{"id":"https://openalex.org/W7150962899","doi":"https://doi.org/10.48550/arxiv.2604.02934","title":"PolyReal: A Benchmark for Real-World Polymer Science Workflows","display_name":"PolyReal: A Benchmark for Real-World Polymer Science Workflows","publication_year":2026,"publication_date":"2026-04-03","ids":{"openalex":"https://openalex.org/W7150962899","doi":"https://doi.org/10.48550/arxiv.2604.02934"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.02934","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02934","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":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.2604.02934","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133010407","display_name":"Wanhao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liu, Wanhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121662050","display_name":"Weida Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Weida","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010620570","display_name":"Jiaqing Xie","orcid":"https://orcid.org/0000-0001-7634-4457"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Jiaqing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yang, Suorong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Suorong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133023902","display_name":"Jue Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066415914","display_name":"Benteng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Benteng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126322329","display_name":"Guangtao Mei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mei, Guangtao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133021993","display_name":"Zonglin Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zonglin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133040161","display_name":"Shufei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Shufei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133052289","display_name":"Yuchun Mo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mo, Yuchun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133020957","display_name":"Lang Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Lang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133046666","display_name":"Jin Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Jin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133016897","display_name":"Houqiang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Houqiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133007160","display_name":"Wanli Ouyang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ouyang, Wanli","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133000412","display_name":"Yuqiang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yuqiang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":15,"corresponding_author_ids":["https://openalex.org/A5133010407"],"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/T11948","display_name":"Machine Learning in Materials Science","score":0.8313999772071838,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.8313999772071838,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.03790000081062317,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.03009999915957451,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7797999978065491},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.7705000042915344},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.6484000086784363},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5083000063896179},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.4672999978065491},{"id":"https://openalex.org/keywords/data-driven","display_name":"Data-driven","score":0.44339999556541443},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.4410000145435333}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7797999978065491},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7705000042915344},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6920999884605408},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.6484000086784363},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5083000063896179},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.4672999978065491},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.44339999556541443},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.4410000145435333},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4375999867916107},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.4361000061035156},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.38659998774528503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3490000069141388},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.33889999985694885},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2687999904155731},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.25949999690055847}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.02934","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02934","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":"doi:10.48550/arxiv.2604.02934","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02934","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"Large":[1],"Language":[2],"Models":[3],"(MLLMs)":[4],"excel":[5],"in":[6,76,192],"general":[7],"domains":[8],"but":[9],"struggle":[10],"with":[11],"complex,":[12],"real-world":[13,49,77,170,193],"science.":[14],"We":[15,68],"posit":[16],"that":[17,168],"polymer":[18,45,88],"science,":[19],"an":[20,30],"interdisciplinary":[21],"field":[22],"spanning":[23],"chemistry,":[24],"physics,":[25],"biology,":[26],"and":[27,55,111,149,162,183],"engineering,":[28],"is":[29],"ideal":[31],"high-stakes":[32],"testbed":[33],"due":[34],"to":[35,44,57,80],"its":[36,163],"diverse":[37],"multimodal":[38,73],"data.":[39],"Yet,":[40],"existing":[41],"benchmarks":[42],"related":[43],"science":[46],"largely":[47],"overlook":[48],"workflows,":[50],"limiting":[51],"their":[52],"practical":[53,186],"utility":[54],"failing":[56],"systematically":[58],"evaluate":[59,81],"MLLMs":[60,82,121],"across":[61],"the":[62,84],"full,":[63],"practice-grounded":[64],"lifecycle":[65,86],"of":[66,87,119],"experimentation.":[67,89],"introduce":[69],"PolyReal,":[70],"a":[71,125,155,185],"novel":[72],"benchmark":[74,187],"grounded":[75],"scientific":[78,160,194],"practices":[79],"on":[83,122,132,142],"full":[85],"It":[90],"covers":[91],"five":[92],"critical":[93],"capabilities:":[94],"(1)":[95],"foundational":[96],"knowledge":[97,161],"application;":[98],"(2)":[99],"lab":[100],"safety":[101],"analysis;":[102],"(3)":[103],"experiment":[104],"mechanism":[105],"reasoning;":[106],"(4)":[107],"raw":[108],"data":[109],"extraction;":[110],"(5)":[112],"performance":[113],"&amp;":[114],"application":[115],"exploration.":[116],"Our":[117],"evaluation":[118,181],"leading":[120],"PolyReal":[123,177],"reveals":[124],"capability":[126],"imbalance.":[127],"While":[128],"models":[129],"perform":[130],"well":[131],"knowledge-intensive":[133],"reasoning":[134],"(e.g.,":[135,145],"Experiment":[136],"Mechanism":[137],"Reasoning),":[138],"they":[139],"drop":[140],"sharply":[141],"practice-based":[143],"tasks":[144,171],"Lab":[146],"Safety":[147],"Analysis":[148],"Raw":[150],"Data":[151],"Extraction).":[152],"This":[153],"exposes":[154],"severe":[156],"gap":[157,182],"between":[158],"abstract":[159],"practical,":[164],"context-dependent":[165],"application,":[166],"showing":[167],"these":[169],"remain":[172],"challenging":[173],"for":[174,188],"MLLMs.":[175],"Thus,":[176],"helps":[178],"address":[179],"this":[180],"provides":[184],"assessing":[189],"AI":[190],"systems":[191],"workflows.":[195]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2026-04-07T00:00:00"}
