{"id":"https://openalex.org/W7166871960","doi":"https://doi.org/10.18653/v1/2026.findings-acl.296","title":"CogGen: A Cognitively Inspired Recursive Framework for Deep Research Report Generation","display_name":"CogGen: A Cognitively Inspired Recursive Framework for Deep Research Report Generation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166871960","doi":"https://doi.org/10.18653/v1/2026.findings-acl.296"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.296","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.296","pdf_url":"https://aclanthology.org/2026.findings-acl.296.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.296.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006893011","display_name":"Kuo Tian","orcid":"https://orcid.org/0000-0002-2581-6984"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuo Tian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139788910","display_name":"Pengfei Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pengfei Sun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139744620","display_name":"Zhen Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhen Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091087566","display_name":"Junran Ding","orcid":"https://orcid.org/0009-0002-0665-0736"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junran Ding","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5047817212","display_name":"Xinyu Dai","orcid":"https://orcid.org/0009-0003-7513-1507"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinyu Dai","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":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.86038408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5961","last_page":"5988"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.40799999237060547,"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":0.40799999237060547,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.11180000007152557,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.08259999752044678,"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/deep-learning","display_name":"Deep learning","score":0.4361000061035156},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.30219998955726624},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2922999858856201},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.2777999937534332},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.27070000767707825}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5954999923706055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5946999788284302},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2639000117778778},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.24320000410079956},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.23559999465942383}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.296","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.296","pdf_url":"https://aclanthology.org/2026.findings-acl.296.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.296","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.296","pdf_url":"https://aclanthology.org/2026.findings-acl.296.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":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166871960.pdf","grobid_xml":"https://content.openalex.org/works/W7166871960.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"autonomous":[1],"synthesis":[2],"of":[3],"deep":[4,58],"research":[5,59],"reports":[6,131],"represents":[7],"a":[8,52,62,89,105,112],"critical":[9],"frontier":[10],"for":[11,57],"Large":[12],"Language":[13],"Models":[14],"(LLMs),":[15],"demanding":[16],"sophisticated":[17],"information":[18],"orchestration":[19],"and":[20,41,47,74,110,137],"non-linear":[21],"narrative":[22],"logic.Current":[23],"approaches":[24],"rely":[25],"on":[26],"rigid":[27],"predefined":[28],"linear":[29],"workflows,":[30],"which":[31],"cause":[32],"error":[33],"accumulation,":[34],"preclude":[35],"global":[36,75],"restructuring":[37],"from":[38,115],"subsequent":[39],"insights,":[40],"ultimately":[42],"limit":[43],"in-depth":[44],"multimodal":[45,81],"fusion":[46],"report":[48,60],"quality.We":[49],"propose":[50],"CogGen,":[51],"Cognitively":[53],"inspired":[54],"recursive":[55],"framework":[56],"Generation.Leveraging":[61],"Hierarchical":[63],"Recursive":[64],"Architecture":[65],"to":[66,80,133],"simulate":[67],"cognitive":[68],"writing,":[69],"CogGen":[70,123],"enables":[71],"flexible":[72],"planning":[73],"restructuring.To":[76],"extend":[77],"this":[78],"recursivity":[79],"content,":[82],"we":[83],"introduce":[84],"Abstract":[85],"Visual":[86],"Representation":[87],"(AVR):":[88],"concise":[90],"intent-driven":[91],"language":[92],"that":[93],"iteratively":[94],"refines":[95],"visual-text":[96],"layouts":[97],"without":[98],"pixel-level":[99],"regeneration":[100],"overhead.We":[101],"further":[102],"present":[103],"CLEF,":[104],"Cognitive":[106],"Load":[107],"Evaluation":[108],"Framework,":[109],"curate":[111],"new":[113],"benchmark":[114],"Our":[116],"World":[117],"in":[118],"Data":[119],"(OWID).Extensive":[120],"experiments":[121],"show":[122],"achieves":[124],"state-of-the-art":[125],"results":[126],"among":[127],"opensource":[128],"systems,":[129],"generating":[130],"comparable":[132],"professional":[134],"analysts'":[135],"outputs":[136],"surpassing":[138],"Gemini":[139],"Deep":[140],"Research.":[141]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}