{"id":"https://openalex.org/W7160255964","doi":"https://doi.org/10.48550/arxiv.2605.01374","title":"MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation","display_name":"MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation","publication_year":2026,"publication_date":"2026-05-02","ids":{"openalex":"https://openalex.org/W7160255964","doi":"https://doi.org/10.48550/arxiv.2605.01374"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.01374","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01374","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.2605.01374","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126903934","display_name":"Pham Khanh Chi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chi, Pham Khanh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135398792","display_name":"Quoc Phong Dao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dao, Quoc Phong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056677095","display_name":"Thuat van Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Thuat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125251729","display_name":"Linh Ngo Van","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Van, Linh Ngo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135376143","display_name":"Trung Le","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Le, Trung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5046079137","display_name":"T. JoAnna Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Thanh Hong","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":0.642799973487854,"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":0.642799973487854,"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":0.06419999897480011,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.032600000500679016,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/noun","display_name":"Noun","score":0.5608999729156494},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5440999865531921},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5408999919891357},{"id":"https://openalex.org/keywords/verb","display_name":"Verb","score":0.4708000123500824},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.3944999873638153},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.37040001153945923},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.3691999912261963}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067999839782715},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5927000045776367},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.5608999729156494},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5440999865531921},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5408999919891357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5385000109672546},{"id":"https://openalex.org/C2776397901","wikidata":"https://www.wikidata.org/wiki/Q24905","display_name":"Verb","level":2,"score":0.4708000123500824},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3944999873638153},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.3691999912261963},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.36800000071525574},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.36320000886917114},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3465000092983246},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C88626702","wikidata":"https://www.wikidata.org/wiki/Q1128903","display_name":"Continuation","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C153962237","wikidata":"https://www.wikidata.org/wiki/Q1401131","display_name":"Noun phrase","level":3,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.01374","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01374","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.2605.01374","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01374","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8552958965301514}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Knowledge":[0],"distillation":[1],"is":[2,35,131,145],"a":[3,31,62,77,113,166],"key":[4],"technique":[5],"for":[6],"compressing":[7],"large":[8],"language":[9],"models":[10],"(LLMs),":[11],"but":[12],"most":[13],"existing":[14],"methods":[15],"align":[16,173],"representations":[17,26,69,138],"at":[18,84],"fixed":[19],"layers":[20,81,94],"or":[21],"token-level":[22],"outputs,":[23],"ignoring":[24],"how":[25],"evolve":[27],"across":[28],"depth.":[29],"As":[30],"result,":[32],"the":[33,41,85,120,157,191],"student":[34,68],"only":[36],"weakly":[37],"guided":[38],"to":[39,88,104,171],"capture":[40,105],"teacher's":[42],"internal":[43],"relational":[44],"structure":[45],"during":[46],"distillation,":[47],"which":[48,152],"limits":[49],"knowledge":[50],"transfer.":[51],"To":[52],"address":[53],"this":[54,110],"limitation,":[55],"we":[56],"propose":[57],"Multi-Granular":[58],"Trajectory":[59],"Alignment":[60,116,169],"(MTA),":[61],"framework":[63],"that":[64,118,136,179],"aligns":[65],"teacher":[66],"and":[67,101,144],"along":[70],"their":[71],"layer-wise":[72],"transformation":[73],"trajectory.":[74],"MTA":[75,180],"adopts":[76],"layer-adaptive":[78],"strategy:":[79],"lower":[80],"are":[82],"aligned":[83],"word":[86],"level":[87],"preserve":[89],"lexical":[90,161],"information,":[91],"while":[92],"higher":[93],"operate":[95],"on":[96,185],"phrase-level":[97],"spans":[98],"(e.g.,":[99],"noun":[100],"verb":[102],"phrases)":[103],"compositional":[106],"semantics.":[107],"We":[108,163],"instantiate":[109],"idea":[111],"through":[112,156],"Dynamic":[114],"Structural":[115],"loss":[117,170],"matches":[119],"relative":[121],"geometry":[122],"among":[123],"semantic":[124],"units":[125],"within":[126],"each":[127,194],"layer.":[128],"This":[129],"design":[130],"motivated":[132],"by":[133],"empirical":[134],"findings":[135],"Transformer":[137],"become":[139],"increasingly":[140],"abstract":[141],"with":[142,148,188],"depth,":[143],"also":[146],"consistent":[147],"linguistic":[149],"views":[150],"in":[151],"higher-level":[153],"meaning":[154],"emerges":[155],"composition":[158],"of":[159,193],"lower-level":[160],"units.":[162],"further":[164],"incorporate":[165],"Hidden":[167],"Representation":[168],"directly":[172],"selected":[174],"teacher-student":[175],"layers.":[176],"Experiments":[177],"show":[178],"consistently":[181],"outperforms":[182],"state-of-the-art":[183],"baselines":[184],"standard":[186],"benchmarks,":[187],"ablations":[189],"confirming":[190],"contribution":[192],"component.":[195]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-06T00:00:00"}