{"id":"https://openalex.org/W7168271328","doi":"https://doi.org/10.48550/arxiv.2607.10562","title":"CRiT-QA: Evaluating Multi-hop Reasoning with Counterfactual Chains and Distractor Traps","display_name":"CRiT-QA: Evaluating Multi-hop Reasoning with Counterfactual Chains and Distractor Traps","publication_year":2026,"publication_date":"2026-07-12","ids":{"openalex":"https://openalex.org/W7168271328","doi":"https://doi.org/10.48550/arxiv.2607.10562"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.10562","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.10562","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.10562","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140673650","display_name":"JungMin Yun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yun, JungMin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140579059","display_name":"JuneHyoung Kwon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kwon, JuneHyoung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140649676","display_name":"YoungBin Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, YoungBin","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":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":0.8055999875068665,"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":0.8055999875068665,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.026499999687075615,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.02500000037252903,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9559000134468079},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6578999757766724},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5200999975204468},{"id":"https://openalex.org/keywords/visual-reasoning","display_name":"Visual reasoning","score":0.4672999978065491},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4187000095844269},{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.40059998631477356},{"id":"https://openalex.org/keywords/motivated-reasoning","display_name":"Motivated reasoning","score":0.385699987411499},{"id":"https://openalex.org/keywords/counterfactual-conditional","display_name":"Counterfactual conditional","score":0.3490000069141388}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9559000134468079},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6578999757766724},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5856000185012817},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5200999975204468},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.4672999978065491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46160000562667847},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.41690000891685486},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.40059998631477356},{"id":"https://openalex.org/C2776325391","wikidata":"https://www.wikidata.org/wiki/Q6917865","display_name":"Motivated reasoning","level":3,"score":0.385699987411499},{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.3490000069141388},{"id":"https://openalex.org/C103057564","wikidata":"https://www.wikidata.org/wiki/Q4751139","display_name":"Analytic reasoning","level":3,"score":0.3393000066280365},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.3303999900817871},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30070000886917114},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C76188268","wikidata":"https://www.wikidata.org/wiki/Q1783165","display_name":"Context effect","level":3,"score":0.288100004196167},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.2791999876499176},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.27790001034736633},{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.10562","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.10562","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:10.48550/arxiv.2607.10562","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.10562","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Evaluating":[0],"the":[1,42,59,124],"multi-hop":[2,21,168],"reasoning":[3,97,111,126,169],"capabilities":[4],"of":[5,48],"large":[6],"language":[7],"models":[8,15,121],"remains":[9],"a":[10,75,161,172],"significant":[11],"challenge.":[12],"Although":[13],"current":[14],"achieve":[16],"strong":[17],"results":[18],"on":[19,34,86,142],"existing":[20],"question":[22],"answering":[23],"datasets,":[24,147],"such":[25,51],"performance":[26,140],"often":[27],"masks":[28],"two":[29],"critical":[30],"vulnerabilities:":[31],"(1)":[32],"reliance":[33,85],"internal":[35],"parametric":[36],"knowledge":[37,88],"rather":[38,128],"than":[39,129],"adherence":[40],"to":[41,79,122,145,151],"provided":[43],"context,":[44],"and":[45,89,154,170],"(2)":[46],"exploitation":[47],"dataset":[49,76],"shortcuts,":[50],"as":[52,160],"single-document":[53],"cues":[54],"or":[55],"type-matching,":[56],"that":[57,113,136],"diminish":[58],"need":[60],"for":[61,165,174],"genuine":[62,167],"evidence":[63],"aggregation":[64],"across":[65],"multiple":[66],"documents.":[67],"We":[68],"introduce":[69],"CRiT-QA":[70,94,143,157],"(Counterfactual":[71],"Reasoning":[72],"with":[73,99],"Traps),":[74],"explicitly":[77],"designed":[78],"address":[80],"both":[81],"limitations.":[82],"To":[83],"neutralize":[84],"memorized":[87],"enforce":[90],"strict":[91],"context":[92],"dependency,":[93],"transforms":[95],"factual":[96],"chains":[98],"counterfactual":[100,152],"entities.":[101],"Furthermore,":[102],"it":[103],"injects":[104],"multi-anchor":[105],"distractor":[106,155],"chains,":[107],"plausible":[108],"but":[109],"incorrect":[110],"paths":[112],"diverge":[114],"at":[115],"different":[116],"hops.":[117],"These":[118],"traps":[119],"require":[120],"follow":[123],"entire":[125],"process":[127],"exploiting":[130],"shallow":[131],"heuristics.":[132],"Our":[133],"experiments":[134],"show":[135],"LLMs":[137],"exhibit":[138],"substantial":[139],"degradation":[141],"compared":[144],"standard":[146],"exposing":[148],"their":[149],"vulnerability":[150],"conditions":[153],"traps.":[156],"thus":[158],"serves":[159],"rigorous":[162],"diagnostic":[163],"tool":[164],"evaluating":[166],"provides":[171],"foundation":[173],"developing":[175],"more":[176],"reliable,":[177],"evidence-grounded":[178],"LLMs.":[179]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-15T00:00:00"}