{"id":"https://openalex.org/W7170133677","doi":"https://doi.org/10.48550/arxiv.2607.19935","title":"MOF-Sleuth: Tool-Grounded Reward Alignment for Explainable Fine-Grained MOF CIF Auditing","display_name":"MOF-Sleuth: Tool-Grounded Reward Alignment for Explainable Fine-Grained MOF CIF Auditing","publication_year":2026,"publication_date":"2026-07-22","ids":{"openalex":"https://openalex.org/W7170133677","doi":"https://doi.org/10.48550/arxiv.2607.19935"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.19935","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.19935","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":null,"license_id":null,"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.2607.19935","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5143502026","display_name":"Yu Shen Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143527143","display_name":"Zhiwei Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zhiwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137913874","display_name":"D L Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Diandian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011830457","display_name":"Kun Peng","orcid":"https://orcid.org/0000-0001-6885-9899"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027433551","display_name":"Fangfang Yuan","orcid":"https://orcid.org/0000-0003-2926-8951"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Fangfang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143530262","display_name":"Cong Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Cong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037831162","display_name":"Chaozhuo Li","orcid":"https://orcid.org/0000-0002-9867-1712"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Chaozhuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143528165","display_name":"Zhiyuan Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Zhiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037159025","display_name":"Yanbing Liu","orcid":"https://orcid.org/0000-0002-9662-3952"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yanbing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5074545617","display_name":"Guobin Zhao","orcid":"https://orcid.org/0000-0002-7728-4211"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Guobin","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/T10096","display_name":"Metal-Organic Frameworks: Synthesis and Applications","score":0.8065000176429749,"subfield":{"id":"https://openalex.org/subfields/1604","display_name":"Inorganic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10096","display_name":"Metal-Organic Frameworks: Synthesis and Applications","score":0.8065000176429749,"subfield":{"id":"https://openalex.org/subfields/1604","display_name":"Inorganic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.1370999962091446,"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/T10578","display_name":"Supramolecular Chemistry and Complexes","score":0.006899999920278788,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/audit","display_name":"Audit","score":0.7300000190734863},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.557699978351593},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5569999814033508},{"id":"https://openalex.org/keywords/compromise","display_name":"Compromise","score":0.39739999175071716},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.36910000443458557},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.36640000343322754}],"concepts":[{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.7300000190734863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7185999751091003},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.557699978351593},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5569999814033508},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5291000008583069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.451200008392334},{"id":"https://openalex.org/C46355384","wikidata":"https://www.wikidata.org/wiki/Q726686","display_name":"Compromise","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3409000039100647},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.31220000982284546},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2770000100135803},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.2630999982357025}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.19935","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.19935","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.19935","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.19935","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.5176382064819336,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"metal-organic":[1],"framework":[2],"(MOF)":[3],"databases":[4],"support":[5],"simulation,":[6],"screening,":[7],"and":[8,18,28,58,76,86,96,101,112,130,143,146,158,184,218,227],"machine":[9],"learning":[10,164],"through":[11],"crystallographic":[12],"information":[13],"files":[14],"(CIFs).":[15],"Subtle":[16],"chemical":[17,89,110,170,182],"structural":[19],"errors":[20],"in":[21,34,224],"these":[22],"inputs":[23],"can":[24],"compromise":[25],"downstream":[26],"results":[27],"hinder":[29],"manual":[30],"inspection.":[31],"LLM":[32,82],"advances":[33],"computational":[35],"chemistry":[36],"offer":[37],"paths":[38],"beyond":[39],"predictive":[40],"screening":[41],"toward":[42],"fine-grained":[43,54],"diagnosis":[44,200],"with":[45,123],"evidence-grounded":[46,74,154],"explanations.":[47],"However,":[48],"two":[49,124],"challenges":[50],"remain:":[51],"(i)":[52],"limited":[53],"attribution:":[55],"MOF-specific":[56,219],"validators":[57],"machine-learning":[59,220],"models":[60],"scale":[61],"detection":[62],"but":[63,179],"provide":[64],"fixed":[65],"checks,":[66],"readiness":[67],"scores,":[68],"or":[69],"coarse":[70],"labels":[71],"rather":[72],"than":[73],"explanations;":[75],"(ii)":[77],"unreliable":[78,87],"CIF":[79,120],"reasoning:":[80],"direct":[81],"auditing":[83,121],"is":[84,91,201],"costly":[85],"because":[88],"evidence":[90,111,150,183],"implicit":[92],"across":[93],"atom-site":[94],"records":[95],"requires":[97],"geometric,":[98],"connectivity,":[99,140],"occupancy,":[100,141],"charge":[102,144],"calculations.":[103],"Both":[104],"stem":[105],"from":[106],"weak":[107],"coupling":[108],"between":[109],"language-model":[113],"explanation.":[114],"We":[115,187],"introduce":[116,188],"MOF-Sleuth,":[117],"a":[118,126,131,159,193,198],"reinforcement-guided":[119],"agent":[122],"modules:":[125],"deterministic":[127],"Forensic":[128],"Lab":[129,136],"Sleuth":[132,147],"reasoning":[133],"engine.":[134],"The":[135],"derives":[137],"composition,":[138],"geometry,":[139],"coordination,":[142],"evidence,":[145],"uses":[148],"this":[149],"to":[151],"produce":[152],"an":[153],"explanation,":[155],"error":[156],"types,":[157],"binary":[160],"decision.":[161],"Reward-guided":[162],"reinforcement":[163],"(RL)":[165],"turns":[166],"tool":[167],"measurements":[168],"into":[169],"explanation-level":[171],"supervision,":[172],"rewarding":[173],"not":[174],"only":[175],"the":[176],"final":[177],"answer":[178],"also":[180],"cited":[181],"evidence-supported":[185],"diagnoses.":[186],"Chemically":[189],"Grounded":[190],"Diagnosis":[191],"(Chem-GD),":[192],"metric":[194],"that":[195],"assesses":[196],"whether":[197],"correct":[199],"explained":[202],"by":[203],"factual,":[204],"relevant":[205],"CIF-derived":[206],"evidence.":[207],"Across":[208],"four":[209],"benchmarks,":[210],"MOF-Sleuth":[211],"establishes":[212],"state-of-the-art":[213],"performance":[214],"among":[215],"LLM-based":[216],"approaches":[217],"methods,":[221],"demonstrating":[222],"gains":[223],"detection,":[225],"attribution,":[226],"grounded":[228],"explanation":[229],"quality.":[230]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-24T00:00:00"}
