{"id":"https://openalex.org/W7163679954","doi":"https://doi.org/10.48550/arxiv.2606.05859","title":"TARPO: Token-Wise Latent-Explicit Reasoning via Action-Routing Policy Optimization","display_name":"TARPO: Token-Wise Latent-Explicit Reasoning via Action-Routing Policy Optimization","publication_year":2026,"publication_date":"2026-06-04","ids":{"openalex":"https://openalex.org/W7163679954","doi":"https://doi.org/10.48550/arxiv.2606.05859"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.05859","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05859","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":null,"license_id":null,"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.2606.05859","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137932012","display_name":"Liting Zhang (2883890)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Liting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137950975","display_name":"Shiwan Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Shiwan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137967757","display_name":"Xuyang Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Xuyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133356835","display_name":"Zichen Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zichen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100417821","display_name":"Jianye Wang","orcid":"https://orcid.org/0000-0003-0821-3089"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jianye","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067376482","display_name":"Qicheng Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Qicheng","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":0.4242999851703644,"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":0.4242999851703644,"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":0.12800000607967377,"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":0.10409999638795853,"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/security-token","display_name":"Security token","score":0.6230999827384949},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4855000078678131},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4652999937534332},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4580000042915344},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.40149998664855957},{"id":"https://openalex.org/keywords/router","display_name":"Router","score":0.39329999685287476},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.365200012922287}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7513999938964844},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6230999827384949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5085999965667725},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4855000078678131},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4580000042915344},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.40149998664855957},{"id":"https://openalex.org/C2775896111","wikidata":"https://www.wikidata.org/wiki/Q642560","display_name":"Router","level":2,"score":0.39329999685287476},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38420000672340393},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.365200012922287},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3287000060081482},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2955999970436096},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.26660001277923584},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.05859","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05859","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.05859","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05859","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7406896352767944}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Latent":[0],"reasoning":[1,20,68,140],"has":[2],"emerged":[3],"as":[4],"a":[5,54,74,87,91,115],"promising":[6],"alternative":[7],"to":[8,126],"discrete":[9,62,99],"Chain-of-Thought":[10],"(CoT)":[11],"in":[12,37],"large":[13],"language":[14],"models":[15],"(LLMs),":[16],"enabling":[17],"more":[18],"expressive":[19],"by":[21],"operating":[22],"over":[23],"continuous":[24,32,66],"representations.":[25],"However,":[26],"the":[27,81,96,103],"inherently":[28],"deterministic":[29],"nature":[30],"of":[31,98],"representations":[33],"limits":[34],"policy":[35],"exploration":[36],"reinforcement":[38],"learning":[39],"(RL).":[40],"To":[41],"address":[42],"this,":[43],"we":[44],"propose":[45],"TARPO":[46,72,133,150],"(Token-Wise":[47],"Latent-Explicit":[48],"Reasoning":[49],"via":[50],"Action-Routing":[51],"Policy":[52],"Optimization),":[53],"pure":[55],"RL":[56,141],"framework":[57],"that":[58,79,132,149],"adaptively":[59],"switches":[60],"between":[61],"token":[63,100],"generation":[64],"and":[65,85,108,128,138],"latent":[67,139],"at":[69,165],"each":[70],"step.":[71],"introduces":[73],"lightweight":[75],"action":[76],"head":[77],"router":[78,109],"observes":[80],"current":[82],"hidden":[83],"state":[84],"samples":[86],"routing":[88],"decision":[89],"from":[90,102],"binary":[92],"mode-selection":[93],"space,":[94],"preserving":[95],"stochasticity":[97],"sampling":[101],"vocabulary.":[104],"The":[105],"LLM":[106],"backbone":[107],"are":[110],"jointly":[111],"optimized":[112],"end-to-end":[113],"with":[114],"shared":[116],"group-relative":[117],"advantage":[118],"signal.":[119],"Extensive":[120],"experiments":[121],"across":[122,143],"Qwen2.5":[123],"(from":[124],"1.5B":[125],"7B)":[127],"Llama-3.1-8B":[129],"backbones":[130],"demonstrate":[131],"consistently":[134],"outperforms":[135],"existing":[136],"explicit":[137],"baselines":[142],"diverse":[144],"benchmarks.":[145],"Further":[146],"analysis":[147],"shows":[148],"learns":[151],"adaptive":[152],"token-wise":[153],"switching":[154],"behaviors":[155],"while":[156],"maintaining":[157],"stable":[158],"training":[159],"dynamics.":[160],"Our":[161],"code":[162],"is":[163],"available":[164],"https://github.com/NKU-LITI/TARPO-master.":[166]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-06T00:00:00"}
