{"id":"https://openalex.org/W4416034679","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.726","title":"MultiConIR: Towards Multi-Condition Information Retrieval","display_name":"MultiConIR: Towards Multi-Condition Information Retrieval","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416034679","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.726"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.726","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.726","pdf_url":"https://aclanthology.org/2025.findings-emnlp.726.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.726.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101930574","display_name":"Xuan Lu","orcid":"https://orcid.org/0000-0002-8010-8075"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuan Lu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101881653","display_name":"Sifan Liu","orcid":"https://orcid.org/0000-0003-4473-1262"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sifan Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Bochao Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bochao Yin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029489135","display_name":"Yongqi Li","orcid":"https://orcid.org/0000-0001-5649-1871"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yongqi Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006817088","display_name":"Xinghao Chen","orcid":"https://orcid.org/0000-0002-2102-8235"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinghao Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109299393","display_name":"Hui Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hui Su","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085787425","display_name":"Yaohui Jin","orcid":"https://orcid.org/0000-0001-6158-6277"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yaohui Jin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049963367","display_name":"Wenjun Zeng","orcid":"https://orcid.org/0000-0003-2531-3137"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenjun Zeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5103000631","display_name":"Xiaoyu Shen","orcid":"https://orcid.org/0000-0002-0217-2469"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoyu Shen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28878753,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"13471","last_page":"13494"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.2937000095844269,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.2937000095844269,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.14069999754428864,"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/T10320","display_name":"Neural Networks and Applications","score":0.049400001764297485,"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/document-retrieval","display_name":"Document retrieval","score":0.42660000920295715},{"id":"https://openalex.org/keywords/data-retrieval","display_name":"Data retrieval","score":0.3027999997138977},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.3005000054836273},{"id":"https://openalex.org/keywords/information-system","display_name":"Information system","score":0.2818000018596649},{"id":"https://openalex.org/keywords/adversarial-information-retrieval","display_name":"Adversarial information retrieval","score":0.2759999930858612}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6575000286102295},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.51910001039505},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.42660000920295715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3409000039100647},{"id":"https://openalex.org/C551230270","wikidata":"https://www.wikidata.org/wiki/Q4368942","display_name":"Data retrieval","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C180198813","wikidata":"https://www.wikidata.org/wiki/Q121182","display_name":"Information system","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C116425068","wikidata":"https://www.wikidata.org/wiki/Q4686695","display_name":"Adversarial information retrieval","level":5,"score":0.2759999930858612},{"id":"https://openalex.org/C90288658","wikidata":"https://www.wikidata.org/wiki/Q3318149","display_name":"Human\u2013computer information retrieval","level":3,"score":0.27239999175071716},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2605000138282776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.726","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.726","pdf_url":"https://aclanthology.org/2025.findings-emnlp.726.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.726","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.726","pdf_url":"https://aclanthology.org/2025.findings-emnlp.726.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416034679.pdf","grobid_xml":"https://content.openalex.org/works/W4416034679.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-condition":[0],"information":[1],"retrieval":[2,22],"(IR)":[3],"presents":[4],"a":[5,16,57],"significant,":[6],"yet":[7],"underexplored":[8],"challenge":[9],"for":[10,103,133],"existing":[11],"systems.This":[12],"paper":[13],"introduces":[14],"MULTICONIR,":[15],"benchmark":[17],"specifically":[18],"designed":[19],"to":[20,76,83,116],"evaluate":[21],"and":[23,47,62,80,86,100,120],"reranking":[24],"models":[25,55],"under":[26],"nuanced":[27],"multi-condition":[28],"query":[29,48,69,84],"scenarios":[30],"across":[31],"five":[32],"diverse":[33],"domains.We":[34],"systematically":[35],"assess":[36],"model":[37],"capabilities":[38],"through":[39],"three":[40],"critical":[41,58],"tasks:":[42],"complexity":[43,70],"robustness,":[44],"relevance":[45,78],"monotonicity,":[46,79],"format":[49],"sensitivity.Our":[50],"extensive":[51],"experiments":[52],"on":[53],"15":[54],"reveal":[56],"vulnerability:":[59],"most":[60],"retrievers":[61],"rerankers":[63],"exhibit":[64],"severe":[65],"performance":[66,90,95,118],"degradation":[67],"as":[68],"increases.Key":[71],"deficiencies":[72],"include":[73],"widespread":[74],"failure":[75],"maintain":[77],"high":[81],"sensitivity":[82],"style":[85],"condition":[87,123],"placement.The":[88],"superior":[89],"of":[91],"GPT-4o":[92],"reveals":[93],"the":[94,113],"gap":[96],"between":[97],"IR":[98,135],"systems":[99,136],"advanced":[101],"LLM":[102],"handling":[104],"sophisticated":[105],"natural":[106],"language":[107],"queries.Furthermore,":[108],"this":[109],"work":[110],"delves":[111],"into":[112],"factors":[114],"contributing":[115],"reranker":[117],"deterioration":[119],"examines":[121],"how":[122],"positioning":[124],"within":[125],"queries":[126],"affects":[127],"similarity":[128],"assessment,":[129],"providing":[130],"crucial":[131],"insights":[132],"advancing":[134],"towards":[137],"complex":[138],"search":[139],"scenarios.":[140]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-08T00:00:00"}
