{"id":"https://openalex.org/W7160906719","doi":"https://doi.org/10.48550/arxiv.2605.09608","title":"Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training","display_name":"Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training","publication_year":2026,"publication_date":"2026-05-10","ids":{"openalex":"https://openalex.org/W7160906719","doi":"https://doi.org/10.48550/arxiv.2605.09608"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.09608","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09608","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.2605.09608","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135947218","display_name":"Yuanyi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuanyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135963112","display_name":"Yifan Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135961740","display_name":"Su Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Su","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135946114","display_name":"Yanggan Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Yanggan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043684987","display_name":"Pengkai Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Pengkai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135990912","display_name":"Wenjun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wenjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135948942","display_name":"Zhaoyi Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Zhaoyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135968152","display_name":"Congkai Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Congkai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135936261","display_name":"Jianmin Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jianmin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135974136","display_name":"Jialun Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Jialun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034057959","display_name":"Shing-Chi Cheung","orcid":"https://orcid.org/0000-0002-3508-7172"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheung, Shing-Chi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135976231","display_name":"Hongxia Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Hongxia","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.42419999837875366,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.42419999837875366,"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":0.15109999477863312,"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/T10028","display_name":"Topic Modeling","score":0.14000000059604645,"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":0.7610999941825867},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5113000273704529},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.46480000019073486},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4422000050544739},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.40389999747276306},{"id":"https://openalex.org/keywords/convex-geometry","display_name":"Convex geometry","score":0.3652999997138977},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.3305000066757202}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.7610999941825867},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5515000224113464},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5113000273704529},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.46480000019073486},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4422000050544739},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.40389999747276306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3950999975204468},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38119998574256897},{"id":"https://openalex.org/C110202963","wikidata":"https://www.wikidata.org/wiki/Q1783542","display_name":"Convex geometry","level":5,"score":0.3652999997138977},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32739999890327454},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3188000023365021},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.311599999666214},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30480000376701355},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.26669999957084656},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.25929999351501465}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.09608","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09608","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.2605.09608","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09608","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Continual":[0],"post-training":[1,64,98],"aims":[2],"to":[3,84,196],"extend":[4],"large":[5],"language":[6],"models":[7],"(LLMs)":[8],"with":[9,137,152],"new":[10,51],"knowledge,":[11],"skills,":[12],"and":[13,25,104,160,192,205,215,233],"behaviors,":[14],"yet":[15],"it":[16,127],"remains":[17],"unclear":[18],"when":[19,26,49,129,148,162],"sequential":[20,36],"updates":[21,52,146],"enable":[22],"capability":[23],"transfer":[24,76,147],"they":[27,149],"cause":[28],"catastrophic":[29],"forgetting.":[30],"Existing":[31],"methods":[32],"mitigate":[33],"forgetting":[34,118,232],"through":[35,65,92],"fine-tuning,":[37],"replay,":[38],"regularization,":[39],"or":[40,55,77],"model":[41,143,154],"merging,":[42],"but":[43],"offer":[44],"limited":[45],"criteria":[46],"for":[47,231,238],"determining":[48],"incorporating":[50],"is":[53,116],"beneficial":[54],"harmful.":[56],"In":[57],"this":[58,170],"work,":[59],"we":[60,95,172],"study":[61,105],"LLM":[62,239],"continual":[63,240],"three":[66],"questions:":[67],"What":[68],"drives":[69],"forgetting?":[70],"When":[71],"do":[72],"sequentially":[73],"acquired":[74],"capabilities":[75],"interfere?":[78],"How":[79],"can":[80,119],"compatibility":[81],"be":[82,120],"used":[83],"control":[85,236],"update":[86,103],"integration?":[87],"We":[88],"address":[89],"these":[90],"questions":[91],"task":[93,99],"geometry:":[94],"represent":[96],"each":[97],"by":[100,110,134,157,169],"its":[101],"parameter":[102],"the":[106,111,130,138,141,153],"covariance":[107,131],"geometry":[108,139,164,194,224],"induced":[109,133],"update.":[112],"Our":[113],"central":[114],"finding":[115],"that:":[117],"considered":[121],"as":[122,226],"a":[123,178,184,234],"state-relative":[124,163],"update-integration":[125,180],"failure,":[126],"arises":[128],"geometries":[132],"tasks":[135],"misalign":[136],"of":[140],"evolving":[142],"state.":[144],"Sequential":[145],"remain":[150],"compatible":[151],"state":[155],"shaped":[156],"previous":[158],"updates,":[159],"interfere":[161],"conflict":[165,195,225],"becomes":[166],"high.":[167],"Motivated":[168],"finding,":[171],"propose":[173],"Geometry-Conflict":[174],"Wasserstein":[175,186,190],"Merging":[176],"(GCWM),":[177],"data-free":[179,211],"method":[181],"that":[182],"constructs":[183],"shared":[185],"metric":[187],"via":[188],"Gaussian":[189],"barycenters":[191],"uses":[193],"gate":[197],"geometry-aware":[198],"correction.":[199],"Across":[200],"Qwen3":[201],"0.6B--14B":[202],"on":[203],"domain-continual":[204],"capability-continual":[206],"settings,":[207],"GCWM":[208],"consistently":[209],"outperforms":[210],"baselines,":[212],"improving":[213],"retention":[214],"final":[216],"performance":[217],"without":[218],"replay":[219],"data.":[220],"These":[221],"results":[222],"identify":[223],"both":[227],"an":[228],"explanatory":[229],"signal":[230,237],"practical":[235],"post-training.":[241]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-13T00:00:00"}
