{"id":"https://openalex.org/W6888077423","doi":"https://doi.org/10.18420/inf2024_113","title":"Assessing Large Language Models in the Agricultural Sector: A Comprehensive Analysis Utilizing a Novel Synthetic Benchmark Dataset","display_name":"Assessing Large Language Models in the Agricultural Sector: A Comprehensive Analysis Utilizing a Novel Synthetic Benchmark Dataset","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W6888077423","doi":"https://doi.org/10.18420/inf2024_113"},"language":"en","primary_location":{"id":"doi:10.18420/inf2024_113","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2024_113","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.18420/inf2024_113","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"K\u00e4sting, Marvin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"K\u00e4sting, Marvin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"H\u00e4nig, Christian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"H\u00e4nig, Christian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"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":0.2857904,"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":true,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.6437000036239624,"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":0.6437000036239624,"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":0.050999999046325684,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.03290000185370445,"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/benchmark","display_name":"Benchmark (surveying)","score":0.9345999956130981},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.7148000001907349},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.5503000020980835},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.46239998936653137},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4359000027179718},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.3467999994754791}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.9345999956130981},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.7148000001907349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6664000153541565},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5701000094413757},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.5503000020980835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5146999955177307},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.46239998936653137},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44760000705718994},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3352999985218048},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3028999865055084},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.27230000495910645},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2574000060558319}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18420/inf2024_113","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2024_113","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.18420/inf2024_113","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2024_113","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.6844019889831543}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,86],"paper":[1],"provides":[2],"a":[3,65,75],"comprehensive":[4],"study":[5],"of":[6,67,98],"Large":[7],"Language":[8],"Models":[9],"(LLMs)":[10],"for":[11],"question-answering":[12],"and":[13,38,103],"information":[14],"retrieval":[15],"tasks":[16],"within":[17],"the":[18,23,83,96],"agricultural":[19,42,55,84],"domain.":[20],"We":[21],"introduce":[22],"novel":[24],"benchmark":[25,61],"dataset":[26],"BVL":[27],"QA":[28],"Corpus":[29],"2024":[30],"specifically":[31],"designed":[32],"to":[33,82,91,94],"thoroughly":[34],"evaluate":[35],"both":[36],"commercial":[37],"non-commercial":[39],"LLMs":[40,68,117],"in":[41],"contexts.":[43],"Using":[44],"LLMs,":[45],"we":[46,63,73],"generate":[47],"question-answer":[48],"pairs":[49],"from":[50,53],"paragraphs":[51],"extracted":[52],"domain-specific":[54],"documents.":[56],"Leveraging":[57],"this":[58],"newly":[59],"developed":[60],"dataset,":[62],"assess":[64],"selection":[66],"using":[69],"standard":[70],"metrics.":[71,120],"Additionally,":[72],"develop":[74],"prototype":[76],"Retrieval-Augmented":[77],"Generation":[78],"(RAG)":[79],"system":[80,87],"tailored":[81],"sector.":[85],"is":[88],"then":[89],"compared":[90],"baseline":[92,116],"evaluations":[93],"determine":[95],"degree":[97],"alignment":[99],"between":[100],"actual":[101],"performance":[102],"initial":[104],"upper":[105],"limit":[106],"estimations.":[107],"Our":[108],"empirical":[109],"analysis":[110],"demonstrates":[111],"that":[112],"RAG":[113],"systems":[114],"outperform":[115],"across":[118],"all":[119]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}