{"id":"https://openalex.org/W4412889442","doi":"https://doi.org/10.18653/v1/2025.acl-srw.18","title":"iPrOp: Interactive Prompt Optimization for Large Language Models with a Human in the Loop","display_name":"iPrOp: Interactive Prompt Optimization for Large Language Models with a Human in the Loop","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412889442","doi":"https://doi.org/10.18653/v1/2025.acl-srw.18"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-srw.18","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-srw.18","pdf_url":"https://aclanthology.org/2025.acl-srw.18.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 4: Student Research Workshop)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-srw.18.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100462956","display_name":"Jiahui Li","orcid":"https://orcid.org/0000-0002-3953-7345"},"institutions":[{"id":"https://openalex.org/I94626330","display_name":"University of Bamberg","ror":"https://ror.org/01c1w6d29","country_code":"DE","type":"education","lineage":["https://openalex.org/I94626330"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jiahui Li","raw_affiliation_strings":["Fundamentals of Natural Language Processing , University of Bamberg , Germany"],"affiliations":[{"raw_affiliation_string":"Fundamentals of Natural Language Processing , University of Bamberg , Germany","institution_ids":["https://openalex.org/I94626330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090743286","display_name":"Roman Klinger","orcid":"https://orcid.org/0000-0002-2014-6619"},"institutions":[{"id":"https://openalex.org/I94626330","display_name":"University of Bamberg","ror":"https://ror.org/01c1w6d29","country_code":"DE","type":"education","lineage":["https://openalex.org/I94626330"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Roman Klinger","raw_affiliation_strings":["Fundamentals of Natural Language Processing , University of Bamberg , Germany"],"affiliations":[{"raw_affiliation_string":"Fundamentals of Natural Language Processing , University of Bamberg , Germany","institution_ids":["https://openalex.org/I94626330"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100462956"],"corresponding_institution_ids":["https://openalex.org/I94626330"],"apc_list":null,"apc_paid":null,"fwci":2.7453,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91566279,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"276","last_page":"285"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9951000213623047,"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":0.9951000213623047,"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/T10028","display_name":"Topic Modeling","score":0.991599977016449,"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/T12031","display_name":"Speech and dialogue systems","score":0.9865999817848206,"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/computer-science","display_name":"Computer science","score":0.7257028818130493},{"id":"https://openalex.org/keywords/human-in-the-loop","display_name":"Human-in-the-loop","score":0.7116035223007202},{"id":"https://openalex.org/keywords/loop","display_name":"Loop (graph theory)","score":0.6650786399841309},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3733823597431183},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09008005261421204}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7257028818130493},{"id":"https://openalex.org/C2780626000","wikidata":"https://www.wikidata.org/wiki/Q5936775","display_name":"Human-in-the-loop","level":2,"score":0.7116035223007202},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.6650786399841309},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3733823597431183},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09008005261421204},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.acl-srw.18","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-srw.18","pdf_url":"https://aclanthology.org/2025.acl-srw.18.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 4: Student Research Workshop)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.acl-srw.18","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-srw.18","pdf_url":"https://aclanthology.org/2025.acl-srw.18.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 4: Student Research Workshop)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3714701824","display_name":"Interaktive PromptOptimierung mit dem Menschen in der Schleife f\u00fcr die Entwicklung und Intervention von Modellen zum Verst\u00e4ndnis nat\u00fcrlicher Sprache (INPROMPT)","funder_award_id":"521755488","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G6743243744","display_name":null,"funder_award_id":"unknown","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412889442.pdf","grobid_xml":"https://content.openalex.org/works/W4412889442.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W2998994232"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W24774503","https://openalex.org/W4367173559","https://openalex.org/W4409348652","https://openalex.org/W4404795748","https://openalex.org/W4405627308","https://openalex.org/W4404893116","https://openalex.org/W4399126769"],"abstract_inverted_index":{"Prompt":[0],"engineering":[1,37],"has":[2,144],"made":[3],"significant":[4],"contributions":[5],"to":[6,33,47,52,58,92,118,127,147,152],"the":[7,18,45,63,97,129,134,145],"era":[8],"of":[9,20,136],"large":[10,77],"language":[11,78],"models,":[12],"yet":[13],"its":[14],"effectiveness":[15],"depends":[16],"on":[17,100],"skills":[19],"a":[21,27],"prompt":[22,30,36,40,70,137],"author.This":[23],"paper":[24],"introduces":[25],"iPrOp,":[26],"novel":[28],"interactive":[29],"optimization":[31,41,64],"approach,":[32],"bridge":[34],"manual":[35],"and":[38,85,94,104],"automatic":[39],"while":[42],"offering":[43],"users":[44,54,91],"flexibility":[46],"assess":[48],"evolving":[49],"prompts.We":[50],"aim":[51],"provide":[53],"with":[55,81],"task-specific":[56],"guidance":[57],"enhance":[59],"human":[60],"engagement":[61],"in":[62,113],"process,":[65],"which":[66],"is":[67],"structured":[68],"through":[69],"variations,":[71],"informative":[72],"instances,":[73],"predictions":[74],"generated":[75],"by":[76],"models":[79],"along":[80],"their":[82,101,119],"corresponding":[83],"explanations,":[84],"relevant":[86],"performance":[87,135],"metrics.This":[88],"approach":[89,143],"empowers":[90],"choose":[93],"further":[95],"refine":[96],"prompts":[98,116],"based":[99],"individual":[102],"preferences":[103],"needs.It":[105],"can":[106],"not":[107],"only":[108],"assist":[109],"non-technical":[110],"domain":[111],"experts":[112],"generating":[114],"optimal":[115],"tailored":[117],"specific":[120],"tasks":[121],"or":[122],"domains,":[123],"but":[124],"also":[125],"enable":[126],"study":[128],"intrinsic":[130],"parameters":[131],"that":[132,141],"influence":[133],"optimization.The":[138],"evaluation":[139],"shows":[140],"our":[142],"capability":[146],"generate":[148],"improved":[149],"prompts,":[150],"leading":[151],"enhanced":[153],"task":[154],"performance.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
