{"id":"https://openalex.org/W4412889818","doi":"https://doi.org/10.18653/v1/2025.acl-long.1356","title":"Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspective of Probability Theory","display_name":"Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspective of Probability Theory","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412889818","doi":"https://doi.org/10.18653/v1/2025.acl-long.1356"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-long.1356","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1356","pdf_url":"https://aclanthology.org/2025.acl-long.1356.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 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-long.1356.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045586454","display_name":"Yuzheng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yexiang Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100607163","display_name":"Zekun Li","orcid":"https://orcid.org/0000-0002-1207-1901"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zekun Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006734524","display_name":"Zhi Fang","orcid":"https://orcid.org/0000-0002-9495-4467"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhi Fang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003255350","display_name":"Nan Xu","orcid":"https://orcid.org/0000-0002-4154-4763"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nan Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061116624","display_name":"Ran He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ran He","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Tieniu Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tieniu Tan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.4233,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91993627,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"27962","last_page":"27994"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12423","display_name":"Software Reliability and Analysis Research","score":0.6075000166893005,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T12423","display_name":"Software Reliability and Analysis Research","score":0.6075000166893005,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.5841000080108643,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T11242","display_name":"Nuclear Materials and Properties","score":0.5270000100135803,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.8163695335388184},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.6497318744659424},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5506904125213623},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5283882021903992},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3353302478790283},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.32254451513290405},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2488301694393158},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24682027101516724}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.8163695335388184},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.6497318744659424},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5506904125213623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5283882021903992},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3353302478790283},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.32254451513290405},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2488301694393158},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24682027101516724},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/2025.acl-long.1356","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1356","pdf_url":"https://aclanthology.org/2025.acl-long.1356.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 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2505.10981","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.10981","pdf_url":"https://arxiv.org/pdf/2505.10981","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.acl-long.1356","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1356","pdf_url":"https://aclanthology.org/2025.acl-long.1356.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 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412889818.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2018871932","https://openalex.org/W641279757","https://openalex.org/W370975646","https://openalex.org/W1670566515","https://openalex.org/W4242022592","https://openalex.org/W596972243","https://openalex.org/W2149537132"],"abstract_inverted_index":{"Recently,":[0],"scaling":[1,38,98,134,164],"test-time":[2,163],"compute":[3],"on":[4,33,46],"Large":[5],"Language":[6],"Models":[7],"(LLM)":[8],"has":[9,15],"garnered":[10],"wide":[11],"attention.":[12],"However,":[13],"there":[14],"been":[16],"limited":[17],"investigation":[18],"of":[19,147,153],"how":[20],"various":[21],"reasoning":[22],"prompting":[23,51,70,104,155],"strategies":[24,52,71],"perform":[25],"as":[26,61],"scaling.":[27],"In":[28],"this":[29,83],"paper,":[30],"we":[31,90,121],"focus":[32],"a":[34,92],"standard":[35],"and":[36,65,85,100,157],"realistic":[37],"setting:":[39],"majority":[40],"voting.":[41],"We":[42,81,136],"systematically":[43],"conduct":[44],"experiments":[45],"6":[47,54],"LLMs":[48],"$\\times$":[49,53],"8":[50],"benchmarks.":[55],"Experiment":[56],"results":[57],"consistently":[58],"show":[59],"that":[60,138],"the":[62,102,111,133,145,151],"sampling":[63,108],"time":[64],"computational":[66],"overhead":[67],"increase,":[68],"complicated":[69,148],"with":[72],"superior":[73],"initial":[74],"performance":[75,99],"gradually":[76],"fall":[77],"behind":[78],"simple":[79,154],"Chain-of-Thought.":[80],"analyze":[82],"phenomenon":[84],"provide":[86,158],"theoretical":[87,128],"proofs.":[88],"Additionally,":[89],"propose":[91],"probabilistic":[93],"method":[94],"to":[95,130,143],"efficiently":[96],"predict":[97],"identify":[101],"best":[103],"strategy":[105],"under":[106],"large":[107],"times,":[109],"eliminating":[110],"need":[112],"for":[113,161],"resource-intensive":[114],"inference":[115],"processes":[116],"in":[117],"practical":[118],"applications.":[119],"Furthermore,":[120],"introduce":[122],"two":[123],"ways":[124],"derived":[125],"from":[126],"our":[127,139],"analysis":[129],"significantly":[131],"improve":[132],"performance.":[135,165],"hope":[137],"research":[140],"can":[141],"promote":[142],"re-examine":[144],"role":[146],"prompting,":[149],"unleash":[150],"potential":[152],"strategies,":[156],"new":[159],"insights":[160],"enhancing":[162],"Code":[166],"is":[167],"available":[168],"at":[169],"https://github.com/MraDonkey/rethinking_prompting.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
