{"id":"https://openalex.org/W4412945443","doi":"https://doi.org/10.18653/v1/2025.acl-long.560","title":"MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models","display_name":"MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412945443","doi":"https://doi.org/10.18653/v1/2025.acl-long.560"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-long.560","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.560","pdf_url":"https://aclanthology.org/2025.acl-long.560.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-long.560.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009783636","display_name":"Zhongzhan Huang","orcid":"https://orcid.org/0000-0001-8422-2898"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhongzhan Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047526703","display_name":"Guoming Ling","orcid":"https://orcid.org/0000-0001-7886-996X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guoming Ling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102853319","display_name":"Shanshan Zhong","orcid":"https://orcid.org/0000-0003-3082-7351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shanshan Zhong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061828638","display_name":"Hefeng Wu","orcid":"https://orcid.org/0000-0002-2132-6515"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hefeng Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5091921032","display_name":"Liang Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang Lin","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":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"11442","last_page":"11460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9901999831199646,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9901999831199646,"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/T10028","display_name":"Topic Modeling","score":0.9868000149726868,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9204999804496765,"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/computer-science","display_name":"Computer science","score":0.7702826261520386},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7603209018707275},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5839331746101379},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.06925731897354126},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.05012449622154236}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7702826261520386},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7603209018707275},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5839331746101379},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.06925731897354126},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.05012449622154236},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.acl-long.560","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.560","pdf_url":"https://aclanthology.org/2025.acl-long.560.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.acl-long.560","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.560","pdf_url":"https://aclanthology.org/2025.acl-long.560.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3972927233","display_name":null,"funder_award_id":"62325605","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6248067210","display_name":null,"funder_award_id":"2023A1515012845","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G7073678484","display_name":null,"funder_award_id":"2021ZD0111601","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"},{"id":"https://openalex.org/G7308144093","display_name":null,"funder_award_id":"62272494","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7519033713","display_name":null,"funder_award_id":"2023A1515011374","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412945443.pdf","grobid_xml":"https://content.openalex.org/works/W4412945443.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526"],"abstract_inverted_index":{"Long":[0],"Context":[1],"Understanding":[2],"(LCU)":[3],"is":[4],"a":[5,64,135],"critical":[6],"area":[7],"for":[8,28,70,153],"exploration":[9],"in":[10,32,58],"current":[11],"large":[12],"language":[13],"models":[14],"(LLMs).However,":[15],"due":[16],"to":[17,114,141],"the":[18,56,78,118,147],"inherently":[19],"lengthy":[20],"nature":[21],"of":[22,103,117,127,150],"long-text":[23],"data,":[24],"existing":[25,48],"LCU":[26,49,80,148],"benchmarks":[27,50],"LLMs":[29],"often":[30],"result":[31],"prohibitively":[33],"high":[34],"evaluation":[35,111],"costs,":[36],"like":[37],"testing":[38],"time":[39],"and":[40,97,157],"inference":[41],"expenses.Through":[42],"extensive":[43],"experimentation,":[44],"we":[45,62,83],"discover":[46],"that":[47],"exhibit":[51],"significant":[52],"redundancy,":[53],"which":[54],"means":[55],"inefficiency":[57],"evaluation.In":[59],"this":[60],"paper,":[61],"propose":[63],"concise":[65],"data":[66,72,156],"compression":[67],"method":[68],"tailored":[69],"longtext":[71],"with":[73,129],"sparse":[74],"information":[75],"characteristics.By":[76],"pruning":[77],"well-known":[79],"benchmark":[81,86],"LongBench,":[82],"create":[84],"MiniLongBench.This":[85],"includes":[87],"only":[88,115],"237":[89],"test":[90],"samples":[91],"across":[92],"six":[93],"major":[94],"task":[95],"categories":[96],"21":[98],"distinct":[99],"tasks.Through":[100],"empirical":[101],"analysis":[102],"over":[104],"60":[105],"LLMs,":[106],"MiniLongBench":[107],"achieves":[108],"an":[109,122],"average":[110,123],"cost":[112],"reduced":[113],"4.5%":[116],"original":[119],"while":[120],"maintaining":[121],"rank":[124],"correlation":[125],"coefficient":[126],"0.97":[128],"Long-Bench":[130],"results.Therefore,":[131],"our":[132,154],"MiniLongBench,":[133],"as":[134],"low-cost":[136],"benchmark,":[137],"holds":[138],"great":[139],"potential":[140],"substantially":[142],"drive":[143],"future":[144],"research":[145],"into":[146],"capabilities":[149],"LLMs.See":[151],"Github":[152],"code,":[155],"tutorial.Summarization":[158],"GovReport":[159],"3-1":[160],"Rouge-L":[161,170,179,188,217],"English":[162,171,180,200,209,218,238,247],"8,734":[163],"7592":[164],"12":[165,212],"(":[166,175,184,193,204,213,222,231,242,251,260,272,282],"94%)":[167,214],"QMSum":[168],"3-2":[169],"10,614":[172],"8,253":[173],"6":[174,192],"97%)":[176,194],"MultiNews":[177],"3-3":[178],"2,113":[181],"1,785":[182],"11":[183],"95%)":[185,273,283],"VCSUM":[186],"3-4":[187],"Chinese":[189,227,256],"15,380":[190],"10,400":[191],"Few-shot":[195],"Learning":[196],"TREC":[197],"4-1":[198],"Acc.(CLS)":[199,226],"5,177":[201],"6,077":[202],"8":[203,230],"96%)":[205,232],"TriviaQA":[206],"4-2":[207],"F1":[208],"8,209":[210],"9,719":[211],"SAMSum":[215],"4-3":[216],"6,258":[219],"5,974":[220],"15":[221,250,259],"93%)":[223,252,261],"LSHT":[224],"4-4":[225],"22,337":[228],"22,759":[229],"Synthetic":[233],"Task":[234],"PassageCount":[235],"5-1":[236],"Acc.(EM)":[237,246,255],"11,414":[239],"10,627":[240],"4":[241],"98%)":[243],"PassageRetrieval-en":[244],"5-2":[245],"9,289":[248],"9,394":[249],"PassageRetrieval-zh":[253],"5-3":[254],"6,745":[257],"6,684":[258],"Code":[262],"Completion":[263],"LCC":[264],"6-1":[265],"Edit":[266,276],"Sim":[267,277],"Python/C#/Java":[268],"1,235":[269],"1,187":[270],"26":[271],"RepoBench-P":[274],"6-2":[275],"Python/Jave":[278],"4,206":[279],"3,723":[280],"23":[281]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
