{"id":"https://openalex.org/W7163326836","doi":"https://doi.org/10.48550/arxiv.2606.03087","title":"Learning to Solve, Forgetting to Retain: Correct-Set Turnover in RLVR","display_name":"Learning to Solve, Forgetting to Retain: Correct-Set Turnover in RLVR","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163326836","doi":"https://doi.org/10.48550/arxiv.2606.03087"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.03087","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03087","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":"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.2606.03087","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137765651","display_name":"Chuanyu Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Chuanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137789808","display_name":"Chenxu Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Chenxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137730978","display_name":"Qingyi Si","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Si, Qingyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137781659","display_name":"Naibin Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Naibin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137760273","display_name":"Peng Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137770767","display_name":"Zheng Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Zheng","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.21889999508857727,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.21889999508857727,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.17949999868869781,"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/T10028","display_name":"Topic Modeling","score":0.11819999665021896,"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/forgetting","display_name":"Forgetting","score":0.5440000295639038},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5335000157356262},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4887000024318695},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4672999978065491},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.39239999651908875},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.3758000135421753},{"id":"https://openalex.org/keywords/unobservable","display_name":"Unobservable","score":0.3621000051498413}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6588000059127808},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5440000295639038},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5335000157356262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49059998989105225},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4887000024318695},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4672999978065491},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.428600013256073},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.39239999651908875},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.3758000135421753},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3723999857902527},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.3621000051498413},{"id":"https://openalex.org/C132758656","wikidata":"https://www.wikidata.org/wiki/Q5307365","display_name":"Dreyfus model of skill acquisition","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C50335755","wikidata":"https://www.wikidata.org/wiki/Q483247","display_name":"Phenomenon","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C2780154230","wikidata":"https://www.wikidata.org/wiki/Q513420","display_name":"Undo","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.25440001487731934},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.03087","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03087","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":"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.2606.03087","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03087","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":"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reinforcement":[0],"learning":[1],"with":[2,79,139],"verifiable":[3],"rewards":[4],"(RLVR)":[5],"improves":[6,145],"the":[7,39,48,67,70,113],"ability":[8],"of":[9,42,72,115],"large":[10],"language":[11],"model,":[12],"yet":[13],"headline":[14],"accuracy":[15],"gains":[16],"often":[17],"conceal":[18],"a":[19,74,83,99],"hidden":[20],"cost:":[21],"previously":[22],"solved":[23],"problems":[24],"quietly":[25],"become":[26],"unsolvable":[27],"as":[28,35],"training":[29],"proceeds.":[30],"We":[31,62],"frame":[32],"this":[33,52],"phenomenon":[34],"\\emph{correct-set":[36],"turnover},":[37],"representing":[38],"coupled":[40],"dynamics":[41],"solution":[43],"acquisition":[44],"and":[45,64,107,136,141,150,158],"regression":[46],"over":[47,147],"mastered":[49,105],"set.":[50],"Under":[51],"view,":[53],"retention":[54],"becomes":[55],"an":[56],"explicit":[57],"optimization":[58],"target":[59],"alongside":[60],"acquisition.":[61],"analytically":[63],"empirically":[65],"establish":[66],"\\emph{repair-window":[68],"principle}:":[69],"cost":[71],"restoring":[73],"regressed":[75],"prompt":[76],"grows":[77],"sharply":[78],"review":[80,101],"delay,":[81],"defining":[82],"low-cost":[84],"window":[85],"that":[86,103],"standard":[87],"RLVR":[88],"pipelines":[89],"fail":[90],"to":[91,111],"exploit.":[92],"To":[93],"address":[94],"this,":[95],"we":[96],"propose":[97],"\\textbf{\\method{}},":[98],"retention-aware":[100],"mechanism":[102],"tracks":[104],"prompts":[106],"periodically":[108],"reintroduces":[109],"them":[110],"\\textbf{remind}":[112],"model":[114],"previous":[116],"solutions.":[117],"By":[118],"utilizing":[119],"pre-rollout":[120],"batch":[121],"replacement,":[122],"\\method{}":[123,143],"incurs":[124],"zero":[125],"additional":[126],"rollout":[127],"overhead.":[128],"Evaluated":[129],"across":[130,156],"20":[131],"benchmarks":[132],"spanning":[133],"image-text,":[134],"video,":[135],"text-only":[137],"tasks":[138],"Qwen3-VL":[140],"Qwen2.5-Math,":[142],"consistently":[144],"performance":[146],"GRPO,":[148],"DAPO,":[149],"replay":[151],"baselines,":[152],"demonstrating":[153],"robust":[154],"generalizability":[155],"modalities":[157],"algorithms.":[159]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-04T00:00:00"}
