{"id":"https://openalex.org/W7163217044","doi":"https://doi.org/10.48550/arxiv.2606.00437","title":"EST-PRM: Stress-Testing Process Reward Models Before They Become Load-Bearing","display_name":"EST-PRM: Stress-Testing Process Reward Models Before They Become Load-Bearing","publication_year":2026,"publication_date":"2026-05-30","ids":{"openalex":"https://openalex.org/W7163217044","doi":"https://doi.org/10.48550/arxiv.2606.00437"},"language":"en","primary_location":{"id":"pmh:oai:dr.lib.iastate.edu:20.500.12876/106867","is_oa":false,"landing_page_url":"https://dr.lib.iastate.edu/handle/20.500.12876/106867","pdf_url":null,"source":{"id":"https://openalex.org/S4377196104","display_name":"Iowa State University Digital Repository (Iowa State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173911158","host_organization_name":"Iowa State University","host_organization_lineage":["https://openalex.org/I173911158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://doi.org/10.48550/arXiv.2606.00437","raw_type":"preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.00437","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137705571","display_name":"Ibne Farabi Shihab","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shihab, Ibne Farabi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122389296","display_name":"Fariya Afrin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Afrin, Fariya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119832027","display_name":"Sanjeda Akter","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akter, Sanjeda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137626995","display_name":"Anuj Sharma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sharma, Anuj","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":0.2289000004529953,"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":0.2289000004529953,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.09109999984502792,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.07930000126361847,"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/correctness","display_name":"Correctness","score":0.9480000138282776},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6136000156402588},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5127000212669373},{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.4359000027179718},{"id":"https://openalex.org/keywords/inflation","display_name":"Inflation (cosmology)","score":0.3991999924182892},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.37950000166893005}],"concepts":[{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.9480000138282776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6674000024795532},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6136000156402588},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5127000212669373},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40849998593330383},{"id":"https://openalex.org/C200941418","wikidata":"https://www.wikidata.org/wiki/Q273508","display_name":"Inflation (cosmology)","level":2,"score":0.3991999924182892},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3864000141620636},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31450000405311584},{"id":"https://openalex.org/C2779714256","wikidata":"https://www.wikidata.org/wiki/Q25305062","display_name":"Multiple Models","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2676999866962433},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:dr.lib.iastate.edu:20.500.12876/106867","is_oa":false,"landing_page_url":"https://dr.lib.iastate.edu/handle/20.500.12876/106867","pdf_url":null,"source":{"id":"https://openalex.org/S4377196104","display_name":"Iowa State University Digital Repository (Iowa State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173911158","host_organization_name":"Iowa State University","host_organization_lineage":["https://openalex.org/I173911158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://doi.org/10.48550/arXiv.2606.00437","raw_type":"preprint"},{"id":"doi:10.48550/arxiv.2606.00437","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00437","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.2606.00437","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00437","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Process":[0],"reward":[1,97,170],"models":[2,106],"(PRMs)":[3],"are":[4,18,107,180],"widely":[5],"used":[6],"in":[7,122,174],"language-model":[8],"training":[9],"with":[10,135],"dense":[11,72],"step-level":[12],"supervision.":[13],"They":[14],"assume":[15],"PRM":[16,49],"scores":[17,50],"stable":[19],"proxies":[20],"for":[21,71],"step":[22,80,84,157],"correctness":[23,53,102,175],"under":[24],"label-preserving":[25],"transformations.":[26],"These":[27],"transformations":[28,45],"change":[29,47],"reasoning":[30,111],"structure":[31],"but":[32],"preserve":[33],"final":[34],"answers.":[35],"We":[36],"argue":[37],"this":[38,63],"assumption":[39],"is":[40,93,153],"not":[41],"well":[42],"validated.":[43],"Such":[44],"can":[46],"how":[48],"relate":[51],"to":[52,56,132],"signals,":[54],"leading":[55],"different":[57],"failure":[58],"modes":[59],"across":[60,125],"models.To":[61],"address":[62],"gap,":[64],"we":[65],"introduce":[66],"\\textbf{EST-PRM},":[67],"a":[68,136,145,160],"stress-testing":[69],"framework":[70],"process":[73],"rewards.":[74],"It":[75],"applies":[76],"three":[77],"transformations:":[78],"(1)":[79],"inflation,":[81,158],"(2)":[82],"dependency-aware":[83],"reordering,":[85],"and":[86,116,144,187],"(3)":[87],"confidence":[88],"markers.":[89],"A":[90],"vulnerability":[91,123],"decomposition":[92],"defined":[94],"that":[95],"separates":[96],"inflation":[98,150,164],"from":[99,113],"loss":[100],"of":[101,140],"sensitivity.":[103],"Five":[104],"PRM-style":[105],"evaluated":[108],"on":[109],"4,687":[110],"chains":[112],"MATH-500,":[114],"GSM8K,":[115],"PRMBench.The":[117],"results":[118],"indicate":[119],"clear":[120],"differences":[121],"patterns":[124],"models.":[126],"Math-Shepherd":[127],"shows":[128],"the":[129],"strongest":[130],"sensitivity":[131],"position":[133],"perturbations,":[134],"Pearson":[137],"correlation":[138],"drop":[139],"$0.152":[141],"\\pm":[142,147,162],"0.038$":[143],"$32.8":[146],"4.9\\%$":[148],"score":[149],"rate.":[151,165],"Qwen2.5-Math-PRM":[152],"most":[154],"affected":[155],"by":[156],"reaching":[159],"$47.6":[161],"4.3\\%$":[163],"Confidence-based":[166],"perturbations":[167],"also":[168],"distort":[169],"calibration,":[171],"revealing":[172],"inconsistencies":[173],"estimation.":[176],"Three":[177],"mitigation":[178],"strategies":[179],"evaluated,":[181],"highlighting":[182],"trade-offs":[183],"between":[184],"robustness":[185],"coverage":[186],"false-positive":[188],"rates.":[189]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-03T00:00:00"}