{"id":"https://openalex.org/W7140223307","doi":"https://doi.org/10.48550/arxiv.2603.20210","title":"CRoCoDiL: Continuous and Robust Conditioned Diffusion for Language","display_name":"CRoCoDiL: Continuous and Robust Conditioned Diffusion for Language","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7140223307","doi":"https://doi.org/10.48550/arxiv.2603.20210"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.20210","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20210","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.20210","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Uziel, Roy","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Uziel, Roy","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Belhasin, Omer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Belhasin, Omer","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Levy, Itay","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Levy, Itay","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Bercovich, Akhiad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bercovich, Akhiad","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"El-Yaniv, Ran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"El-Yaniv, Ran","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zilberstein, Ran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zilberstein, Ran","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Elad, Michael","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elad, Michael","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"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":0.4602000117301941,"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":0.4602000117301941,"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":0.2953999936580658,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.045899998396635056,"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/security-token","display_name":"Security token","score":0.5684999823570251},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5302000045776367},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.4277999997138977},{"id":"https://openalex.org/keywords/subnetwork","display_name":"Subnetwork","score":0.42640000581741333},{"id":"https://openalex.org/keywords/decodes","display_name":"Decodes","score":0.4212999939918518},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.41179999709129333},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.3889999985694885},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.3824000060558319},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.37560001015663147}],"concepts":[{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5684999823570251},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5648999810218811},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5302000045776367},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5254999995231628},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.42640000581741333},{"id":"https://openalex.org/C2778858076","wikidata":"https://www.wikidata.org/wiki/Q5249539","display_name":"Decodes","level":3,"score":0.4212999939918518},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.41179999709129333},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3889999985694885},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3824000060558319},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.37529999017715454},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3562999963760376},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33880001306533813},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.32690000534057617},{"id":"https://openalex.org/C68710425","wikidata":"https://www.wikidata.org/wiki/Q5275442","display_name":"Diffusion process","level":3,"score":0.325300008058548},{"id":"https://openalex.org/C62799726","wikidata":"https://www.wikidata.org/wiki/Q190056","display_name":"Hilbert space","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2639999985694885},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.20210","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20210","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.20210","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20210","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":"article"},"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":{"Masked":[0],"Diffusion":[1,51],"Models":[2],"(MDMs)":[3],"provide":[4],"an":[5,61,87,122,158],"efficient":[6],"non-causal":[7],"alternative":[8],"to":[9,22,74,119],"autoregressive":[10],"generation":[11,148],"but":[12],"often":[13],"struggle":[14],"with":[15],"token":[16],"dependencies":[17],"and":[18,48,115,124,150],"semantic":[19,42],"incoherence":[20],"due":[21],"their":[23],"reliance":[24],"on":[25,91],"discrete":[26,136],"marginal":[27],"distributions.":[28],"We":[29,44],"address":[30],"these":[31,118],"limitations":[32],"by":[33,86],"shifting":[34],"the":[35,65,75,92,135],"diffusion":[36],"process":[37],"into":[38],"a":[39,54,78,104,127],"continuous":[40,69,113],"sentence-level":[41],"space.":[43],"propose":[45],"CRoCoDiL":[46],"(Continuous":[47],"Robust":[49],"Conditioned":[50],"for":[52],"Language),":[53],"unified":[55],"fine-tuning":[56],"approach":[57,106],"that":[58,107,130,143],"jointly":[59],"trains":[60],"encoder-demasker":[62],"architecture,":[63],"grounding":[64],"MDM":[66,88],"demasking":[67],"in":[68,81,112,157],"latent":[70,110,132],"representations.":[71],"This":[72],"leads":[73],"formation":[76],"of":[77],"novel":[79],"autoencoder":[80],"which":[82],"decoding":[83],"is":[84],"obtained":[85],"algorithm.":[89],"Relying":[90],"same":[93],"framework,":[94],"we":[95],"introduce":[96],"two":[97],"unconditional":[98,159],"text":[99],"synthesis":[100],"algorithms:":[101],"Continuous-Then-Discrete":[102],"(ConThenDisc),":[103],"hybrid-diffusion":[105],"first":[108],"generates":[109],"representations":[111,133],"space":[114],"then":[116],"decodes":[117],"tokens":[120],"via":[121],"MDM,":[123],"Continuous-Within-Discrete":[125],"(ConWithinDisc),":[126],"multi-diffusion":[128],"strategy":[129],"refines":[131],"throughout":[134],"sampling":[137,155],"process.":[138],"Experiments":[139],"using":[140],"LLaDA":[141],"show":[142],"our":[144],"methods":[145],"achieve":[146],"superior":[147],"quality":[149],"more":[151],"than":[152],"10x":[153],"faster":[154],"speeds":[156],"setting.":[160]},"counts_by_year":[],"updated_date":"2026-04-21T06:05:55.347736","created_date":"2026-03-25T00:00:00"}
