{"id":"https://openalex.org/W7166799426","doi":"https://doi.org/10.18653/v1/2026.acl-industry.96","title":"ProductResearch: Training E-Commerce Deep Research Agents via Multi-Agent Synthetic Trajectory Distillation","display_name":"ProductResearch: Training E-Commerce Deep Research Agents via Multi-Agent Synthetic Trajectory Distillation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166799426","doi":"https://doi.org/10.18653/v1/2026.acl-industry.96"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.acl-industry.96","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-industry.96","pdf_url":"https://aclanthology.org/2026.acl-industry.96.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.acl-industry.96.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139815966","display_name":"Jiangyuan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jiangyuan Wang","raw_affiliation_strings":["Alibaba International Digital Commercial Group ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba International Digital Commercial Group ,","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009789784","display_name":"Kejun Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Kejun Xiao","raw_affiliation_strings":["Alibaba International Digital Commercial Group ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba International Digital Commercial Group ,","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073188782","display_name":"Huaipeng Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Huaipeng Zhao","raw_affiliation_strings":["Alibaba International Digital Commercial Group ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba International Digital Commercial Group ,","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139778070","display_name":"Tao Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Tao Luo","raw_affiliation_strings":["Alibaba International Digital Commercial Group ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba International Digital Commercial Group ,","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139751984","display_name":"Xiaoyi Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Xiaoyi Zeng","raw_affiliation_strings":["Alibaba International Digital Commercial Group ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba International Digital Commercial Group ,","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.76464452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1378","last_page":"1391"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.04270000010728836,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.04270000010728836,"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/T14347","display_name":"Big Data and Digital Economy","score":0.03099999949336052,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.025499999523162842,"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/training","display_name":"Training (meteorology)","score":0.5638999938964844},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5069000124931335},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3474000096321106},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.329800009727478},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.31779998540878296},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.29319998621940613}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5638999938964844},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5059999823570251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4586000144481659},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3939000070095062},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3474000096321106},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3336000144481659},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.acl-industry.96","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-industry.96","pdf_url":"https://aclanthology.org/2026.acl-industry.96.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.acl-industry.96","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-industry.96","pdf_url":"https://aclanthology.org/2026.acl-industry.96.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4484958052635193}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166799426.pdf","grobid_xml":"https://content.openalex.org/works/W7166799426.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Model":[2],"(LLM)-based":[3],"agents":[4,124],"show":[5,130],"promise":[6],"for":[7,22,56,125,177],"e-commerce":[8,59],"conversational":[9],"shopping,":[10],"yet":[11],"existing":[12],"implementations":[13],"lack":[14],"the":[15,26,157],"interaction":[16],"depth":[17],"and":[18,75,102,153,165,174],"contextual":[19],"breadth":[20],"required":[21],"complex":[23,126],"product":[24,95],"research.Meanwhile,":[25],"Deep":[27],"Research":[28,85],"paradigm,":[29],"despite":[30],"advancing":[31],"information":[32],"synthesis":[33],"in":[34,92,148],"web":[35],"search,":[36],"suffers":[37],"from":[38,72],"domain":[39],"gaps":[40],"when":[41],"transferred":[42],"to":[43,67,87],"e-commerce.We":[44],"propose":[45],"ProductResearch,":[46],"a":[47,64,76,84,105,132],"multi-agent":[48,111,167],"framework":[49,62],"that":[50,79,109,131],"synthesizes":[51],"highfidelity,":[52],"long-horizon":[53],"tool-use":[54],"trajectories":[55,90,98],"training":[57,117,170],"robust":[58],"shopping":[60,70,127,180],"agents.The":[61],"employs":[63],"User":[65],"Agent":[66,78,86],"infer":[68],"nuanced":[69],"intents":[71],"behavioral":[73],"histories,":[74],"Supervisor":[77],"orchestrates":[80],"iterative":[81],"collaboration":[82],"with":[83],"generate":[88],"synthetic":[89,139,168],"culminating":[91],"comprehensive,":[93],"insightful":[94],"research":[96,151,163],"reports.These":[97],"are":[99],"rigorously":[100],"filtered":[101],"distilled":[103],"through":[104],"reflective":[106],"internalization":[107],"process":[108],"consolidates":[110],"supervisory":[112],"interactions":[113],"into":[114],"coherent":[115],"singlerole":[116],"examples,":[118],"enabling":[119],"effective":[120,173],"finetuning":[121],"of":[122,159],"LLM":[123],"inquiries.Extensive":[128],"experiments":[129],"compact":[133],"MoE":[134],"model":[135,147],"fine-tuned":[136],"on":[137],"our":[138],"data":[140],"achieves":[141],"substantial":[142],"improvements":[143],"over":[144],"its":[145],"base":[146],"response":[149],"comprehensiveness,":[150],"depth,":[152],"user-perceived":[154],"utility,":[155],"approaching":[156],"performance":[158],"frontier":[160],"proprietary":[161],"deep":[162],"systems":[164],"establishing":[166],"trajectory":[169],"as":[171],"an":[172],"scalable":[175],"paradigm":[176],"enhancing":[178],"LLM-based":[179],"assistance.":[181]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-07-02T00:00:00"}