{"id":"https://openalex.org/W7225017379","doi":"https://doi.org/10.5281/zenodo.23839348","title":"PROMPT ENGINEERING TECHNIQUES IN LARGE LANGUAGE MODELS : A Comparative Study","display_name":"PROMPT ENGINEERING TECHNIQUES IN LARGE LANGUAGE MODELS : A Comparative Study","publication_year":2026,"publication_date":"2026-10-31","ids":{"openalex":"https://openalex.org/W7225017379","doi":"https://doi.org/10.5281/zenodo.23839348"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.23839348","doi":"https://doi.org/10.5281/zenodo.23839348","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23839348","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"JournalArticle"},"volume":null,"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.23839348","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5159101263","display_name":"Vedika Chaudhari","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vedika Chaudhari","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5160261268","display_name":"Prof. Supriya D. Survase","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prof. Supriya D. Survase","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.82041581,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T10028","display_name":"Topic Modeling","score":0.9560999870300293,"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/T10028","display_name":"Topic Modeling","score":0.9560999870300293,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.02630000002682209,"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":0.00570000009611249,"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/prompt-engineering","display_name":"prompt engineering","score":0.996999979019165},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9990000128746033},{"id":"https://openalex.org/keywords/zero-shot-prompting","display_name":"zero-shot prompting","score":0.9869999885559082},{"id":"https://openalex.org/keywords/few-shot-prompting","display_name":"few-shot prompting","score":0.996999979019165},{"id":"https://openalex.org/keywords/chain-of-thought","display_name":"chain-of-thought","score":0.9369999766349792},{"id":"https://openalex.org/keywords/tree-of-thoughts","display_name":"tree-of-thought","score":0.9760000109672546},{"id":"https://openalex.org/keywords/graph-of-thoughts","display_name":"graph-of-thought","score":0.9990000128746033},{"id":"https://openalex.org/keywords/self-refinement","display_name":"self-refinement","score":0.8460000157356262},{"id":"https://openalex.org/keywords/retrieval-augmented-generation","display_name":"retrieval-augmented generation","score":0.9990000128746033},{"id":"https://openalex.org/keywords/multi-step-reasoning","display_name":"multi-step reasoning","score":0.8690000176429749},{"id":"https://openalex.org/keywords/computational-cost","display_name":"computational cost","score":0.4819999933242798},{"id":"https://openalex.org/keywords/external-knowledge-retrieval","display_name":"external knowledge retrieval","score":0.6050000190734863}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6553000211715698},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48500001430511475},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4474000036716461},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.445499986410141},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3928000032901764},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3133000135421753},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.29120001196861267},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.2768000066280365},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.26739999651908875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2644999921321869},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C56289965","wikidata":"https://www.wikidata.org/wiki/Q5249246","display_name":"Decision tree model","level":3,"score":0.25369998812675476},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.23839348","doi":"https://doi.org/10.5281/zenodo.23839348","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23839348","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"JournalArticle"},{"id":"doi:10.5281/zenodo.23839349","doi":"https://doi.org/10.5281/zenodo.23839349","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23839349","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"JournalArticle"}],"best_oa_location":{"id":"doi:10.5281/zenodo.23839348","doi":"https://doi.org/10.5281/zenodo.23839348","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23839348","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"JournalArticle"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7084763325","https://openalex.org/W4402346183","https://openalex.org/W7171810793","https://openalex.org/W7204957365","https://openalex.org/W7208835288","https://openalex.org/W7214052412","https://openalex.org/W4413366872","https://openalex.org/W4406586176","https://openalex.org/W6977138140","https://openalex.org/W7160122775"],"abstract_inverted_index":{"Even":[0],"though":[1],"LLMs":[2],"can":[3,137],"solve":[4,161],"different":[5,143,150],"kinds":[6],"of":[7,13,20,28,44,74,81,85,89,98,222,238],"tasks":[8],"without":[9],"training,":[10],"the":[11,14,18,21,26,63,104,121,126,130,165,198,223,230,232,236,244],"quality":[12],"answer":[15,199],"depends":[16],"on":[17,125],"formulation":[19],"request.":[22],"Prompt":[23],"Engineering":[24],"is":[25,123,167,182],"art":[27],"formulating":[29,216],"a":[30,59,217,226],"question":[31],"right.":[32],"There":[33],"are":[34,187],"many":[35],"ways":[36],"to":[37,61,160,176,215],"do":[38],"it,":[39],"they":[40,186],"differ":[41],"in":[42,103,149,192,200,205,210,213,243],"terms":[43],"their":[45],"design,":[46],"cost,":[47],"use":[48,237],"cases":[49,202],"and":[50,71,93,110,145,172,241],"computational":[51,113],"requirements,":[52],"thus":[53],"it":[54],"may":[55],"be":[56,101,139,177],"challenging":[57],"for":[58],"beginner":[60],"choose":[62],"right":[64],"one.":[65],"In":[66],"this":[67],"paper,":[68],"we":[69],"compare":[70],"contrast":[72],"seven":[73],"them:":[75],"Zero-shot":[76],"Prompting,":[77,79],"Few-shot":[78],"Chain":[80],"Thought":[82],"(CoT),":[83],"Tree":[84],"Thoughts":[86,90],"(ToT),":[87],"Graph":[88],"(GoT),":[91],"Self-Refine,":[92],"Retrieval-Augmented":[94],"Generation":[95],"(RAG).":[96],"All":[97,129],"them":[99],"will":[100],"described":[102],"same":[105],"categories:":[106],"idea,":[107],"example,":[108],"pros":[109],"cons,":[111],"uses,":[112],"requirements.":[114],"No":[115],"experiments":[116],"have":[117],"been":[118],"conducted,":[119],"however,":[120,185],"paper":[122,224],"based":[124],"literature":[127,153],"review.":[128],"information":[131],"comes":[132,212],"from":[133],"original":[134],"sources.":[135],"They":[136],"not":[138,183,204],"compared":[140],"directly":[141],"since":[142],"models":[144],"methods":[146],"were":[147],"used":[148],"papers.":[151],"The":[152,170,207,219],"suggests":[154],"that":[155,193],"reasoning":[156],"steps":[157],"enumeration":[158],"aids":[159],"multi-step":[162],"problems":[163],"if":[164,179],"model":[166],"big":[168],"enough.":[169],"tree":[171],"graph":[173],"approaches":[174],"prove":[175],"helpful":[178],"one":[180,240],"thought":[181],"enough;":[184],"invoked":[188],"much":[189],"more":[190],"often":[191],"case.":[194],"Self":[195],"feedback":[196],"improves":[197],"some":[201],"but":[203],"others.":[206],"external":[208],"knowledge":[209],"RAG":[211],"addition":[214],"prompt.":[218],"last":[220],"part":[221],"includes":[225],"brief":[227],"comparison":[228],"between":[229],"techniques,":[231],"costs":[233],"associated":[234],"with":[235],"each":[239],"gaps":[242],"research.":[245]},"counts_by_year":[],"updated_date":"2026-11-02T09:45:03.842371","created_date":"2026-11-01T00:00:00"}