{"id":"https://openalex.org/W7155034514","doi":"https://doi.org/10.48550/arxiv.2604.17621","title":"KnowledgeBerg: Evaluating Systematic Knowledge Coverage and Compositional Reasoning in Large Language Models","display_name":"KnowledgeBerg: Evaluating Systematic Knowledge Coverage and Compositional Reasoning in Large Language Models","publication_year":2026,"publication_date":"2026-04-19","ids":{"openalex":"https://openalex.org/W7155034514","doi":"https://doi.org/10.48550/arxiv.2604.17621"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.17621","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17621","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.2604.17621","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015156155","display_name":"Xiao Zhang","orcid":"https://orcid.org/0000-0003-2547-7262"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134108186","display_name":"Qianru Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meng, Qianru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060987863","display_name":"Yongjian Chen","orcid":"https://orcid.org/0000-0002-2930-8450"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yongjian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134144341","display_name":"Yumeng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yumeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134131039","display_name":"Johan Bos","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bos, Johan","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/T10028","display_name":"Topic Modeling","score":0.4221000075340271,"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":0.4221000075340271,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.0820000022649765,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.07999999821186066,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/cardinality","display_name":"Cardinality (data modeling)","score":0.6643999814987183},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.6524999737739563},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5845999717712402},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.578000009059906},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4677000045776367},{"id":"https://openalex.org/keywords/universe","display_name":"Universe","score":0.4366999864578247},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.41690000891685486}],"concepts":[{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.6643999814987183},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.6524999737739563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5938000082969666},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5845999717712402},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.578000009059906},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4677000045776367},{"id":"https://openalex.org/C84999194","wikidata":"https://www.wikidata.org/wiki/Q1","display_name":"Universe","level":2,"score":0.4366999864578247},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38690000772476196},{"id":"https://openalex.org/C156340839","wikidata":"https://www.wikidata.org/wiki/Q2704791","display_name":"Enumeration","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3375999927520752},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3147999942302704},{"id":"https://openalex.org/C50335755","wikidata":"https://www.wikidata.org/wiki/Q483247","display_name":"Phenomenon","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.2782000005245209}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.17621","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17621","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.2604.17621","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17621","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":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.41859301924705505}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Many":[0],"real-world":[1],"questions":[2,69],"appear":[3],"deceptively":[4],"simple":[5],"yet":[6],"implicitly":[7],"demand":[8],"two":[9,41],"capabilities:":[10],"(i)":[11],"systematic":[12],"coverage":[13],"of":[14,33,48,57,66,114],"a":[15,27,64],"bounded":[16,175],"knowledge":[17,44,169],"universe":[18,101],"and":[19,52,78,103,126,137,143,153,170],"(ii)":[20],"compositional":[21,58,172],"set-based":[22],"reasoning":[23,53,130,173],"over":[24,174],"that":[25],"universe,":[26,51],"phenomenon":[28],"we":[29],"term":[30],"\"the":[31],"tip":[32],"the":[34,46,49,55],"iceberg.\"":[35],"We":[36,61],"formalize":[37],"this":[38],"challenge":[39],"through":[40],"orthogonal":[42],"dimensions:":[43],"width,":[45],"cardinality":[47],"required":[50],"depth,":[54],"number":[56],"set":[59],"operations.":[60],"introduce":[62],"KnowledgeBerg,":[63],"benchmark":[65],"4,800":[67],"multiple-choice":[68],"derived":[70],"from":[71],"1,183":[72],"enumeration":[73,102],"seeds":[74],"spanning":[75],"10":[76],"domains":[77],"17":[79],"languages,":[80],"with":[81],"universes":[82],"grounded":[83],"in":[84,163],"authoritative":[85],"sources":[86],"to":[87,123,151],"ensure":[88],"reproducibility.":[89],"Representative":[90],"open-source":[91],"LLMs":[92,166],"demonstrate":[93],"severe":[94],"limitations,":[95],"achieving":[96],"only":[97],"5.26-36.88":[98],"F1":[99],"on":[100,106],"16.00-44.19":[104],"accuracy":[105],"knowledge-grounded":[107],"reasoning.":[108],"Diagnostic":[109],"analyses":[110],"reveal":[111],"three":[112],"stages":[113],"failure:":[115],"completeness,":[116],"or":[117,121,128],"missing":[118],"knowledge;":[119],"awareness,":[120],"failure":[122],"identify":[124],"requirements;":[125],"application,":[127],"incorrect":[129],"execution.":[131],"This":[132],"pattern":[133],"persists":[134],"across":[135],"languages":[136],"model":[138],"scales.":[139],"Although":[140],"test-time":[141],"compute":[142],"retrieval":[144],"augmentation":[145],"yield":[146],"measurable":[147],"gains":[148],"--":[149,157],"up":[150],"4.35":[152],"3.78":[154],"points,":[155],"respectively":[156],"substantial":[158],"gaps":[159],"remain,":[160],"exposing":[161],"limitations":[162],"how":[164],"current":[165],"organize":[167],"structured":[168],"execute":[171],"domains.":[176],"The":[177],"dataset":[178],"is":[179],"available":[180],"at":[181],"https://huggingface.co/datasets/2npc/KnowledgeBerg":[182]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-22T00:00:00"}
