{"id":"https://openalex.org/W4416037136","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.29","title":"RoT: Enhancing Table Reasoning with Iterative Row-Wise Traversals","display_name":"RoT: Enhancing Table Reasoning with Iterative Row-Wise Traversals","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416037136","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.29"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.emnlp-main.29","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.29","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.29","pdf_url":"https://aclanthology.org/2025.emnlp-main.29.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2025.emnlp-main.29.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018081469","display_name":"Xuanliang Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanliang Zhang","raw_affiliation_strings":["Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000300840","display_name":"Dingzirui Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingzirui Wang","raw_affiliation_strings":["Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102437760","display_name":"Keyan Xu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keyan Xu","raw_affiliation_strings":["Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100584833","display_name":"Qingfu Zhu","orcid":"https://orcid.org/0000-0003-3395-222X","observed_orcids":["https://orcid.org/0000-0003-3395-222X"]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingfu Zhu","raw_affiliation_strings":["Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019108029","display_name":"Wanxiang Che","orcid":"https://orcid.org/0000-0002-3907-0335","observed_orcids":["https://orcid.org/0000-0002-3907-0335"]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanxiang Che","raw_affiliation_strings":["Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":3.793,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.94508438,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"559","last_page":"579"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8568999767303467,"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":0.8568999767303467,"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":0.09200000017881393,"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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.015599999576807022,"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/table-reasoning","display_name":"table reasoning","score":0.9950000047683716},{"id":"https://openalex.org/keywords/long-chain-of-thought","display_name":"long chain-of-thought","score":0.8809999823570251},{"id":"https://openalex.org/keywords/hallucination-mitigation","display_name":"hallucination mitigation","score":0.7400000095367432},{"id":"https://openalex.org/keywords/training-free-reasoning","display_name":"training-free reasoning","score":0.6990000009536743},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.7919999957084656},{"id":"https://openalex.org/keywords/iterative-reasoning","display_name":"iterative reasoning","score":0.503000020980835}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5570999979972839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44020000100135803},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.41029998660087585},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.260699987411499},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2606000006198883},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25940001010894775},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.25699999928474426}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/2025.emnlp-main.29","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.29","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.29","pdf_url":"https://aclanthology.org/2025.emnlp-main.29.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2505.15110","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.15110","pdf_url":"https://arxiv.org/pdf/2505.15110","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,"listed_in":[],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2505.15110","doi":"https://doi.org/10.48550/arxiv.2505.15110","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2505.15110","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,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.emnlp-main.29","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.29","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.29","pdf_url":"https://aclanthology.org/2025.emnlp-main.29.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2565984771","display_name":null,"funder_award_id":"62236004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3596954764","display_name":null,"funder_award_id":"62476073","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4035621038","display_name":null,"funder_award_id":"62441603","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416037136.pdf","grobid_xml":"https://content.openalex.org/works/W4416037136.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4414897670","https://openalex.org/W4390784213","https://openalex.org/W4416036470","https://openalex.org/W4406709267","https://openalex.org/W7128294665","https://openalex.org/W7124167994","https://openalex.org/W4394907085","https://openalex.org/W6967047494","https://openalex.org/W4416343982","https://openalex.org/W4318908878"],"abstract_inverted_index":{"The":[0],"table":[1,17,38,54,65],"reasoning":[2,19,31,69,77,135],"task,":[3],"crucial":[4],"for":[5,46,68],"efficient":[6],"data":[7],"acquisition,":[8],"aims":[9],"to":[10,34,53,96],"answer":[11],"questions":[12],"based":[13],"on":[14,37,119],"the":[15,97],"given":[16],".Recently,":[18],"large":[20],"language":[21],"models":[22],"(RLLMs)":[23],"with":[24,123,133],"Long":[25,40,131],"Chain-of-Thought":[26],"(Long":[27],"CoT)":[28],"significantly":[29],"enhance":[30],"capabilities,":[32],"leading":[33],"brilliant":[35],"performance":[36],"reasoning.However,":[39],"CoT":[41,132],"suffers":[42],"from":[43],"high":[44],"cost":[45],"training":[47],"and":[48,71,82,115,121],"exhibits":[49],"low":[50],"reliability":[51],"due":[52],"content":[55],"hallucinations.Therefore,":[56],"we":[57],"propose":[58],"Rowof-Thought":[59],"(ROT),":[60],"which":[61],"performs":[62],"iteratively":[63],"row-wise":[64],"traversal,":[66],"allowing":[67],"extension":[70],"reflection-based":[72],"refinement":[73],"at":[74],"each":[75],"traversal.Scaling":[76],"length":[78],"by":[79,110],"rowwise":[80],"traversal":[81,92],"leveraging":[83],"reflection":[84],"capabilities":[85],"of":[86,113],"LLMs,":[87],"ROT":[88,129],"is":[89],"training-free.The":[90],"sequential":[91],"encourages":[93],"greater":[94],"attention":[95],"table,":[98],"thus":[99],"reducing":[100],"hallucinations.Experiments":[101],"show":[102],"that":[103],"ROT,":[104],"using":[105],"non-reasoning":[106],"models,":[107,125],"outperforms":[108,130],"RLLMs":[109],"an":[111],"average":[112],"4.3%,":[114],"achieves":[116],"state-of-the-art":[117],"results":[118],"WikiTableQuestions":[120],"TableBench":[122],"comparable":[124],"proving":[126],"its":[127],"effectiveness.Also,":[128],"fewer":[134],"tokens,":[136],"indicating":[137],"higher":[138],"efficiency.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":4}],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2025-11-08T00:00:00"}