{"id":"https://openalex.org/W4310290453","doi":"https://doi.org/10.48550/arxiv.2211.14275","title":"Solving math word problems with process- and outcome-based feedback","display_name":"Solving math word problems with process- and outcome-based feedback","publication_year":2022,"publication_date":"2022-11-25","ids":{"openalex":"https://openalex.org/W4310290453","doi":"https://doi.org/10.48550/arxiv.2211.14275"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2211.14275","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.14275","pdf_url":"https://arxiv.org/pdf/2211.14275","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2211.14275","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059226057","display_name":"Jonathan Uesato","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Uesato, Jonathan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026189313","display_name":"Nate Kushman","orcid":"https://orcid.org/0000-0002-8284-210X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kushman, Nate","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082761102","display_name":"Ramana Kumar","orcid":"https://orcid.org/0000-0002-2319-1933"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kumar, Ramana","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031035504","display_name":"Francis Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Francis","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065489996","display_name":"Noah Siegel","orcid":"https://orcid.org/0000-0002-5746-117X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siegel, Noah","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028677586","display_name":"Lisa Wang","orcid":"https://orcid.org/0000-0001-9726-0383"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lisa","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009239144","display_name":"Antonia Creswell","orcid":"https://orcid.org/0000-0003-1037-9395"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Creswell, Antonia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029611587","display_name":"Geoffrey Irving","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Irving, Geoffrey","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5018830387","display_name":"Irina Higgins","orcid":"https://orcid.org/0000-0002-1890-2091"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Higgins, Irina","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5059226057"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":21,"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":0.9986000061035156,"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":0.9986000061035156,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9955999851226807,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.982200026512146,"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/outcome","display_name":"Outcome (game theory)","score":0.786843478679657},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.7259598970413208},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7159568667411804},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6542098522186279},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5360982418060303},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5049458146095276},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3725685179233551},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3601503372192383},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15432694554328918},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.12638741731643677},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07793107628822327}],"concepts":[{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.786843478679657},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.7259598970413208},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7159568667411804},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6542098522186279},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5360982418060303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5049458146095276},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3725685179233551},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3601503372192383},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15432694554328918},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.12638741731643677},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07793107628822327},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2211.14275","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.14275","pdf_url":"https://arxiv.org/pdf/2211.14275","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2211.14275","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2211.14275","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":"pmh:oai:arXiv.org:2211.14275","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.14275","pdf_url":"https://arxiv.org/pdf/2211.14275","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8799999952316284,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2978999882","https://openalex.org/W3141031773","https://openalex.org/W1595686156","https://openalex.org/W2181392282","https://openalex.org/W2119369480","https://openalex.org/W2153369162","https://openalex.org/W148937441","https://openalex.org/W4367046737","https://openalex.org/W2104122207","https://openalex.org/W2296205523"],"abstract_inverted_index":{"Recent":[0],"work":[1],"has":[2],"shown":[3],"that":[4,103,135],"asking":[5],"language":[6,98],"models":[7,134],"to":[8,71,125],"generate":[9],"reasoning":[10,16,46,65,119,157],"steps":[11,120],"improves":[12],"performance":[13],"on":[14,95],"many":[15,77],"tasks.":[17],"When":[18],"moving":[19],"beyond":[20],"prompting,":[21],"this":[22],"raises":[23],"the":[24,37,45,85,143],"question":[25],"of":[26],"how":[27],"we":[28,121,141],"should":[29],"supervise":[30,36,44],"such":[31,80],"models:":[32],"outcome-based":[33,92,105],"approaches":[34,42,52,93],"which":[35,43,67],"final":[38],"result,":[39],"or":[40,129],"process-based":[41,127,137],"process":[47],"itself?":[48],"Differences":[49],"between":[50,89],"these":[51],"might":[53],"naturally":[54],"be":[55,69],"expected":[56],"not":[57],"just":[58],"in":[59,64,76],"final-answer":[60,109,151],"errors":[61],"but":[62],"also":[63],"errors,":[66],"can":[68],"difficult":[70],"detect":[72],"and":[73,91,153],"are":[74],"problematic":[75],"real-world":[78],"domains":[79],"as":[81],"education.":[82],"We":[83,101],"run":[84],"first":[86],"comprehensive":[87],"comparison":[88],"process-":[90],"trained":[94],"a":[96],"natural":[97],"task,":[99],"GSM8K.":[100],"find":[102,122],"pure":[104],"supervision":[106,128,130],"produces":[107],"similar":[108],"error":[110,152,158],"rates":[111],"with":[112],"less":[113],"label":[114],"supervision.":[115],"However,":[116],"for":[117],"correct":[118],"it":[123],"necessary":[124],"use":[126],"from":[131,147],"learned":[132],"reward":[133],"emulate":[136],"feedback.":[138],"In":[139],"total,":[140],"improve":[142],"previous":[144],"best":[145],"results":[146],"16.8%":[148],"$\\to$":[149,155],"12.7%":[150],"14.0%":[154],"3.4%":[156],"among":[159],"final-answer-correct":[160],"solutions.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5}],"updated_date":"2026-02-25T08:12:03.925757","created_date":"2025-10-10T00:00:00"}
