{"id":"https://openalex.org/W7134854901","doi":"https://doi.org/10.48550/arxiv.2603.06981","title":"Diffusion Controller: Framework, Algorithms and Parameterization","display_name":"Diffusion Controller: Framework, Algorithms and Parameterization","publication_year":2026,"publication_date":"2026-03-07","ids":{"openalex":"https://openalex.org/W7134854901","doi":"https://doi.org/10.48550/arxiv.2603.06981"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.06981","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128671352","display_name":"Tong Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yang, Tong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128661500","display_name":"Moonkyung Ryu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ryu, Moonkyung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128667431","display_name":"Chih-Wei Hsu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hsu, Chih-Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049376842","display_name":"Guy Tennenholtz","orcid":"https://orcid.org/0000-0002-2727-2351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tennenholtz, Guy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128664664","display_name":"Yuejie Chi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chi, Yuejie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128668530","display_name":"Craig Boutilier","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boutilier, Craig","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128669847","display_name":"Bo Dai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Bo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5128671352"],"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.48750001192092896,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.48750001192092896,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.06480000168085098,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.06019999831914902,"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/heuristics","display_name":"Heuristics","score":0.6644999980926514},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5527999997138977},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.506600022315979},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.46560001373291016},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.44279998540878296},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.43799999356269836},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.3977999985218048},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.37929999828338623}],"concepts":[{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.6644999980926514},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5527999997138977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5476999878883362},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5235999822616577},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.506600022315979},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.46560001373291016},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.44850000739097595},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.44279998540878296},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.43799999356269836},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3977999985218048},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37130001187324524},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3384999930858612},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3301999866962433},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C170131372","wikidata":"https://www.wikidata.org/wiki/Q7617811","display_name":"Stochastic control","level":3,"score":0.3176000118255615},{"id":"https://openalex.org/C75438885","wikidata":"https://www.wikidata.org/wiki/Q3403615","display_name":"Large deviations theory","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.27730000019073486},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2732999920845032},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2565999925136566}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.06981","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.06981","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.06981","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.06981","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"Controllable":[0],"diffusion":[1,31,75],"generation":[2],"often":[3],"relies":[4],"on":[5,129,143],"various":[6],"heuristics":[7],"that":[8,28],"are":[9],"seemingly":[10],"disconnected":[11],"without":[12],"a":[13,24,82,87,93,106,115,120,125,139],"unified":[14,25],"understanding.":[15],"We":[16],"bridge":[17],"this":[18,45],"gap":[19],"with":[20,92,138],"Diffusion":[21,145],"Controller":[22],"(DiffCon),":[23],"control-theoretic":[26],"view":[27],"casts":[29],"reverse":[30],"sampling":[32],"as":[33],"state-only":[34],"stochastic":[35],"control":[36,47,122],"within":[37],"(generalized)":[38],"linearly-solvable":[39],"Markov":[40],"Decision":[41],"Processes":[42],"(LS-MDPs).":[43],"Under":[44],"framework,":[46],"acts":[48],"by":[49],"reweighting":[50],"the":[51,64,97,110,168],"pretrained":[52,117],"reverse-time":[53],"transition":[54],"kernels,":[55],"balancing":[56],"terminal":[57],"objectives":[58],"against":[59],"an":[60],"$f$-divergence":[61],"cost.":[62],"From":[63],"resulting":[65],"optimality":[66],"conditions,":[67],"we":[68],"derive":[69],"practical":[70],"reinforcement":[71],"learning":[72],"methods":[73],"for":[74],"fine-tuning:":[76],"(i)":[77],"f-divergence-regularized":[78],"policy-gradient":[79],"updates,":[80],"including":[81],"PPO-style":[83],"rule,":[84],"and":[85,149,159,166],"(ii)":[86],"regularizer-determined":[88],"reward-weighted":[89],"regression":[90],"objective":[91],"minimizer-preservation":[94],"guarantee":[95],"under":[96],"Kullback-Leibler":[98],"(KL)":[99],"divergence.":[100],"The":[101],"LS-MDP":[102],"framework":[103],"further":[104],"implies":[105],"principled":[107],"model":[108],"form:":[109],"optimal":[111],"score":[112],"decomposes":[113],"into":[114],"fixed":[116],"baseline":[118],"plus":[119],"lightweight":[121],"correction,":[123],"motivating":[124],"side-network":[126],"parameterization":[127],"conditioned":[128],"exposed":[130],"intermediate":[131],"denoising":[132],"outputs,":[133],"enabling":[134],"effective":[135],"gray-box":[136,164],"adaptation":[137],"frozen":[140],"backbone.":[141],"Experiments":[142],"Stable":[144],"v1.4":[146],"across":[147],"supervised":[148],"reward-driven":[150],"finetuning":[151],"show":[152],"consistent":[153],"gains":[154],"in":[155],"preference-alignment":[156],"win":[157],"rates":[158],"improved":[160],"quality-efficiency":[161],"trade-offs":[162],"versus":[163],"baselines":[165],"even":[167],"parameter-efficient":[169],"white-box":[170],"adapter":[171],"LoRA.":[172]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-03-11T00:00:00"}