{"id":"https://openalex.org/W7140312832","doi":"https://doi.org/10.48550/arxiv.2603.22608","title":"Understanding LLM Performance Degradation in Multi-Instance Processing: The Roles of Instance Count and Context Length","display_name":"Understanding LLM Performance Degradation in Multi-Instance Processing: The Roles of Instance Count and Context Length","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140312832","doi":"https://doi.org/10.48550/arxiv.2603.22608"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.22608","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22608","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.22608","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130600211","display_name":"Jingxuan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jingxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130571861","display_name":"Mohammad Taher Pilehvar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pilehvar, Mohammad Taher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130574145","display_name":"Jose Camacho-Collados","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Camacho-Collados, Jose","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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/T10028","display_name":"Topic Modeling","score":0.1851000040769577,"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":0.1851000040769577,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.13279999792575836,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.11670000106096268,"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/context","display_name":"Context (archaeology)","score":0.7182999849319458},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5679000020027161},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.5001000165939331},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.4397999942302704},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.2709999978542328}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7182999849319458},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6518999934196472},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5679000020027161},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.5001000165939331},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.4397999942302704},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3971000015735626},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3686999976634979},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33880001306533813},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.321399986743927},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27720001339912415},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.22608","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22608","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":"doi:10.48550/arxiv.2603.22608","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22608","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Users":[0],"often":[1],"rely":[2],"on":[3,54,66,123,148],"Large":[4],"Language":[5],"Models":[6],"(LLMs)":[7],"for":[8,91,111,160],"processing":[9,86],"multiple":[10],"documents":[11],"or":[12],"performing":[13],"analysis":[14,129],"over":[15],"a":[16,27,47,80,105,120,145],"number":[17,28,141],"of":[18,26,29,39,83,89,107,114,142],"instances.":[19],"For":[20],"example,":[21],"analysing":[22],"the":[23,37,84,140,149],"overall":[24],"sentiment":[25,38],"movie":[30],"reviews":[31],"requires":[32],"an":[33],"LLM":[34,52,158],"to":[35,45,166],"process":[36],"each":[40],"review":[41],"individually":[42],"in":[43,93,171],"order":[44],"provide":[46],"final":[48,150],"aggregated":[49],"answer.":[50],"While":[51],"performance":[53,109,121,159],"such":[55],"individual":[56],"tasks":[57,92],"is":[58,135],"generally":[59],"high,":[60],"there":[61],"has":[62,144],"been":[63],"little":[64],"research":[65],"how":[67],"LLMs":[68,90,103],"perform":[69,79],"when":[70,156],"dealing":[71],"with":[72,137],"multi-instance":[73,85],"inputs.":[74],"In":[75],"this":[76,138],"paper,":[77],"we":[78],"comprehensive":[81],"evaluation":[82],"(MIP)":[87],"ability":[88],"which":[94],"they":[95],"excel":[96],"individually.":[97],"The":[98],"results":[99],"show":[100],"that":[101,131,155],"all":[102],"follow":[104],"pattern":[106],"slight":[108],"degradation":[110],"small":[112],"numbers":[113],"instances":[115,143],"(approximately":[116],"20-100),":[117],"followed":[118],"by":[119],"collapse":[122],"larger":[124],"instance":[125,173],"counts.":[126],"Crucially,":[127],"our":[128],"shows":[130],"while":[132],"context":[133,168],"length":[134,169],"associated":[136],"degradation,":[139],"stronger":[146],"effect":[147],"results.":[151],"This":[152],"finding":[153],"suggests":[154],"optimising":[157],"MIP,":[161],"attention":[162],"should":[163],"be":[164],"paid":[165],"both":[167],"and,":[170],"particular,":[172],"count.":[174]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-26T00:00:00"}
