{"id":"https://openalex.org/W7163892147","doi":"https://doi.org/10.48550/arxiv.2606.06880","title":"Towards Retrieving Interaction Spaces for Agentic Search","display_name":"Towards Retrieving Interaction Spaces for Agentic Search","publication_year":2026,"publication_date":"2026-06-05","ids":{"openalex":"https://openalex.org/W7163892147","doi":"https://doi.org/10.48550/arxiv.2606.06880"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.06880","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06880","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.06880","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012958162","display_name":"Shengyao Zhuang","orcid":"https://orcid.org/0000-0002-6711-0955"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhuang, Shengyao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138166085","display_name":"Yuansheng Ni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ni, Yuansheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084148879","display_name":"Hengxin Fun","orcid":"https://orcid.org/0009-0009-0157-0017"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fun, Hengxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138144770","display_name":"Jimmy Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Jimmy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138110146","display_name":"Xueguang Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Xueguang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.8086000084877014,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.8086000084877014,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.02930000051856041,"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":0.024700000882148743,"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/construct","display_name":"Construct (python library)","score":0.7164000272750854},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.6789000034332275},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5353000164031982},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5005999803543091},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.4302999973297119},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4142000079154968},{"id":"https://openalex.org/keywords/vector-space-model","display_name":"Vector space model","score":0.40540000796318054}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7222999930381775},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.7164000272750854},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.6789000034332275},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5403000116348267},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5353000164031982},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5005999803543091},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4302999973297119},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4142000079154968},{"id":"https://openalex.org/C89686163","wikidata":"https://www.wikidata.org/wiki/Q1187982","display_name":"Vector space model","level":2,"score":0.40540000796318054},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3926999866962433},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.37279999256134033},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.35359999537467957},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C13854087","wikidata":"https://www.wikidata.org/wiki/Q1061656","display_name":"Interaction design","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.30250000953674316},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.26460000872612}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.06880","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06880","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.06880","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06880","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Retrieval":[0],"for":[1,83,138,166],"search":[2,85],"agents":[3,34],"is":[4,61,86],"still":[5],"inherited":[6],"from":[7],"non-agentic":[8],"information":[9],"retrieval:":[10],"a":[11,20,62,105,125,141],"retriever":[12],"ranks":[13],"the":[14,17,39,65,73,79,95,109,111,131,156,173,187],"corpus":[15,28,41,74,110],"and":[16,48,68,130],"agent":[18,112],"reads":[19],"small":[21],"set":[22],"of":[23,81,108,143,186,207],"returned":[24],"documents.":[25],"Recent":[26],"direct":[27],"interaction":[29,53,103,157],"(DCI)":[30],"work":[31],"shows":[32],"that":[33,78,92],"can":[35,113],"instead":[36],"interact":[37],"with":[38,115,180,205],"raw":[40],"through":[42],"shell":[43,59],"tools":[44],"such":[45],"as":[46,72],"grep":[47],"file":[49],"reads.":[50],"But":[51],"unbounded":[52],"does":[54],"not":[55,87],"scale:":[56],"every":[57],"broad":[58],"command":[60],"scan":[63],"over":[64],"whole":[66],"corpus,":[67],"latency":[69],"degrades":[70,202],"sharply":[71],"grows.":[75],"We":[76],"argue":[77],"role":[80],"retrieval":[82],"agentic":[84],"just":[88],"to":[89,100,154,203],"select":[90],"documents":[91,161],"fit":[93],"in":[94],"LLM":[96],"context":[97],"window,":[98],"but":[99],"construct":[101,155],"an":[102],"space:":[104],"bounded":[106],"subset":[107],"explore":[114],"associated":[116],"tools.":[117],"Two":[118],"design":[119],"consequences":[120],"follow.":[121],"The":[122],"space":[123],"needs":[124],"boundary":[126],"supplied":[127],"by":[128],"retrieval,":[129],"objects":[132],"within":[133],"it":[134],"should":[135],"be":[136],"processed":[137,163],"interaction.":[139],"As":[140],"proof":[142],"concept,":[144],"we":[145,151],"propose":[146],"RISE":[147,171],"(Retrieving":[148],"Interaction":[149],"SpacE):":[150],"use":[152],"BM25":[153],"space;":[158],"meanwhile,":[159],"its":[160],"are":[162],"during":[164],"indexing":[165],"shell-style":[167],"navigation.":[168],"On":[169],"BrowseComp-Plus,":[170],"matches":[172],"pure-shell":[174],"DCI":[175,199],"baseline":[176],"at":[177,182],"78%":[178],"accuracy":[179],"gpt-5.4-mini":[181],"roughly":[183],"one":[184],"quarter":[185],"per-query":[188],"cost.":[189],"At":[190],"1M":[191],"documents,":[192],"RISE-BM25":[193],"reaches":[194],"81%":[195],"on":[196,200],"gpt-5.4-mini,":[197],"whereas":[198],"gpt-5.4-nano":[201],"60%":[204],"33":[206],"100":[208],"wall-clock":[209],"failures.":[210]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-09T00:00:00"}