{"id":"https://openalex.org/W7133315871","doi":"https://doi.org/10.48550/arxiv.2603.00503","title":"M$^2$: Dual-Memory Augmentation for Long-Horizon Web Agents via Trajectory Summarization and Insight Retrieval","display_name":"M$^2$: Dual-Memory Augmentation for Long-Horizon Web Agents via Trajectory Summarization and Insight Retrieval","publication_year":2026,"publication_date":"2026-02-28","ids":{"openalex":"https://openalex.org/W7133315871","doi":"https://doi.org/10.48550/arxiv.2603.00503"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.00503","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00503","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.2603.00503","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127885763","display_name":"Dawei Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yan, Dawei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127938265","display_name":"Haokui Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Haokui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Huzhang, Guangda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huzhang, Guangda","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128029760","display_name":"Yang Li (7082)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127937364","display_name":"Yibo Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yibo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128016245","display_name":"Qing-Guo Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Qing-Guo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127989632","display_name":"Zhao Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127973622","display_name":"Weihua Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Weihua","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128000068","display_name":"Ying Li (38224)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ying","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127917611","display_name":"Wei Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127975543","display_name":"Chunhua Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Chunhua","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5127885763"],"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8190000057220459,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8190000057220459,"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":0.05829999968409538,"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/T12031","display_name":"Speech and dialogue systems","score":0.010700000450015068,"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/automatic-summarization","display_name":"Automatic summarization","score":0.7391999959945679},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6413000226020813},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.43869999051094055},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.43869999051094055},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41449999809265137},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4113999903202057},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.4047999978065491},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.39419999718666077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8486999869346619},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.7391999959945679},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6413000226020813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5047000050544739},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41449999809265137},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4113999903202057},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3937999904155731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37940001487731934},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.35679998993873596},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3411000072956085},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3253999948501587},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.29280000925064087},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.00503","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00503","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.2603.00503","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00503","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":[{"score":0.6976258754730225,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"Large":[1],"Language":[2],"Models":[3],"(MLLMs)":[4],"based":[5],"agents":[6],"have":[7],"demonstrated":[8],"remarkable":[9],"potential":[10],"in":[11],"autonomous":[12],"web":[13],"navigation.":[14],"However,":[15],"handling":[16],"long-horizon":[17,49],"tasks":[18],"remains":[19],"a":[20,57,72,126],"critical":[21],"bottleneck.":[22],"Prevailing":[23],"strategies":[24],"often":[25],"rely":[26],"heavily":[27],"on":[28],"extensive":[29],"data":[30],"collection":[31],"and":[32,42,66,92,115,131],"model":[33],"training,":[34],"yet":[35],"still":[36],"struggle":[37],"with":[38,102],"high":[39],"computational":[40,151],"costs":[41],"insufficient":[43],"reasoning":[44],"capabilities":[45],"when":[46],"facing":[47],"complex,":[48],"scenarios.":[50],"To":[51],"address":[52],"this,":[53],"we":[54],"propose":[55],"M$^2$,":[56],"training-free,":[58],"memory-augmented":[59],"framework":[60],"designed":[61],"to":[62,83,98,125,146],"optimize":[63],"context":[64],"efficiency":[65],"decision-making":[67],"robustness.":[68],"Our":[69],"approach":[70],"incorporates":[71],"dual-tier":[73],"memory":[74],"mechanism":[75],"that":[76,118],"synergizes":[77],"Dynamic":[78],"Trajectory":[79],"Summarization":[80],"(Internal":[81],"Memory)":[82,97],"compress":[84],"verbose":[85],"interaction":[86],"history":[87],"into":[88],"concise":[89],"state":[90],"updates,":[91],"Insight":[93],"Retrieval":[94],"Augmentation":[95],"(External":[96],"guide":[99],"the":[100],"agent":[101],"actionable":[103],"guidelines":[104],"retrieved":[105],"from":[106],"an":[107],"offline":[108],"insight":[109],"bank.":[110],"Extensive":[111],"evaluations":[112],"across":[113],"WebVoyager":[114],"OnlineMind2Web":[116],"demonstrate":[117],"M$^2$":[119],"consistently":[120],"surpasses":[121],"baselines,":[122],"yielding":[123],"up":[124,145],"19.6%":[127],"success":[128],"rate":[129],"increase":[130],"58.7%":[132],"token":[133],"reduction":[134],"for":[135],"Qwen3-VL-32B,":[136],"while":[137],"proprietary":[138],"models":[139],"like":[140],"Claude":[141],"achieve":[142],"accuracy":[143],"gains":[144],"12.5%":[147],"alongside":[148],"significantly":[149],"lower":[150],"overhead.":[152]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2026-03-04T00:00:00"}