{"id":"https://openalex.org/W4416260019","doi":"https://doi.org/10.48550/arxiv.2506.21581","title":"Evaluating the Robustness of Dense Retrievers in Interdisciplinary Domains","display_name":"Evaluating the Robustness of Dense Retrievers in Interdisciplinary Domains","publication_year":2025,"publication_date":"2025-06-16","ids":{"openalex":"https://openalex.org/W4416260019","doi":"https://doi.org/10.48550/arxiv.2506.21581"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2506.21581","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.21581","pdf_url":"https://arxiv.org/pdf/2506.21581","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.21581","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109746310","display_name":"Sarthak Chaturvedi","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chaturvedi, Sarthak","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103415600","display_name":"Anurag Acharya","orcid":"https://orcid.org/0000-0002-3883-5287"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Acharya, Anurag","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025769957","display_name":"Rounak Meyur","orcid":"https://orcid.org/0000-0002-7650-338X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meyur, Rounak","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Hayashi, Koby","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hayashi, Koby","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050892907","display_name":"Sai Munikoti","orcid":"https://orcid.org/0000-0002-1205-7405"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Munikoti, Sai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5087089195","display_name":"Sameera Horawalavithana","orcid":"https://orcid.org/0000-0002-0327-3819"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Horawalavithana, Sameera","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5109746310"],"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":0.9110000133514404,"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":0.9110000133514404,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.014399999752640724,"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/T10028","display_name":"Topic Modeling","score":0.007499999832361937,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7520999908447266},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6625000238418579},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5730000138282776},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5418000221252441},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5246000289916992},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.4812999963760376},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.39910000562667847}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8039000034332275},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7520999908447266},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6625000238418579},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5730000138282776},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5418000221252441},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5246000289916992},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5091000199317932},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5023000240325928},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.4812999963760376},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4239000082015991},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.39910000562667847},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3709000051021576},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.3375000059604645},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2621000111103058},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2506.21581","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.21581","pdf_url":"https://arxiv.org/pdf/2506.21581","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.21581","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.21581","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.21581","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.21581","pdf_url":"https://arxiv.org/pdf/2506.21581","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"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":{"Evaluation":[0,192],"benchmark":[1,120,155,180],"characteristics":[2],"may":[3],"distort":[4],"the":[5,45,118,125,140,153,172],"true":[6],"benefits":[7,47,94],"of":[8,48,185],"domain":[9,87,107,199],"adaptation":[10,88,108,200],"in":[11,22,139,189],"retrieval":[12,54,186],"models.":[13],"This":[14],"creates":[15],"misleading":[16],"assessments":[17,184],"that":[18,27,85,152,179,210,231],"influence":[19,44],"deployment":[20],"decisions":[21],"specialized":[23,190],"domains.":[24,191],"We":[25,71,143],"show":[26,90],"two":[28,76],"benchmarks":[29,77,146],"with":[30,78,102,121,194,204],"drastically":[31],"different":[32,79,92],"features":[33],"such":[34],"as":[35,55],"topic":[36,105,148],"diversity,":[37],"boundary":[38],"overlap,":[39],"and":[40,164,224],"semantic":[41,80,123,206],"complexity":[42],"can":[43],"perceived":[46,93],"fine-tuning.":[49],"Using":[50],"environmental":[51],"regulatory":[52,214],"document":[53,215],"a":[56,136],"case":[57],"study,":[58],"we":[59],"fine-tune":[60],"ColBERTv2":[61],"model":[62],"on":[63,96,117],"Environmental":[64],"Impact":[65],"Statements":[66],"(EIS)":[67],"from":[68],"federal":[69],"agencies.":[70],"evaluate":[72],"these":[73,145],"models":[74,127],"across":[75],"structures.":[81],"Our":[82,217],"findings":[83,218],"reveal":[84,208],"identical":[86],"approaches":[89],"very":[91],"depending":[95],"evaluation":[97],"methodology.":[98],"On":[99],"one":[100],"benchmark,":[101],"clearly":[103],"separated":[104],"boundaries,":[106],"shows":[109,156],"small":[110],"improvements":[111,130,209],"(maximum":[112],"0.61%":[113],"NDCG":[114,134],"gain).":[115],"However,":[116],"other":[119],"overlapping":[122,205],"structures,":[124],"same":[126],"demonstrate":[128,178],"large":[129],"(up":[131],"to":[132,171],"2.22%":[133],"gain),":[135],"3.6-fold":[137],"difference":[138],"performance":[141,174],"benefit.":[142],"compare":[144],"through":[147],"diversity":[149],"metrics,":[150],"finding":[151],"higher-performing":[154],"11%":[157],"higher":[158],"average":[159],"cosine":[160],"distances":[161],"between":[162],"contexts":[163],"23%":[165],"lower":[166],"silhouette":[167],"scores,":[168],"directly":[169],"contributing":[170],"observed":[173],"difference.":[175],"These":[176],"results":[177],"selection":[181],"strongly":[182],"determines":[183],"system":[187],"effectiveness":[188],"frameworks":[193],"well-separated":[195],"topics":[196],"regularly":[197],"underestimate":[198],"benefits,":[201],"while":[202],"those":[203],"boundaries":[207],"better":[211],"reflect":[212],"real-world":[213],"complexity.":[216],"have":[219],"important":[220],"implications":[221],"for":[222,228],"developing":[223],"deploying":[225],"AI":[226],"systems":[227],"interdisciplinary":[229],"domains":[230],"integrate":[232],"multiple":[233],"topics.":[234]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
