{"id":"https://openalex.org/W7162797406","doi":"https://doi.org/10.48550/arxiv.2605.30227","title":"Unifying Temporal and Structural Credit Assignment in LLM-Based Multi-Agent Prompt Optimization","display_name":"Unifying Temporal and Structural Credit Assignment in LLM-Based Multi-Agent Prompt Optimization","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7162797406","doi":"https://doi.org/10.48550/arxiv.2605.30227"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30227","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30227","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.2605.30227","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137397716","display_name":"Wenwu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Wenwu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042338811","display_name":"Yuran Song","orcid":"https://orcid.org/0000-0003-1218-4719"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yuran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137320599","display_name":"Mingze Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Mingze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137337481","display_name":"Bo Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Bo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137318700","display_name":"Wenhao Li","orcid":"https://orcid.org/0009-0006-1400-3773"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Wenhao","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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.2062000036239624,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.2062000036239624,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.17499999701976776,"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/T10028","display_name":"Topic Modeling","score":0.08780000358819962,"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/coordinate-descent","display_name":"Coordinate descent","score":0.510699987411499},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5083000063896179},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4844000041484833},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.48249998688697815},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4724999964237213},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4138999879360199},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.3856000006198883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7462999820709229},{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.510699987411499},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5083000063896179},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4844000041484833},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.48249998688697815},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4724999964237213},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4142000079154968},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4052000045776367},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3856000006198883},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35339999198913574},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34150001406669617},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2768000066280365},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2702000141143799},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.2606000006198883}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30227","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30227","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.2605.30227","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30227","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":[{"display_name":"Reduced inequalities","score":0.6232353448867798,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"Multi-Agent":[1],"Systems":[2],"(MAS)":[3],"empower":[4],"Large":[5],"Language":[6],"Models":[7],"to":[8,24,44,48,67,91,103,141],"tackle":[9],"complex":[10],"reasoning":[11,150],"tasks":[12],"through":[13],"collaborative":[14],"interaction,":[15],"optimizing":[16,131],"their":[17],"dynamics":[18],"remains":[19],"a":[20,113,162],"formidable":[21],"challenge":[22],"due":[23],"the":[25,30,34,80,144],"discrete,":[26,114],"non-differentiable":[27],"nature":[28],"of":[29,36],"computation":[31],"graph":[32],"and":[33,74,95,134,164],"sparsity":[35],"global":[37,126],"supervisory":[38],"signals.":[39,70],"Existing":[40],"black-box":[41],"optimizers":[42],"struggle":[43],"attribute":[45],"trajectory-level":[46],"failure":[47],"specific":[49],"local":[50],"components,":[51],"resulting":[52],"in":[53],"inefficient,":[54],"high-variance":[55],"exploration.":[56],"We":[57,71],"argue":[58],"that":[59],"tractable":[60],"MAS":[61],"optimization":[62],"needs":[63],"structural":[64,75,97],"inductive":[65],"biases":[66],"disentangle":[68],"error":[69],"propose":[72],"temporal":[73,86],"credit":[76],"assignment,":[77],"which":[78],"decomposes":[79],"objective":[81],"along":[82],"two":[83],"axes:":[84],"(i)":[85],"credit,":[87,98],"using":[88,99,137],"state-space":[89],"bottlenecks":[90],"identify":[92],"critical":[93],"rounds,":[94],"(ii)":[96],"stationary":[100],"role":[101,132],"policies":[102],"isolate":[104],"agent":[105],"contributions.":[106],"Leveraging":[107],"these":[108],"decomposed":[109],"signals,":[110],"we":[111],"introduce":[112],"verbalized":[115],"block":[116],"coordinate":[117],"descent":[118],"algorithm":[119],"for":[120],"iterative":[121],"refinement.":[122],"Rather":[123],"than":[124],"indiscriminate":[125],"updates,":[127],"it":[128],"alternates":[129],"between":[130],"prompts":[133],"aggregation":[135],"protocols,":[136],"LLM-generated":[138],"\"proxy":[139],"gradients\"":[140],"target":[142],"only":[143],"identified":[145],"weak":[146],"links.":[147],"Across":[148],"diverse":[149],"benchmarks,":[151],"our":[152],"approach":[153],"substantially":[154],"reduces":[155],"query":[156],"complexity":[157],"while":[158],"improving":[159],"performance,":[160],"providing":[161],"principled":[163],"interpretable":[165],"path":[166],"toward":[167],"self-improving":[168],"MAS.":[169]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-30T00:00:00"}
