{"id":"https://openalex.org/W4414581114","doi":"https://doi.org/10.18653/v1/2026.findings-acl.757","title":"TAGS: A Test-Time Generalist\u2013Specialist Framework with Retrieval-Augmented Reasoning and Verification","display_name":"TAGS: A Test-Time Generalist\u2013Specialist Framework with Retrieval-Augmented Reasoning and Verification","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4414581114","doi":"https://doi.org/10.18653/v1/2026.findings-acl.757"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.757","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.757","pdf_url":"https://aclanthology.org/2026.findings-acl.757.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.757.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102761515","display_name":"Jianghao Wu","orcid":"https://orcid.org/0000-0001-6756-5207"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianghao Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007640861","display_name":"Feilong Tang","orcid":"https://orcid.org/0000-0002-1384-198X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feilong Tang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035840897","display_name":"Yulong Li","orcid":"https://orcid.org/0000-0003-3412-0732"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yulong Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020111214","display_name":"Ming-Che Hu","orcid":"https://orcid.org/0000-0002-5288-2936"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming Hu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113031088","display_name":"Haochen Xue","orcid":"https://orcid.org/0009-0008-4913-6853"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haochen Xue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082611298","display_name":"Shoaib Jameel","orcid":"https://orcid.org/0000-0001-7534-3313"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shoaib Jameel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zongyuan Ge","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zongyuan Ge","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101092100","display_name":"Yutong Xie","orcid":"https://orcid.org/0009-0006-4267-905X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yutong Xie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5033585021","display_name":"Imran Razzak","orcid":"https://orcid.org/0000-0002-3930-6600"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Imran Razzak","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":0.00651665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"15428","last_page":"15445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9894999861717224,"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":0.9894999861717224,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9544000029563904,"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":0.9337000250816345,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.6047999858856201},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5960000157356262},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5393000245094299},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4316999912261963},{"id":"https://openalex.org/keywords/automated-reasoning","display_name":"Automated reasoning","score":0.4172999858856201},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.40869998931884766}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7583000063896179},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6047999858856201},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5960000157356262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5521000027656555},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5393000245094299},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4846999943256378},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.4172999858856201},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.40869998931884766},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3490000069141388},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.321399986743927},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C82029504","wikidata":"https://www.wikidata.org/wiki/Q4373882","display_name":"Sequential consistency","level":4,"score":0.296099990606308},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27149999141693115},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.2603999972343445}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.757","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.757","pdf_url":"https://aclanthology.org/2026.findings-acl.757.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2505.18283","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.18283","pdf_url":"https://arxiv.org/pdf/2505.18283","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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"},{"id":"doi:10.48550/arxiv.2505.18283","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2505.18283","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.757","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.757","pdf_url":"https://aclanthology.org/2026.findings-acl.757.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414581114.pdf","grobid_xml":"https://content.openalex.org/works/W4414581114.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"such":[2],"as":[3],"Chain-of-Thought":[4],"prompting":[5],"have":[6],"significantly":[7],"improved":[8],"large":[9],"language":[10],"models":[11],"(LLMs)":[12],"in":[13],"zero-shot":[14],"medical":[15,26,142],"reasoning.However,":[16],"prompting-based":[17],"methods":[18],"often":[19],"remain":[20],"shallow":[21],"and":[22,35,97,100,128],"unstable,":[23],"while":[24],"fine-tuned":[25,141],"LLMs":[27],"suffer":[28],"from":[29,134],"poor":[30],"generalization":[31],"under":[32],"distribution":[33],"shifts":[34],"limited":[36],"adaptability":[37],"to":[38,61,108,136],"unseen":[39],"clinical":[40],"scenarios.To":[41],"address":[42],"these":[43],"limitations,":[44],"we":[45,77],"present":[46],"TAGS,":[47],"a":[48,53,58,82,101,130],"test-time":[49],"framework":[50],"that":[51,86,104],"combines":[52],"broadly":[54],"capable":[55],"generalist":[56],"with":[57],"domainspecific":[59],"specialist":[60],"offer":[62],"complementary":[63],"perspectives":[64],"without":[65,144],"any":[66,145],"model":[67,133],"fine-tuning":[68],"or":[69],"parameter":[70,146],"updates.To":[71],"support":[72],"this":[73],"generalist-specialist":[74],"reasoning":[75,106],"process,":[76],"introduce":[78],"two":[79],"auxiliary":[80],"modules:":[81],"hierarchical":[83],"retrieval":[84],"mechanism":[85],"provides":[87],"multi-scale":[88],"exemplars":[89],"by":[90,123,126],"selecting":[91],"examples":[92],"based":[93],"on":[94],"both":[95],"semantic":[96],"rationale-level":[98],"similarity,":[99],"reliability":[102],"scorer":[103],"evaluates":[105],"consistency":[107],"guide":[109],"final":[110],"answer":[111],"aggregation.TAGS":[112],"achieves":[113],"strong":[114],"performance":[115],"across":[116],"nine":[117],"MedQA":[118],"benchmarks,":[119],"boosting":[120],"GPT-4o":[121],"accuracy":[122],"13.8%,":[124],"DeepSeek-R1":[125],"16.8%,":[127],"improving":[129],"vanilla":[131],"7B":[132],"14.1%":[135],"23.9%.These":[137],"results":[138],"surpass":[139],"several":[140],"LLMs,":[143],"updates.":[147]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
