{"id":"https://openalex.org/W7166879708","doi":"https://doi.org/10.18653/v1/2026.findings-acl.134","title":"From Coarse to Fine: Benchmarking and Reward Modeling for Writing-Centric Generation Tasks","display_name":"From Coarse to Fine: Benchmarking and Reward Modeling for Writing-Centric Generation Tasks","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166879708","doi":"https://doi.org/10.18653/v1/2026.findings-acl.134"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.134","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.134","pdf_url":"https://aclanthology.org/2026.findings-acl.134.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.134.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122913726","display_name":"Qingyu Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyu Ren","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science , College of Computer Science and Artificial Intelligence , Fudan University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science , College of Computer Science and Artificial Intelligence , Fudan University ,","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081439632","display_name":"Tianjun Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianjun Pan","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science , College of Computer Science and Artificial Intelligence , Fudan University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science , College of Computer Science and Artificial Intelligence , Fudan University ,","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039782834","display_name":"Xingzhou Chen","orcid":"https://orcid.org/0000-0003-1631-5202"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingzhou Chen","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science , College of Computer Science and Artificial Intelligence , Fudan University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science , College of Computer Science and Artificial Intelligence , Fudan University ,","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139724042","display_name":"Xuhong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuhong Wang","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.96827042,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2796","last_page":"2810"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12070","display_name":"Writing and Handwriting Education","score":0.7907999753952026,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12070","display_name":"Writing and Handwriting Education","score":0.7907999753952026,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.010999999940395355,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10636","display_name":"Innovative Teaching and Learning Methods","score":0.010900000110268593,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5282999873161316},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.3546000123023987},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2667999863624573},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.2605000138282776},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.24969999492168427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6383000016212463},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5282999873161316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3573000133037567},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2976999878883362},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28949999809265137},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.24969999492168427},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2493000030517578}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.134","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.134","pdf_url":"https://aclanthology.org/2026.findings-acl.134.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.134","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.134","pdf_url":"https://aclanthology.org/2026.findings-acl.134.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7059547901153564,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166879708.pdf","grobid_xml":"https://content.openalex.org/works/W7166879708.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2,25,71,97,132],"have":[3],"achieved":[4],"remarkable":[5],"progress":[6],"in":[7],"text":[8],"generation":[9],"but":[10],"still":[11],"struggle":[12],"with":[13],"generative":[14],"writing":[15,23,69,95,138],"tasks.In":[16],"terms":[17,38],"of":[18,35,39,82,94,105],"evaluation,":[19],"existing":[20,41],"benchmarks":[21,139],"evaluate":[22],"reward":[24,51,56,70,96,107,126],"coarsely":[26],"and":[27,72,88,109,114,140],"fail":[28],"to":[29],"measure":[30],"performance":[31],"from":[32],"the":[33,100,103,106],"perspective":[34],"specific":[36],"requirements.In":[37],"training,":[40],"training":[42,77],"methods":[43],"either":[44],"use":[45],"LLM-as-a-judge":[46],"approaches":[47],"or":[48],"train":[49],"coarse-grained":[50],"models,":[52],"lacking":[53],"fine-grained":[54,64,74],"requirement-adherence":[55],"modeling.To":[57],"address":[58],"these":[59],"issues,":[60],"we":[61],"propose":[62],"a":[63,73],"evaluation":[65,80,93],"pipeline":[66],"WEval":[67,83],"for":[68,123],"reinforcement":[75],"learning":[76],"framework":[78],"WRL.The":[79],"data":[81],"covers":[84],"multiple":[85],"task":[86],"categories":[87],"requirement":[89],"types,":[90],"enabling":[91],"systematic":[92],"by":[98,117],"measuring":[99],"correlation":[101],"between":[102],"rankings":[104],"model":[108,127],"gold":[110],"rankings.WRL":[111],"constructs":[112],"positive":[113],"negative":[115],"samples":[116],"selectively":[118],"dropping":[119],"instruction":[120],"requirements,":[121],"allowing":[122],"more":[124],"precise":[125],"training.Experiments":[128],"show":[129],"that":[130],"our":[131],"achieve":[133],"substantial":[134],"improvements":[135],"across":[136],"various":[137],"exhibit":[141],"strong":[142],"generalization.":[143]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-07-02T00:00:00"}
