{"id":"https://openalex.org/W7138290571","doi":"https://doi.org/10.48550/arxiv.2603.15262","title":"Probe-then-Plan: Environment-Aware Planning for Industrial E-commerce Search","display_name":"Probe-then-Plan: Environment-Aware Planning for Industrial E-commerce Search","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7138290571","doi":"https://doi.org/10.48550/arxiv.2603.15262"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.15262","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15262","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.2603.15262","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113247807","display_name":"M Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Mengxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129656488","display_name":"Zhouwei Zhai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhai, Zhouwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129669237","display_name":"Jin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jin","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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.27059999108314514,"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"}},"topics":[{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.27059999108314514,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.062199998646974564,"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":0.05849999934434891,"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/planner","display_name":"Planner","score":0.7609999775886536},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6100999712944031},{"id":"https://openalex.org/keywords/rewriting","display_name":"Rewriting","score":0.48590001463890076},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.46059998869895935},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.438400000333786},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.36390000581741333},{"id":"https://openalex.org/keywords/automated-planning-and-scheduling","display_name":"Automated planning and scheduling","score":0.34450000524520874},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.34139999747276306}],"concepts":[{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.7609999775886536},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7354000210762024},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6100999712944031},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49300000071525574},{"id":"https://openalex.org/C154690210","wikidata":"https://www.wikidata.org/wiki/Q1668499","display_name":"Rewriting","level":2,"score":0.48590001463890076},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46720001101493835},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.438400000333786},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C114073186","wikidata":"https://www.wikidata.org/wiki/Q2631895","display_name":"Automated planning and scheduling","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C2780490138","wikidata":"https://www.wikidata.org/wiki/Q7079636","display_name":"Offline learning","level":3,"score":0.3003999888896942},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.29330000281333923},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C551230270","wikidata":"https://www.wikidata.org/wiki/Q4368942","display_name":"Data retrieval","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C201789804","wikidata":"https://www.wikidata.org/wiki/Q2362762","display_name":"Search problem","level":2,"score":0.2524000108242035},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.15262","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15262","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.2603.15262","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15262","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"e-commerce":[1],"search":[2,41,70,104],"is":[3,28,134],"evolving":[4],"to":[5,30,97,140],"resolve":[6,60],"complex":[7,167],"user":[8],"intents.":[9],"While":[10],"Large":[11],"Language":[12],"Models":[13],"(LLMs)":[14],"offer":[15],"strong":[16],"reasoning,":[17],"existing":[18],"LLM-based":[19],"paradigms":[20],"face":[21],"a":[22,73,83,86],"fundamental":[23],"blindness-latency":[24],"dilemma:":[25],"query":[26],"rewriting":[27],"agnostic":[29],"retrieval":[31,92],"capabilities":[32],"and":[33,48,101,130,176,189,195],"real-time":[34],"inventory,":[35],"yielding":[36],"invalid":[37],"plans;":[38],"conversely,":[39],"deep":[40],"agents":[42],"rely":[43],"on":[44,180],"iterative":[45],"tool":[46],"calls":[47],"reflection,":[49],"incurring":[50],"seconds":[51],"of":[52],"latency":[53],"incompatible":[54],"with":[55,146],"industrial":[56],"sub-second":[57],"budgets.":[58],"To":[59],"this":[61],"conflict,":[62],"we":[63],"propose":[64],"Environment-Aware":[65],"Search":[66],"Planning":[67],"(EASP),":[68],"reformulating":[69],"planning":[71,165],"as":[72],"dynamic":[74],"reasoning":[75],"process":[76],"grounded":[77,103],"in":[78,193,202],"environmental":[79],"reality.":[80],"EASP":[81,184,197],"introduces":[82],"Probe-then-Plan":[84],"mechanism:":[85],"lightweight":[87],"Retrieval":[88],"Probe":[89],"exposes":[90],"the":[91,95,124],"snapshot,":[93],"enabling":[94],"Planner":[96,128,133],"diagnose":[98],"execution":[99],"gaps":[100],"generate":[102],"plans.":[105],"The":[106,132],"methodology":[107],"comprises":[108],"three":[109],"stages:":[110],"(1)":[111],"Offline":[112],"Data":[113],"Synthesis:":[114],"A":[115,159],"Teacher":[116],"Agent":[117],"synthesizes":[118],"diverse,":[119],"execution-validated":[120],"plans":[121],"by":[122],"diagnosing":[123],"probed":[125],"environment.":[126],"(2)":[127],"Training":[129],"Alignment:":[131],"initialized":[135],"via":[136,151],"Supervised":[137],"Fine-Tuning":[138],"(SFT)":[139],"internalize":[141],"diagnostic":[142],"capabilities,":[143],"then":[144],"aligned":[145],"business":[147],"outcomes":[148],"(conversion":[149],"rate)":[150],"Reinforcement":[152],"Learning":[153],"(RL).":[154],"(3)":[155],"Adaptive":[156],"Online":[157],"Serving:":[158],"complexity-aware":[160],"routing":[161],"mechanism":[162],"selectively":[163],"activates":[164],"for":[166],"queries,":[168],"ensuring":[169],"optimal":[170],"resource":[171],"allocation.":[172],"Extensive":[173],"offline":[174],"evaluations":[175],"online":[177],"A/B":[178],"testing":[179],"JD.com":[181],"demonstrate":[182],"that":[183],"significantly":[185],"improves":[186],"relevant":[187],"recall":[188],"achieves":[190],"substantial":[191],"lifts":[192],"UCVR":[194],"GMV.":[196],"has":[198],"been":[199],"successfully":[200],"deployed":[201],"JD.com's":[203],"AI-Search":[204],"system.":[205]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-18T00:00:00"}