{"id":"https://openalex.org/W7163081565","doi":"https://doi.org/10.48550/arxiv.2605.30904","title":"MergeTok: Unified Continuous and Discrete Visual Tokenization via Token Merging","display_name":"MergeTok: Unified Continuous and Discrete Visual Tokenization via Token Merging","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163081565","doi":"https://doi.org/10.48550/arxiv.2605.30904"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30904","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30904","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.2605.30904","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066093415","display_name":"Luyuan Zhang","orcid":"https://orcid.org/0000-0001-9972-0742"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Luyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137527972","display_name":"Siyuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Siyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137555960","display_name":"Zedong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zedong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137559104","display_name":"Qingsong Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Qingsong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137566797","display_name":"Cheng Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043482575","display_name":"Anna Wang","orcid":"https://orcid.org/0000-0001-9905-767X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Anna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137580780","display_name":"Yanhao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yanhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137582578","display_name":"Chen Chen","orcid":"https://orcid.org/0000-0002-6065-8889"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137512251","display_name":"Haonan Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Haonan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137571821","display_name":"Haoqian Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Haoqian","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9397000074386597,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9397000074386597,"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":0.011099999770522118,"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/T11448","display_name":"Face recognition and analysis","score":0.007400000002235174,"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/codebook","display_name":"Codebook","score":0.7702000141143799},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.7621999979019165},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4828000068664551},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.47760000824928284},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3856000006198883},{"id":"https://openalex.org/keywords/lexical-analysis","display_name":"Lexical analysis","score":0.3653999865055084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3352000117301941},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3269999921321869}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7932000160217285},{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.7702000141143799},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.7621999979019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5509999990463257},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4828000068664551},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.47760000824928284},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3856000006198883},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37220001220703125},{"id":"https://openalex.org/C176982825","wikidata":"https://www.wikidata.org/wiki/Q835922","display_name":"Lexical analysis","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3463999927043915},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C202708506","wikidata":"https://www.wikidata.org/wiki/Q7449050","display_name":"Semantic compression","level":5,"score":0.303600013256073},{"id":"https://openalex.org/C2986420190","wikidata":"https://www.wikidata.org/wiki/Q39045939","display_name":"Semantic space","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27970001101493835},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2671999931335449},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.26499998569488525},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C2781142347","wikidata":"https://www.wikidata.org/wiki/Q1366592","display_name":"Hilbert curve","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30904","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30904","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.2605.30904","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30904","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Most":[0],"visual":[1,171],"tokenizers":[2,66,172],"for":[3,29],"image":[4],"generation":[5,38,133],"are":[6,26],"bifurcated":[7],"into":[8],"two":[9],"families":[10],"with":[11,41,137,157,173],"complementary":[12],"limitations:":[13],"continuous":[14,61],"VAEs":[15],"offer":[16],"high-fidelity":[17],"reconstruction":[18,131],"but":[19],"suffer":[20],"from":[21],"dense,":[22],"entangled":[23],"latents":[24],"that":[25,58,90,124,165],"poorly":[27],"suited":[28],"semantic":[30,77,99,175],"control,":[31],"whereas":[32],"discrete":[33,64],"VQ-based":[34],"models":[35,146],"enable":[36],"autoregressive":[37,159],"yet":[39],"struggle":[40],"gradient":[42],"sparsity,":[43],"unstable":[44],"training,":[45],"and":[46,63,121,132,144,160,177],"codebook":[47],"collapse.":[48],"In":[49],"this":[50],"work,":[51],"we":[52],"introduce":[53],"MergeTok,":[54],"a":[55,68,76,87,166],"unified":[56],"tokenizer":[57],"jointly":[59],"optimizes":[60],"(VAE)":[62],"(VQ)":[65],"within":[67],"encoder-decoder":[69],"architecture,":[70],"leveraging":[71],"token":[72,149,154],"merging":[73],"techniques":[74],"as":[75],"bridge.":[78],"By":[79],"clustering":[80],"similar":[81],"tokens":[82],"during":[83],"encoding,":[84],"MergeTok":[85,128],"establishes":[86],"structural":[88],"prior":[89],"provides":[91],"dual":[92],"supervision":[93],"signals:":[94],"(i)":[95],"it":[96,114],"imposes":[97],"merged-token":[98],"alignment":[100],"in":[101],"the":[102],"VAE":[103,143],"branch,":[104],"regularizing":[105],"its":[106],"latent":[107],"space":[108],"toward":[109],"disentangled,":[110],"semantic-aware":[111],"representations;":[112],"(ii)":[113],"derives":[115],"group-wise":[116],"constraints,":[117],"promoting":[118],"intra-group":[119],"diversity":[120],"inter-group":[122],"exclusivity":[123],"stabilize":[125],"VQ":[126,145],"training.":[127],"shows":[129,164],"competitive":[130],"performance":[134],"on":[135],"ImageNet-256,":[136],"substantially":[138],"lower":[139],"rFID":[140],"than":[141],"strong":[142],"under":[147],"matched":[148],"budgets,":[150],"while":[151],"producing":[152],"semantically-organized":[153],"representations":[155],"compatible":[156],"both":[158],"diffusion":[161],"generators.":[162],"This":[163],"single":[167],"architecture":[168],"can":[169],"endow":[170],"robust":[174],"organization":[176],"generator-friendly":[178],"discreteness.":[179]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-02T00:00:00"}
