{"id":"https://openalex.org/W7156758487","doi":"https://doi.org/10.48550/arxiv.2604.23557","title":"DLM: Unified Decision Language Models for Offline Multi-Agent Sequential Decision Making","display_name":"DLM: Unified Decision Language Models for Offline Multi-Agent Sequential Decision Making","publication_year":2026,"publication_date":"2026-04-26","ids":{"openalex":"https://openalex.org/W7156758487","doi":"https://doi.org/10.48550/arxiv.2604.23557"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.23557","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23557","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":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.2604.23557","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109676488","display_name":"Zhuohui Zhang","orcid":"https://orcid.org/0009-0000-5040-9654"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhuohui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134756001","display_name":"Bin Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Bin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134757442","display_name":"Bin He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Bin","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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.21080000698566437,"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":0.21080000698566437,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.20520000159740448,"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":0.12720000743865967,"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/robustness","display_name":"Robustness (evolution)","score":0.5856999754905701},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.5835999846458435},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5220999717712402},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.48019999265670776},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.44209998846054077},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.43380001187324524},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4153999984264374},{"id":"https://openalex.org/keywords/offline-learning","display_name":"Offline learning","score":0.40540000796318054},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.3336000144481659}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8123000264167786},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6373000144958496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6176999807357788},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5856999754905701},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.5835999846458435},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5220999717712402},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.48019999265670776},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.44209998846054077},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.43380001187324524},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C2780490138","wikidata":"https://www.wikidata.org/wiki/Q7079636","display_name":"Offline learning","level":3,"score":0.40540000796318054},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C59594135","wikidata":"https://www.wikidata.org/wiki/Q5249242","display_name":"Decision model","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C150325174","wikidata":"https://www.wikidata.org/wiki/Q4335500","display_name":"Optimal decision","level":3,"score":0.28349998593330383},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C2780102126","wikidata":"https://www.wikidata.org/wiki/Q10928179","display_name":"Online and offline","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C28901747","wikidata":"https://www.wikidata.org/wiki/Q177571","display_name":"Decision theory","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26840001344680786},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.2630000114440918},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.25589999556541443},{"id":"https://openalex.org/C2984634286","wikidata":"https://www.wikidata.org/wiki/Q1331926","display_name":"Decision process","level":2,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.23557","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23557","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.23557","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23557","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.8029414415359497,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Building":[0],"scalable":[1],"and":[2,28,51,102,141],"reusable":[3],"multi-agent":[4,15,65],"decision":[5,66],"policies":[6],"from":[7,106],"offline":[8,14,107,138],"datasets":[9,95],"remains":[10],"a":[11,41,69,88,111,133],"challenge":[12],"in":[13,85],"reinforcement":[16],"learning":[17],"(MARL),":[18],"as":[19,68],"existing":[20],"methods":[21],"often":[22],"rely":[23],"on":[24,128],"fixed":[25],"observation":[26],"formats":[27],"action":[29],"spaces":[30],"that":[31,45,132],"limit":[32],"generalization.":[33],"In":[34],"contrast,":[35],"large":[36],"language":[37],"models":[38],"(LLMs)":[39],"offer":[40],"flexible":[42],"modeling":[43],"interface":[44],"can":[46],"naturally":[47],"accommodate":[48],"heterogeneous":[49],"observations":[50],"actions.":[52],"Motivated":[53],"by":[54,110],"this,":[55],"we":[56],"propose":[57],"the":[58,75],"Decision":[59],"Language":[60],"Model":[61],"(DLM),":[62],"which":[63,92],"formulates":[64],"making":[67],"dialogue-style":[70,94],"sequence":[71],"prediction":[72],"problem":[73],"under":[74],"centralized":[76,97],"training":[77,98],"with":[78,99],"decentralized":[79],"execution":[80],"paradigm.":[81],"DLM":[82,135],"is":[83],"trained":[84],"two":[86],"stages:":[87],"supervised":[89],"fine-tuning":[90],"phase,":[91],"leverages":[93],"for":[96],"inter-agent":[100],"context":[101],"generates":[103],"executable":[104],"actions":[105,122],"trajectories,":[108],"followed":[109],"group":[112],"relative":[113],"policy":[114],"optimization":[115],"phase":[116],"to":[117,120,151],"enhance":[118],"robustness":[119],"out-of-distribution":[121],"through":[123],"lightweight":[124],"reward":[125],"functions.":[126],"Experiments":[127],"multiple":[129],"benchmarks":[130],"show":[131],"unified":[134],"outperforms":[136],"strong":[137,148],"MARL":[139],"baselines":[140],"LLM-based":[142],"conversational":[143],"decision-making":[144],"methods,":[145],"while":[146],"demonstrating":[147],"zero-shot":[149],"generalization":[150],"unseen":[152],"scenarios":[153],"across":[154],"tasks.":[155]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-29T00:00:00"}