{"id":"https://openalex.org/W4416284950","doi":"https://doi.org/10.48550/arxiv.2507.07544","title":"Position: We Need An Algorithmic Understanding of Generative AI","display_name":"Position: We Need An Algorithmic Understanding of Generative AI","publication_year":2025,"publication_date":"2025-07-10","ids":{"openalex":"https://openalex.org/W4416284950","doi":"https://doi.org/10.48550/arxiv.2507.07544"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2507.07544","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.07544","pdf_url":"https://arxiv.org/pdf/2507.07544","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":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.07544","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011718238","display_name":"Oliver Eberle","orcid":"https://orcid.org/0000-0002-6967-9950"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eberle, Oliver","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037635590","display_name":"Thomas McGee","orcid":"https://orcid.org/0000-0001-9192-4169"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McGee, Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082916041","display_name":"Hamza Giaffar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Giaffar, Hamza","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079675053","display_name":"Taylor W. Webb","orcid":"https://orcid.org/0000-0002-1335-3177"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Webb, Taylor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5059293348","display_name":"Ida Momennejad","orcid":"https://orcid.org/0000-0003-0830-3973"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Momennejad, Ida","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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.225600004196167,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.225600004196167,"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/T11883","display_name":"Embodied and Extended Cognition","score":0.061799999326467514,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.05790000036358833,"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/generative-grammar","display_name":"Generative grammar","score":0.6103000044822693},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5878999829292297},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.5378000140190125},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.3319999873638153},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.2919999957084656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6471999883651733},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6103000044822693},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5878999829292297},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.5378000140190125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49900001287460327},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.3698999881744385},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.361299991607666},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35589998960494995},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3082999885082245},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C78780964","wikidata":"https://www.wikidata.org/wiki/Q7233193","display_name":"Position paper","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2874999940395355},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.275299996137619}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2507.07544","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.07544","pdf_url":"https://arxiv.org/pdf/2507.07544","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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2507.07544","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.07544","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.07544","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.07544","pdf_url":"https://arxiv.org/pdf/2507.07544","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"What":[0],"algorithms":[1,49],"do":[2],"LLMs":[3,51,128],"actually":[4,129],"learn":[5,52],"and":[6,30,53,66,69,82,107,119,177,187],"use":[7],"to":[8,57,73,135,154,171],"solve":[9,74,130],"problems?":[10],"Studies":[11],"addressing":[12],"this":[13,87],"question":[14],"are":[15,20],"sparse,":[16],"as":[17,180,182],"research":[18,46],"priorities":[19],"focused":[21],"on":[22,90],"improving":[23,178],"performance":[24,164],"through":[25],"scale,":[26],"leaving":[27],"a":[28,42,83,142,152],"theoretical":[29],"empirical":[31],"gap":[32],"in":[33,62,168],"understanding":[34,144],"emergent":[35,91],"algorithms.":[36,93],"This":[37,166],"position":[38],"paper":[39],"proposes":[40],"AlgEval:":[41],"framework":[43],"for":[44,175,185],"systematic":[45,124],"into":[47],"the":[48,99,139,160],"that":[50],"use.":[54],"AlgEval":[55],"aims":[56],"uncover":[58],"algorithmic":[59,71,149],"primitives,":[60],"reflected":[61],"latent":[63],"representations,":[64],"attention,":[65],"inference-time":[67],"compute,":[68],"their":[70],"composition":[72],"task-specific":[75],"problems.":[76],"We":[77],"highlight":[78],"potential":[79],"methodological":[80],"paths":[81],"case":[84,95],"study":[85,96],"toward":[86,141],"goal,":[88],"focusing":[89],"search":[92],"Our":[94],"illustrates":[97],"both":[98],"formation":[100],"of":[101,110,116,126,145,159],"top-down":[102],"hypotheses":[103,112],"about":[104],"candidate":[105],"algorithms,":[106],"bottom-up":[108],"tests":[109],"these":[111],"via":[113],"circuit-level":[114],"analysis":[115],"attention":[117],"patterns":[118],"hidden":[120],"states.":[121],"The":[122],"rigorous,":[123],"evaluation":[125],"how":[127],"tasks":[131],"provides":[132],"an":[133],"alternative":[134],"resource-intensive":[136],"scaling,":[137],"reorienting":[138],"field":[140],"principled":[143],"underlying":[146],"computations.":[147],"Such":[148],"explanations":[150],"offer":[151],"pathway":[153],"human-understandable":[155],"interpretability,":[156],"enabling":[157],"comprehension":[158],"model's":[161],"internal":[162],"reasoning":[163],"measures.":[165],"can":[167],"turn":[169],"lead":[170],"more":[172],"sample-efficient":[173],"methods":[174],"training":[176],"performance,":[179],"well":[181],"novel":[183],"architectures":[184],"end-to-end":[186],"multi-agent":[188],"systems.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
