{"id":"https://openalex.org/W7129358830","doi":"https://doi.org/10.48550/arxiv.2602.14089","title":"TabTracer: Monte Carlo Tree Search for Complex Table Reasoning with Large Language Models","display_name":"TabTracer: Monte Carlo Tree Search for Complex Table Reasoning with Large Language Models","publication_year":2026,"publication_date":"2026-02-15","ids":{"openalex":"https://openalex.org/W7129358830","doi":"https://doi.org/10.48550/arxiv.2602.14089"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.14089","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.14089","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.14089","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126189138","display_name":"Zhizhao Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Luo, Zhizhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027609768","display_name":"Zhaojing Luo","orcid":"https://orcid.org/0000-0001-7271-3999"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Zhaojing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032263010","display_name":"Meihui Zhang","orcid":"https://orcid.org/0000-0002-0752-9877"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Meihui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126208774","display_name":"Rui Mao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mao, Rui","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5126189138"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.22439999878406525,"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":0.22439999878406525,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.13650000095367432,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.09210000187158585,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5351999998092651},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5216000080108643},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.5194000005722046},{"id":"https://openalex.org/keywords/backtracking","display_name":"Backtracking","score":0.4390000104904175},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4260999858379364},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4221000075340271},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42089998722076416},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.42010000348091125},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.4101000130176544}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8137999773025513},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5351999998092651},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5216000080108643},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.5194000005722046},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4530999958515167},{"id":"https://openalex.org/C156884757","wikidata":"https://www.wikidata.org/wiki/Q798554","display_name":"Backtracking","level":2,"score":0.4390000104904175},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4260999858379364},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4221000075340271},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42089998722076416},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.42010000348091125},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.4101000130176544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39320001006126404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3635999858379364},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33629998564720154},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C111065885","wikidata":"https://www.wikidata.org/wiki/Q1189053","display_name":"Fuzz testing","level":3,"score":0.31679999828338623},{"id":"https://openalex.org/C48859967","wikidata":"https://www.wikidata.org/wiki/Q6486712","display_name":"Language construct","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C190290938","wikidata":"https://www.wikidata.org/wiki/Q387015","display_name":"Trie","level":3,"score":0.2854999899864197},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.2808000147342682},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C110251889","wikidata":"https://www.wikidata.org/wiki/Q1569697","display_name":"Model checking","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26179999113082886},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.2615000009536743},{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C207024777","wikidata":"https://www.wikidata.org/wiki/Q621673","display_name":"Search tree","level":3,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.14089","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.14089","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.14089","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.14089","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1,11],"models":[2],"(LLMs)":[3],"have":[4],"emerged":[5],"as":[6],"powerful":[7],"tools":[8,38],"for":[9,99],"natural":[10],"table":[12,93,136],"reasoning,":[13],"where":[14],"there":[15],"are":[16,68],"two":[17],"main":[18],"categories":[19],"of":[20,134],"methods.":[21],"Prompt-based":[22],"approaches":[23,36],"rely":[24,61],"on":[25,62,173],"language-only":[26],"inference":[27],"or":[28,64],"one-pass":[29],"program":[30],"generation":[31],"without":[32],"step-level":[33,106],"verification.":[34],"Agent-based":[35],"use":[37],"in":[39,189],"a":[40,131,164],"closed":[41],"loop,":[42],"but":[43],"verification":[44,100,107],"is":[45,50],"often":[46],"local":[47],"and":[48,56,101,111,114,121,138,147,160,176],"backtracking":[49],"limited,":[51],"allowing":[52],"errors":[53],"to":[54,73,117,143,167,187],"propagate":[55],"increasing":[57],"cost.":[58,170],"Moreover,":[59],"they":[60],"chain-":[63],"beam-style":[65],"trajectories":[66],"that":[67,86,180],"typically":[69],"combinatorially":[70],"redundant,":[71],"leading":[72],"high":[74],"token":[75,169,193],"costs.":[76],"In":[77],"this":[78],"paper,":[79],"we":[80],"propose":[81],"TabTracer,":[82],"an":[83],"agentic":[84],"framework":[85],"coordinates":[87],"multi-step":[88],"tool":[89],"calls":[90],"over":[91],"intermediate":[92],"states,":[94],"with":[95,108,156,163],"explicit":[96],"state":[97,161],"tracking":[98],"rollback.":[102],"First,":[103],"it":[104,153],"enforces":[105],"typed":[109],"operations":[110],"lightweight":[112],"numeric":[113],"format":[115],"checks":[116],"provide":[118],"reliable":[119],"rewards":[120],"suppress":[122],"hallucinations.":[123],"Second,":[124],"execution-feedback":[125],"Monte":[126],"Carlo":[127],"Tree":[128],"Search":[129],"maintains":[130],"search":[132],"tree":[133],"candidate":[135],"states":[137],"uses":[139],"backpropagated":[140],"reflection":[141],"scores":[142],"guide":[144],"UCB1":[145],"selection":[146],"rollback":[148],"via":[149],"versioned":[150],"snapshots.":[151],"Third,":[152],"reduces":[154],"redundancy":[155],"budget-aware":[157],"pruning,":[158],"deduplication,":[159],"hashing":[162],"monotonicity":[165],"gate":[166],"cut":[168],"Comprehensive":[171],"evaluation":[172],"TabFact,":[174],"WikiTQ,":[175],"CRT":[177],"datasets":[178],"shows":[179],"TabTracer":[181],"outperforms":[182],"state-of-the-art":[183],"baselines":[184],"by":[185,195],"up":[186],"6.7%":[188],"accuracy":[190],"while":[191],"reducing":[192],"consumption":[194],"59--84%.":[196]},"counts_by_year":[],"updated_date":"2026-02-18T06:25:47.457606","created_date":"2026-02-18T00:00:00"}