{"id":"https://openalex.org/W7147155959","doi":"https://doi.org/10.48550/arxiv.2603.28651","title":"Not Search, But Scan: Benchmarking MLLMs on Scan-Oriented Academic Paper Reasoning","display_name":"Not Search, But Scan: Benchmarking MLLMs on Scan-Oriented Academic Paper Reasoning","publication_year":2026,"publication_date":"2026-03-27","ids":{"openalex":"https://openalex.org/W7147155959","doi":"https://doi.org/10.48550/arxiv.2603.28651"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.28651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.28651","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.2603.28651","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132583512","display_name":"Rongjin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li, Rongjin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132612667","display_name":"Zichen Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Zichen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121768734","display_name":"Xianghe Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xianghe","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034376319","display_name":"Xinyi Hu","orcid":"https://orcid.org/0000-0003-2078-7720"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Xinyi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132613506","display_name":"Zhengyu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zhengyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132568634","display_name":"Zhengyu Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Zhengyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132610943","display_name":"Yiling Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Yiling","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132581776","display_name":"Jiayuan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jiayuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103782544","display_name":"Weisheng Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Weisheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132574620","display_name":"Jiacheng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jiacheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072316255","display_name":"Zhongjun Yang","orcid":"https://orcid.org/0000-0002-4541-0316"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zhongjun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132697062","display_name":"Haihong E","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"E, Haihong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":12,"corresponding_author_ids":["https://openalex.org/A5132583512"],"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":0.4641999900341034,"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":0.4641999900341034,"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/T13629","display_name":"Text Readability and Simplification","score":0.11429999768733978,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.1120000034570694,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7706999778747559},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7257999777793884},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6593999862670898},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.652999997138977},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5519000291824341},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4733000099658966},{"id":"https://openalex.org/keywords/qualitative-reasoning","display_name":"Qualitative reasoning","score":0.3522999882698059}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7706999778747559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7432000041007996},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7257999777793884},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6593999862670898},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.652999997138977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5778999924659729},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5519000291824341},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4733000099658966},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.37070000171661377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3677000105381012},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3434000015258789},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3239000141620636},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.3147999942302704},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.28651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.28651","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.2603.28651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.28651","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":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8020284175872803}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,107,169,190,200,206],"rapid":[2],"progress":[3],"of":[4,161,182,205],"multimodal":[5],"large":[6],"language":[7],"models":[8,96,151],"(MLLMs),":[9],"AI":[10],"already":[11],"performs":[12],"well":[13],"at":[14],"literature":[15],"retrieval":[16],"and":[17,72,99,129,132,139,156,188,202],"certain":[18],"reasoning":[19,46,59,140],"tasks,":[20],"serving":[21],"as":[22],"a":[23,51,81,90,144,158],"capable":[24],"assistant":[25],"to":[26,50,66,97,109,198],"human":[27,104],"researchers,":[28,105],"yet":[29],"it":[30],"remains":[31],"far":[32],"from":[33,121],"autonomous":[34],"research.":[35],"The":[36,113],"fundamental":[37],"reason":[38],"is":[39,47],"that":[40,94],"current":[41,183],"work":[42,204],"on":[43,55,185],"academic":[44,85],"paper":[45,86],"largely":[48],"confined":[49],"search-oriented":[52],"paradigm":[53],"centered":[54],"pre-specified":[56],"targets,":[57],"with":[58,143],"grounded":[60],"in":[61],"relevance":[62],"retrieval,":[63],"which":[64],"struggles":[65],"support":[67],"researcher-style":[68],"full-document":[69],"understanding,":[70],"reasoning,":[71],"verification.":[73],"To":[74],"bridge":[75],"this":[76],"gap,":[77],"we":[78],"propose":[79],"\\textbf{ScholScan},":[80],"new":[82],"benchmark":[83,114],"for":[84,136,164],"reasoning.":[87],"ScholScan":[88,197],"introduces":[89],"scan-oriented":[91,186,207],"task":[92,208],"setting":[93],"asks":[95],"read":[98],"cross-check":[100],"entire":[101],"papers":[102],"like":[103],"scanning":[106],"document":[108],"identify":[110],"consistency":[111],"issues.":[112],"comprises":[115],"1,800":[116],"carefully":[117],"annotated":[118],"questions":[119],"drawn":[120],"nine":[122],"error":[123,166],"categories":[124],"across":[125,152],"13":[126],"natural-science":[127],"domains":[128],"715":[130],"papers,":[131],"provides":[133],"detailed":[134],"annotations":[135],"evidence":[137],"localization":[138],"traces,":[141],"together":[142],"unified":[145],"evaluation":[146],"protocol.":[147],"We":[148,195],"assessed":[149],"15":[150],"24":[153],"input":[154],"configurations":[155],"conducted":[157],"fine-grained":[159],"analysis":[160],"MLLM":[162],"capabilities":[163],"all":[165],"categories.":[167],"Across":[168],"board,":[170],"retrieval-augmented":[171],"generation":[172],"(RAG)":[173],"methods":[174],"yield":[175],"no":[176],"significant":[177],"improvements,":[178],"revealing":[179],"systematic":[180],"deficiencies":[181],"MLLMs":[184],"tasks":[187],"underscoring":[189],"challenge":[191],"posed":[192],"by":[193],"ScholScan.":[194],"expect":[196],"be":[199],"leading":[201],"representative":[203],"paradigm.":[209]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}