{"id":"https://openalex.org/W7157123882","doi":"https://doi.org/10.48550/arxiv.2604.23396","title":"Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval","display_name":"Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval","publication_year":2026,"publication_date":"2026-04-25","ids":{"openalex":"https://openalex.org/W7157123882","doi":"https://doi.org/10.48550/arxiv.2604.23396"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.23396","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23396","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.2604.23396","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106343200","display_name":"Kidist Amde Mekonnen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mekonnen, Kidist Amde","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134769240","display_name":"Yongkang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yongkang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101101653","display_name":"Yubao Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Yubao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034714310","display_name":"Simon Lupart","orcid":"https://orcid.org/0009-0008-2383-4557"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lupart, Simon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134780373","display_name":"Maarten de Rijke","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"de Rijke, Maarten","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/T10181","display_name":"Natural Language Processing Techniques","score":0.29510000348091125,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.29510000348091125,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.289900004863739,"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/T10028","display_name":"Topic Modeling","score":0.09200000017881393,"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/decoding-methods","display_name":"Decoding methods","score":0.7989000082015991},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.566100001335144},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5637999773025513},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4602000117301941},{"id":"https://openalex.org/keywords/grammaticality","display_name":"Grammaticality","score":0.4551999866962433},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4406999945640564},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4214000105857849},{"id":"https://openalex.org/keywords/decodes","display_name":"Decodes","score":0.3720000088214874}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7989000082015991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7311000227928162},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.566100001335144},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5637999773025513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4697999954223633},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4602000117301941},{"id":"https://openalex.org/C2779525943","wikidata":"https://www.wikidata.org/wiki/Q1187300","display_name":"Grammaticality","level":3,"score":0.4551999866962433},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4214000105857849},{"id":"https://openalex.org/C2778858076","wikidata":"https://www.wikidata.org/wiki/Q5249539","display_name":"Decodes","level":3,"score":0.3720000088214874},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3294000029563904},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.28290000557899475},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C30684385","wikidata":"https://www.wikidata.org/wiki/Q176509","display_name":"Ringing","level":3,"score":0.273499995470047},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.26589998602867126},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.23396","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23396","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.2604.23396","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23396","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generative":[0,34],"retrieval":[1],"(GR)":[2],"ranks":[3],"documents":[4],"by":[5,41],"autoregressively":[6],"generating":[7],"document":[8],"identifiers.":[9],"Because":[10],"many":[11],"GR":[12],"methods":[13],"rely":[14],"on":[15,86,229],"trie-constrained":[16],"beam":[17],"search,":[18],"they":[19],"are":[20],"vulnerable":[21],"to":[22,45],"early":[23],"pruning":[24],"of":[25,215,232],"relevant":[26],"prefixes":[27],"under":[28,75,141,218,236],"finite-beam":[29],"decoding.":[30,55,132],"Planning":[31],"Ahead":[32],"in":[33,99,202],"Retrieval":[35],"(PAG)":[36],"mitigates":[37],"this":[38],"failure":[39],"mode":[40],"using":[42,179],"simultaneous":[43],"decoding":[44,65,78,168,217],"compute":[46],"a":[47],"document-level":[48],"look-ahead":[49,160],"prior":[50],"that":[51,110,135,158,192,225],"guides":[52],"subsequent":[53],"sequential":[54],"We":[56,133,173],"reproduce":[57,81],"PAG":[58],"at":[59],"inference":[60,221],"time":[61],"and":[62,72,90,93,122,126,187,212,240],"stress-test":[63],"its":[64],"behavior.":[66],"Using":[67],"the":[68,76,82,95,117,152,159,199,213,219,230,233],"authors'":[69],"released":[70,220],"checkpoint":[71],"identifier/trie":[73],"artifacts":[74],"reported":[77,96,210],"setup,":[79,222],"we":[80,105],"main":[83],"effectiveness":[84,211],"results":[85,207],"MS":[87],"MARCO":[88],"Dev":[89],"TREC-DL":[91],"2019/2020,":[92],"corroborate":[94],"beam-size-latency":[97],"trade-off":[98],"our":[100,203,206],"hardware":[101],"setting.":[102,204],"Beyond":[103],"reproduction,":[104],"introduce":[106],"plan":[107,149],"drift":[108],"diagnostics":[109],"quantify":[111],"how":[112,127],"intent-preserving":[113,145],"query":[114,196,238],"variations":[115],"alter":[116],"planner's":[118],"top-n":[119],"candidate":[120,154],"set":[121],"highest-weight":[123],"planner":[124],"tokens,":[125],"these":[128,226],"changes":[129],"affect":[130],"guided":[131],"find":[134],"PAG's":[136,209],"planning":[137,234],"signal":[138,235],"is":[139],"brittle":[140],"lexical":[142],"surface-form":[143],"variation:":[144],"typos":[146],"can":[147],"trigger":[148],"collapse,":[150],"where":[151],"planned":[153],"pool":[155],"shifts":[156],"enough":[157],"bonus":[161],"provides":[162,198],"little":[163],"useful":[164],"guidance,":[165],"effectively":[166],"reverting":[167],"toward":[169],"weaker":[170],"unguided":[171],"search.":[172],"further":[174],"evaluate":[175],"fixed-index":[176],"cross-lingual":[177],"robustness":[178],"non-English":[180],"mMARCO":[181],"queries":[182],"against":[183],"an":[184],"English":[185],"index,":[186],"assess":[188],"query-side":[189],"mitigation":[190],"strategies":[191],"require":[193],"no":[194],"re-indexing;":[195],"translation":[197],"strongest":[200],"recovery":[201],"Overall,":[205],"confirm":[208],"benefit":[214],"planning-guided":[216],"while":[223],"showing":[224],"gains":[227],"depend":[228],"stability":[231],"realistic":[237],"variation":[239],"query-document":[241],"mismatch.":[242]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-29T00:00:00"}