{"id":"https://openalex.org/W4378498569","doi":"https://doi.org/10.48550/arxiv.2305.15387","title":"Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering","display_name":"Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering","publication_year":2023,"publication_date":"2023-05-24","ids":{"openalex":"https://openalex.org/W4378498569","doi":"https://doi.org/10.48550/arxiv.2305.15387"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2305.15387","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.15387","pdf_url":"https://arxiv.org/pdf/2305.15387","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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2305.15387","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077903013","display_name":"Avi Caciularu","orcid":"https://orcid.org/0000-0003-0573-1075"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Caciularu, Avi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101509445","display_name":"Matthew E. Peters","orcid":"https://orcid.org/0000-0002-2105-2585"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peters, Matthew E.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005409420","display_name":"Jacob Goldberger","orcid":"https://orcid.org/0000-0002-2225-1914"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Goldberger, Jacob","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033006575","display_name":"Ido Dagan","orcid":"https://orcid.org/0000-0003-3415-3374"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dagan, Ido","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5064858748","display_name":"Arman Cohan","orcid":"https://orcid.org/0000-0002-8954-2724"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cohan, Arman","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5077903013"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"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/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9919999837875366,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9625999927520752,"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/automatic-summarization","display_name":"Automatic summarization","score":0.8466135263442993},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8266157507896423},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.6840422749519348},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6149290800094604},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5746796131134033},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5445137619972229},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5019981861114502},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4644686281681061},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.45021870732307434},{"id":"https://openalex.org/keywords/multi-document-summarization","display_name":"Multi-document summarization","score":0.4371083974838257},{"id":"https://openalex.org/keywords/document-classification","display_name":"Document classification","score":0.4218592941761017},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4127640724182129},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.2485913634300232}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8466135263442993},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8266157507896423},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6840422749519348},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6149290800094604},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5746796131134033},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5445137619972229},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5019981861114502},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4644686281681061},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.45021870732307434},{"id":"https://openalex.org/C134714966","wikidata":"https://www.wikidata.org/wiki/Q6934448","display_name":"Multi-document summarization","level":3,"score":0.4371083974838257},{"id":"https://openalex.org/C2780479914","wikidata":"https://www.wikidata.org/wiki/Q302088","display_name":"Document classification","level":2,"score":0.4218592941761017},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4127640724182129},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.2485913634300232},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2305.15387","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.15387","pdf_url":"https://arxiv.org/pdf/2305.15387","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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2305.15387","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2305.15387","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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2305.15387","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.15387","pdf_url":"https://arxiv.org/pdf/2305.15387","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":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320323706","display_name":"Ministry of Science and Technology, Israel","ror":"https://ror.org/02heb2n75"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4378498569.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4214678372","https://openalex.org/W1605559518","https://openalex.org/W3164984162","https://openalex.org/W2104677027","https://openalex.org/W2902627734","https://openalex.org/W2112885393","https://openalex.org/W2173208124","https://openalex.org/W2568827738","https://openalex.org/W1990695371","https://openalex.org/W4214601164"],"abstract_inverted_index":{"The":[0],"integration":[1],"of":[2,48,193],"multi-document":[3,15,30,105,131,182,185],"pre-training":[4,27,38,126,142],"objectives":[5],"into":[6,75],"language":[7],"models":[8,132],"has":[9],"resulted":[10],"in":[11,14,60],"remarkable":[12],"improvements":[13,192],"downstream":[16],"tasks.":[17],"In":[18,79],"this":[19,24,166],"work,":[20],"we":[21,51,168],"propose":[22],"extending":[23],"idea":[25],"by":[26],"a":[28,33,44,57,80,119],"generic":[29],"model":[31,84,110,147,171],"from":[32,56,92],"novel":[34,104],"cross-document":[35,101],"question":[36,95],"answering":[37],"objective.":[39],"To":[40],"that":[41,122,133,151],"end,":[42],"given":[43],"set":[45],"(or":[46],"cluster)":[47],"topically-related":[49,77],"documents,":[50],"systematically":[52],"generate":[53],"semantically-oriented":[54],"questions":[55,72],"salient":[58],"sentence":[59,91],"one":[61],"document":[62],"and":[63,117,159,176,188,197,202],"challenge":[64],"the":[65,83,90,94,109,125,146],"model,":[66],"during":[67],"pre-training,":[68],"to":[69,88,111,148,195],"answer":[70],"these":[71],"while":[73,99],"\"peeking\"":[74],"other":[76],"documents.":[78],"similar":[81],"manner,":[82],"is":[85],"also":[86],"challenged":[87],"recover":[89,113],"which":[93],"was":[96],"generated,":[97],"again":[98],"leveraging":[100],"information.":[102],"This":[103],"QA":[106],"formulation":[107,144],"directs":[108],"better":[112],"cross-text":[114],"informational":[115],"relations,":[116],"introduces":[118],"natural":[120],"augmentation":[121],"artificially":[123],"increases":[124],"data.":[127],"Further,":[128],"unlike":[129],"prior":[130],"focus":[134],"on":[135],"either":[136],"classification":[137],"or":[138],"summarization":[139],"tasks,":[140,183],"our":[141,170],"objective":[143],"enables":[145],"perform":[149],"tasks":[150],"involve":[152],"both":[153],"short":[154],"text":[155,161],"generation":[156,162],"(e.g.,":[157,163],"QA)":[158],"long":[160],"summarization).":[164],"Following":[165],"scheme,":[167],"pre-train":[169],"--":[172,175],"termed":[173],"QAmden":[174],"evaluate":[177],"its":[178],"performance":[179],"across":[180],"several":[181],"including":[184],"QA,":[186],"summarization,":[187,190],"query-focused":[189],"yielding":[191],"up":[194],"7%,":[196],"significantly":[198],"outperforms":[199],"zero-shot":[200],"GPT-3.5":[201],"GPT-4.":[203]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}