{"id":"https://openalex.org/W7166061191","doi":"https://doi.org/10.48550/arxiv.2606.26787","title":"AIGP: An LLM-Based Framework for Long-Term Value Alignment in E-Commerce Pricing","display_name":"AIGP: An LLM-Based Framework for Long-Term Value Alignment in E-Commerce Pricing","publication_year":2026,"publication_date":"2026-06-25","ids":{"openalex":"https://openalex.org/W7166061191","doi":"https://doi.org/10.48550/arxiv.2606.26787"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.26787","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26787","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.2606.26787","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030838042","display_name":"Chennan Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Chennan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139411655","display_name":"Yanning Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yanning","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113751519","display_name":"Siqi Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Siqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024025118","display_name":"Xiuchong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiuchong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139433714","display_name":"Fei Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Fei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5060902826","display_name":"Keping Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Keping","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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.29260000586509705,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.29260000586509705,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.23800000548362732,"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/T11182","display_name":"Auction Theory and Applications","score":0.03869999945163727,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dynamic-pricing","display_name":"Dynamic pricing","score":0.6638000011444092},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5630000233650208},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.48899999260902405},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.439300000667572},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4350000023841858},{"id":"https://openalex.org/keywords/investment-theory","display_name":"Investment theory","score":0.40459999442100525},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.38019999861717224},{"id":"https://openalex.org/keywords/milestone","display_name":"Milestone","score":0.37279999256134033}],"concepts":[{"id":"https://openalex.org/C2779391423","wikidata":"https://www.wikidata.org/wiki/Q17009728","display_name":"Dynamic pricing","level":2,"score":0.6638000011444092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.621999979019165},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5630000233650208},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.48899999260902405},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.439300000667572},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4350000023841858},{"id":"https://openalex.org/C185632549","wikidata":"https://www.wikidata.org/wiki/Q48967834","display_name":"Investment theory","level":3,"score":0.40459999442100525},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.38019999861717224},{"id":"https://openalex.org/C120060458","wikidata":"https://www.wikidata.org/wiki/Q10145","display_name":"Milestone","level":2,"score":0.37279999256134033},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32440000772476196},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.31619998812675476},{"id":"https://openalex.org/C2780193402","wikidata":"https://www.wikidata.org/wiki/Q3394670","display_name":"Pricing strategies","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C14646407","wikidata":"https://www.wikidata.org/wiki/Q1430750","display_name":"Bellman equation","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30979999899864197},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.27970001101493835},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C2777868144","wikidata":"https://www.wikidata.org/wiki/Q7239817","display_name":"Preference elicitation","level":3,"score":0.2630000114440918},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C86637286","wikidata":"https://www.wikidata.org/wiki/Q7317264","display_name":"Rate of return","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.26787","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26787","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.2606.26787","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26787","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":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.6503636837005615}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Traditional":[0],"dynamic":[1],"pricing":[2,62,104,118,167],"models":[3],"in":[4,142,145,149],"large-scale":[5,128],"e-commerce":[6],"suffer":[7],"from":[8],"limited":[9],"interpretability,":[10],"poor":[11],"utilization":[12],"of":[13],"unstructured":[14],"information,":[15],"and":[16,33,55,106,127,147,165],"misalignment":[17],"with":[18,50,120],"long-term":[19,121],"business":[20,122],"objectives":[21],"such":[22],"as":[23,97],"cumulative":[24],"Gross":[25],"Merchandise":[26],"Value":[27,84],"(GMV),":[28],"Return":[29],"on":[30,92,132],"Investment":[31],"(ROI)":[32],"milestone":[34,150],"achievement.":[35],"We":[36],"propose":[37],"AIGP,":[38],"a":[39,44,98],"novel":[40],"framework":[41],"that":[42,136],"leverages":[43],"Large":[45],"Language":[46],"Model":[47],"(LLM)":[48],"prompted":[49],"domain":[51],"knowledge,":[52],"structured":[53],"data":[54],"textual":[56],"context":[57],"to":[58,79,101,157],"make":[59],"interpretable,":[60],"knowledge-aware":[61],"decisions.":[63],"For":[64],"efficient":[65],"deployment":[66],"while":[67,161],"maintaining":[68],"high-quality":[69],"outputs,":[70],"we":[71],"employ":[72],"supervised":[73],"fine-tuning":[74],"for":[75,110],"knowledge":[76],"distillation.":[77],"Central":[78],"AIGP":[80,137],"is":[81],"the":[82,117,158],"Long-Term":[83],"Estimator":[85],"(LTVE),":[86],"trained":[87],"via":[88],"offline":[89,125],"reinforcement":[90],"learning":[91],"historical":[93],"data,":[94],"which":[95],"serves":[96],"reward":[99],"model":[100],"score":[102],"candidate":[103],"actions":[105],"select":[107],"preference":[108],"pairs":[109],"Direct":[111],"Preference":[112],"Optimization":[113],"(DPO),":[114],"thereby":[115],"aligning":[116],"policy":[119],"objectives.":[123],"Extensive":[124],"evaluations":[126],"online":[129],"A/B":[130],"tests":[131],"Tao":[133],"Factory":[134],"demonstrate":[135],"achieves":[138],"significant":[139],"improvements:":[140],"+13.21%":[141],"GMV,":[143],"+7.59%":[144],"ROI,":[146],"+8.20%":[148],"achievement":[151],"rate":[152],"over":[153],"14":[154],"days":[155],"compared":[156],"production":[159],"baseline,":[160],"simultaneously":[162],"providing":[163],"interpretable":[164],"transparent":[166],"rationales.":[168]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-27T00:00:00"}