{"id":"https://openalex.org/W7161675460","doi":"https://doi.org/10.48550/arxiv.2605.17026","title":"Why Do Reasoning Models Lose Coverage? The Role of Data and Forks in the Road","display_name":"Why Do Reasoning Models Lose Coverage? The Role of Data and Forks in the Road","publication_year":2026,"publication_date":"2026-05-16","ids":{"openalex":"https://openalex.org/W7161675460","doi":"https://doi.org/10.48550/arxiv.2605.17026"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17026","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17026","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.17026","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136498258","display_name":"Ngoc-Hieu Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Ngoc-Hieu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136496065","display_name":"Parshin Shojaee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shojaee, Parshin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104222816","display_name":"Phuc Minh Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Phuc Minh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136467911","display_name":"Nan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Nan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136476242","display_name":"Chandan K Reddy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reddy, Chandan K","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080642445","display_name":"Khoa D. Doan","orcid":"https://orcid.org/0000-0002-1610-8206"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Doan, Khoa D","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136502207","display_name":"Rui Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Rui","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":0.18629999458789825,"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":0.18629999458789825,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.15060000121593475,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1444000005722046,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/shrinkage","display_name":"Shrinkage","score":0.7148000001907349},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44839999079704285},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.448199987411499},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.36340001225471497},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.3531999886035919},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.34779998660087585},{"id":"https://openalex.org/keywords/sequential-analysis","display_name":"Sequential analysis","score":0.2912999987602234}],"concepts":[{"id":"https://openalex.org/C180145272","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage","level":2,"score":0.7148000001907349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6384000182151794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4724000096321106},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44839999079704285},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.448199987411499},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36309999227523804},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.34779998660087585},{"id":"https://openalex.org/C80478641","wikidata":"https://www.wikidata.org/wiki/Q195771","display_name":"Sequential analysis","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C107524782","wikidata":"https://www.wikidata.org/wiki/Q40164","display_name":"Lever","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17026","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17026","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.17026","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17026","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":"Preprint"},"sustainable_development_goals":[{"score":0.583040177822113,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"progress":[1],"in":[2,84,115,125,143,183],"large":[3],"language":[4],"models":[5,185],"has":[6],"led":[7],"to":[8,48,79],"the":[9,49,57,74,85,131,138,144],"emergence":[10],"of":[11,73,140,163,181],"reasoning":[12,58,96,119,184],"models,":[13],"which":[14],"have":[15,35],"shown":[16],"strong":[17],"performance":[18],"on":[19],"complex":[20],"tasks":[21],"through":[22,158],"specialized":[23],"fine-tuning":[24,75],"procedures.":[25],"While":[26],"these":[27,126],"methods":[28],"reliably":[29],"improve":[30],"pass@1":[31],"accuracy,":[32],"prior":[33],"works":[34],"observed":[36],"that":[37,66,107,130,150],"they":[38],"show":[39],"a":[40,166,178],"coverage":[41],"shrinkage":[42,59,132,152,182],"behavior,":[43],"where":[44,88],"pass@k":[45],"degrades":[46],"relative":[47],"base":[50],"model.":[51],"In":[52],"this":[53,67,100,151],"paper,":[54],"we":[55,102,128],"investigate":[56],"arise":[60],"under":[61],"SFT-based":[62],"post-training.":[63],"We":[64,147],"hypothesize":[65],"behavior":[68,153],"is":[69,134],"driven":[70],"by":[71],"properties":[72],"data,":[76],"specifically":[77],"related":[78],"decision":[80],"points":[81],"or":[82],"\"forks":[83],"road\"":[86],"scenarios":[87,142],"model":[89],"faces":[90],"indecipherable":[91,113],"patterns":[92],"with":[93,137],"multiple":[94],"valid":[95],"paths.":[97],"To":[98],"test":[99],"hypothesis,":[101],"design":[103,162],"controlled":[104],"case":[105],"studies":[106],"simulate":[108],"such":[109],"decision-point":[110,141],"settings,":[111,127],"spanning":[112],"nodes":[114],"graph":[116],"branching,":[117],"and":[118,165,186],"modes.":[120],"By":[121],"tracking":[122],"post-training":[123],"dynamics":[124],"find":[129],"phenomenon":[133],"tightly":[135],"correlated":[136],"prevalence":[139],"training":[145],"data.":[146],"also":[148],"demonstrate":[149],"can":[154],"be":[155],"partially":[156],"mitigated":[157],"targeted":[159],"data":[160],"synthesis":[161],"decision-points,":[164],"more":[167],"systematic":[168],"diversity-encouraging":[169],"decoding":[170],"mechanism.":[171],"Our":[172],"findings":[173],"identify":[174],"data-centric":[175],"factors":[176],"as":[177,190],"key":[179],"driver":[180],"highlight":[187],"diversity-aware":[188],"designs":[189],"an":[191],"effective":[192],"lever":[193],"for":[194],"controlling":[195],"it.":[196]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-20T00:00:00"}