{"id":"https://openalex.org/W7166796270","doi":"https://doi.org/10.18653/v1/2026.semeval-1.6","title":"nchellwig at SemEval-2026 Task 3: Self-Consistent Structured Generation (SCSG) for Dimensional Aspect-Based Sentiment Analysis using Large Language Models","display_name":"nchellwig at SemEval-2026 Task 3: Self-Consistent Structured Generation (SCSG) for Dimensional Aspect-Based Sentiment Analysis using Large Language Models","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166796270","doi":"https://doi.org/10.18653/v1/2026.semeval-1.6"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.semeval-1.6","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.semeval-1.6","pdf_url":"https://aclanthology.org/2026.semeval-1.6.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 20th International Workshop on Semantic Evaluation (2026)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.semeval-1.6.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093323666","display_name":"Nils Constantin Hellwig","orcid":"https://orcid.org/0009-0000-7305-8797"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nils Constantin Hellwig","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088698198","display_name":"Jakob Fehle","orcid":"https://orcid.org/0009-0001-7845-9511"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jakob Fehle","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014534985","display_name":"Udo Kruschwitz","orcid":"https://orcid.org/0000-0002-5503-0341"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Udo Kruschwitz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139826633","display_name":"Christian Wolff","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christian Wolff","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":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78593467,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"47"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.8537999987602234,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.8537999987602234,"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/T12488","display_name":"Mental Health via Writing","score":0.02419999986886978,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.020800000056624413,"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/task","display_name":"Task (project management)","score":0.6003999710083008},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5763000249862671},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4074999988079071},{"id":"https://openalex.org/keywords/computational-linguistics","display_name":"Computational linguistics","score":0.26589998602867126},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.25870001316070557}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6980000138282776},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6291000247001648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6011999845504761},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6003999710083008},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5763000249862671},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2711000144481659},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.25380000472068787},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.semeval-1.6","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.semeval-1.6","pdf_url":"https://aclanthology.org/2026.semeval-1.6.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 20th International Workshop on Semantic Evaluation (2026)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.semeval-1.6","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.semeval-1.6","pdf_url":"https://aclanthology.org/2026.semeval-1.6.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 20th International Workshop on Semantic Evaluation (2026)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166796270.pdf","grobid_xml":"https://content.openalex.org/works/W7166796270.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"Self-Consistent":[2],"Structured":[3],"Generation":[4],"(SCSG)":[5],"for":[6,54,108],"Dimensional":[7],"Aspect-Based":[8],"Sentiment":[9],"Analysis":[10],"in":[11,86],"SemEval-2026":[12],"Task":[13],"3":[14],"(Track":[15],"A).SCSG":[16],"enhances":[17],"prediction":[18],"reliability":[19],"by":[20],"executing":[21],"a":[22,36],"LoRA-adapted":[23],"large":[24],"language":[25],"model":[26],"multiple":[27,46],"times":[28],"per":[29],"instance,":[30],"retaining":[31],"only":[32],"tuples":[33],"that":[34,67],"achieve":[35],"majority":[37],"consensus":[38],"across":[39,59,90],"runs.To":[40],"mitigate":[41],"the":[42,87],"computational":[43],"overhead":[44],"of":[45,99],"forward":[47],"passes,":[48],"we":[49],"leverage":[50],"vLLM's":[51],"PagedAttention":[52],"mechanism":[53],"efficient":[55],"key-value":[56],"cache":[57],"reuse.Evaluation":[58],"6":[60],"languages":[61],"and":[62,103],"8":[63],"language-domain":[64],"combinations":[65],"demonstrates":[66],"self-consistency":[68],"with":[69,79],"15":[70],"executions":[71],"yields":[72],"statistically":[73],"significant":[74],"improvements":[75],"over":[76],"single-inference":[77],"prompting,":[78],"our":[80],"system":[81],"(leveraging":[82],"Gemma":[83],"3)":[84],"ranking":[85],"top":[88],"seven":[89],"all":[91],"settings,":[92],"achieving":[93],"second":[94],"place":[95,105],"on":[96,106],"three":[97],"out":[98],"four":[100],"English":[101],"subsets":[102],"first":[104],"Tatar-Restaurant":[107],"DimASTE.":[109]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}