrieval":[34,74],"models.":[35],"In":[36],"paper,":[38],"we":[39],"propose":[40],"GazBy":[41],"(Gaze-based":[42],"Bert":[43],"model":[44,51,79],"for":[45,106],"document":[46,63],"relevancy),":[47],"a":[48,140],"lightweight":[49],"joint":[50],"that":[52],"integrates":[53],"fixation":[56],"estimation":[57],"transformer":[59],"models":[60],"predict":[62],"relevance,":[64],"incorporating":[65],"more":[66,132],"nuanced":[67],"information":[68,73],"about":[69],"cognitive":[70],"processing":[71],"(IR).":[75],"We":[76,134],"evaluate":[77],"our":[78],"on":[80],"the":[81,100,117],"Text":[82],"Retrieval":[83],"Conference":[84],"(TREC)":[85],"Deep":[86],"Learning":[87],"(DL)":[88],"2019":[89],"2020":[91],"Tracks.":[92],"Our":[93],"experiments":[94],"show":[95],"encouraging":[96],"results":[97],"illustrate":[99],"effective":[101],"ineffective":[103],"entry":[104],"points":[105],"using":[107,144],"help":[111],"with":[112],"transformer-based":[113],"retrievers.":[115],"With":[116],"rise":[118],"of":[119],"virtual":[120],"reality":[121,125],"(VR)":[122],"augmented":[124],"(AR),":[126],"data":[129],"will":[130],"become":[131],"available.":[133],"hope":[135],"work":[137],"serves":[138],"as":[139],"first":[141],"step":[142],"exploring":[143],"modern":[148],"engines.":[151]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2022-07-08T00:00:00"}
