{"id":"https://openalex.org/W7163683496","doi":"https://doi.org/10.48550/arxiv.2606.05402","title":"ReasoningFlow: Discourse Structures for Understanding LLM Reasoning Traces","display_name":"ReasoningFlow: Discourse Structures for Understanding LLM Reasoning Traces","publication_year":2026,"publication_date":"2026-06-03","ids":{"openalex":"https://openalex.org/W7163683496","doi":"https://doi.org/10.48550/arxiv.2606.05402"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.05402","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05402","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.2606.05402","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055439291","display_name":"Jinu Lee","orcid":"https://orcid.org/0000-0002-8997-448X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Jinu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137997061","display_name":"Shivam Agarwal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Agarwal, Shivam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137529251","display_name":"Amruta Parulekar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Parulekar, Amruta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001735064","display_name":"Siddarth Madala","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Madala, Siddarth","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137937410","display_name":"Dilek Hakkani-Tur","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hakkani-Tur, Dilek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137927134","display_name":"Julia Hockenmaier","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hockenmaier, Julia","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":0.32269999384880066,"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":0.32269999384880066,"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":0.16680000722408295,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.14169999957084656,"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/annotation","display_name":"Annotation","score":0.5821999907493591},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.5382000207901001},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.5224000215530396},{"id":"https://openalex.org/keywords/model-based-reasoning","display_name":"Model-based reasoning","score":0.5040000081062317},{"id":"https://openalex.org/keywords/qualitative-reasoning","display_name":"Qualitative reasoning","score":0.47600001096725464},{"id":"https://openalex.org/keywords/reasoning-system","display_name":"Reasoning system","score":0.4390000104904175},{"id":"https://openalex.org/keywords/backtracking","display_name":"Backtracking","score":0.43700000643730164},{"id":"https://openalex.org/keywords/opportunistic-reasoning","display_name":"Opportunistic reasoning","score":0.41690000891685486},{"id":"https://openalex.org/keywords/semantic-reasoner","display_name":"Semantic reasoner","score":0.4115999937057495}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7181000113487244},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5821999907493591},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.5382000207901001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5343000292778015},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.5224000215530396},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.5040000081062317},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.47600001096725464},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.4390000104904175},{"id":"https://openalex.org/C156884757","wikidata":"https://www.wikidata.org/wiki/Q798554","display_name":"Backtracking","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4318000078201294},{"id":"https://openalex.org/C86827895","wikidata":"https://www.wikidata.org/wiki/Q7098582","display_name":"Opportunistic reasoning","level":4,"score":0.41690000891685486},{"id":"https://openalex.org/C9616225","wikidata":"https://www.wikidata.org/wiki/Q3929429","display_name":"Semantic reasoner","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.388700008392334},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.38350000977516174},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.37299999594688416},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C103057564","wikidata":"https://www.wikidata.org/wiki/Q4751139","display_name":"Analytic reasoning","level":3,"score":0.30140000581741333},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2840999960899353},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C166088908","wikidata":"https://www.wikidata.org/wiki/Q308495","display_name":"Abductive reasoning","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.05402","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05402","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.2606.05402","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05402","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":[{"id":"https://metadata.un.org/sdg/4","score":0.5496605634689331,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"reasoning":[1,5,23,37,118,132],"models":[2,83,107],"(LRMs)":[3],"produce":[4],"traces":[6,38,58,72],"with":[7],"non-linear":[8],"structures,":[9],"such":[10],"as":[11],"backtracking":[12],"and":[13,19,47,81,108,124,167],"self-correction,":[14],"that":[15,30,126],"complicate":[16],"the":[17,22,32,140,159,165],"evaluation":[18],"monitoring":[20],"of":[21,35,56,70,139],"process.":[24],"We":[25,45,163],"introduce":[26],"ReasoningFlow,":[27],"a":[28],"framework":[29],"captures":[31],"discourse":[33,161],"structures":[34],"LRM":[36],"into":[39],"fine-grained":[40,117],"directed":[41],"acyclic":[42],"graphs":[43],"(DAGs).":[44],"develop":[46],"validate":[48],"our":[49],"annotation":[50,55,69],"schema":[51],"through":[52],"careful":[53],"manual":[54],"31":[57],"(2.1k":[59],"steps),":[60],"achieving":[61],"high":[62],"inter-annotator":[63],"agreement,":[64],"then":[65],"scale":[66],"to":[67,146],"automatic":[68],"1,260":[71],"(247.7k":[73],"steps)":[74],"spanning":[75],"three":[76],"tasks":[77],"(math,":[78],"science,":[79],"argumentation)":[80],"five":[82],"(Qwen2.5-32B-Inst,":[84],"QwQ-32B,":[85],"DeepSeek-V3,":[86],"DeepSeek-R1,":[87],"GPT-oss-120B).":[88],"By":[89],"analyzing":[90],"ReasoningFlow":[91,114],"graphs,":[92],"we":[93],"find:":[94],"(1)":[95],"LRMs":[96],"exhibit":[97],"structurally":[98],"similar":[99],"traces,":[100],"despite":[101],"being":[102],"trained":[103],"from":[104],"different":[105],"base":[106],"potentially":[109],"non-overlapping":[110],"post-training":[111],"data.":[112],"(2)":[113],"reveals":[115],"diverse":[116],"behaviors":[119],"(e.g.,":[120],"local":[121],"verification,":[122],"self-reflection,":[123],"assumptions)":[125],"can":[127],"be":[128],"used":[129,145],"for":[130],"better":[131],"trace":[133],"monitorability.":[134],"(3)":[135],"In":[136],"LRMs,":[137],"most":[138],"erroneous":[141],"steps":[142,155],"are":[143],"not":[144,157],"derive":[147],"final":[148],"answers.":[149],"(4)":[150],"Mechanistic":[151],"causal":[152],"dependencies":[153],"between":[154],"do":[156],"reflect":[158],"language-level":[160],"structure.":[162],"release":[164],"dataset":[166],"code":[168],"in:":[169],"https://github.com/jinulee-v/reasoningflow.":[170]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-06T00:00:00"}