{"id":"https://openalex.org/W4401201608","doi":"https://doi.org/10.48550/arxiv.2407.19346","title":"Polynomial Regression as a Task for Understanding In-context Learning Through Finetuning and Alignment","display_name":"Polynomial Regression as a Task for Understanding In-context Learning Through Finetuning and Alignment","publication_year":2024,"publication_date":"2024-07-27","ids":{"openalex":"https://openalex.org/W4401201608","doi":"https://doi.org/10.48550/arxiv.2407.19346"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2407.19346","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.19346","pdf_url":"https://arxiv.org/pdf/2407.19346","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2407.19346","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106018507","display_name":"Max Wilcoxson","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wilcoxson, Max","raw_affiliation_strings":["EECS , University of California , Berkeley , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS , University of California , Berkeley , USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106113019","display_name":"Morten Svendg\u00e5rd","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Svendg\u00e5rd, Morten","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087180852","display_name":"Ria Doshi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Doshi, Ria","raw_affiliation_strings":["EECS , University of California , Berkeley , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS , University of California , Berkeley , USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Davis, Dylan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Davis, Dylan","raw_affiliation_strings":["EECS , University of California , Berkeley , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS , University of California , Berkeley , USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093567581","display_name":"Reya Vir","orcid":"https://orcid.org/0009-0003-3117-5655","observed_orcids":["https://orcid.org/0009-0003-3117-5655"]},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vir, Reya","raw_affiliation_strings":["EECS , University of California , Berkeley , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS , University of California , Berkeley , USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079317491","display_name":"Anant Sahai","orcid":"https://orcid.org/0000-0001-9263-7719","observed_orcids":["https://orcid.org/0000-0001-9263-7719"]},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sahai, Anant","raw_affiliation_strings":["EECS , University of California , Berkeley , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS , University of California , Berkeley , USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.6157000064849854,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.6157000064849854,"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/T10028","display_name":"Topic Modeling","score":0.3197999894618988,"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":0.012600000016391277,"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/in-context-learning","display_name":"in-context learning","score":0.9850000143051147},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"polynomial regression","score":0.8740000128746033},{"id":"https://openalex.org/keywords/prompting","display_name":"prompting","score":0.6579999923706055},{"id":"https://openalex.org/keywords/alignment","display_name":"alignment","score":0.621999979019165},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.7329999804496765},{"id":"https://openalex.org/keywords/transformer","display_name":"transformer models","score":0.6240000128746033},{"id":"https://openalex.org/keywords/fine-tuning","display_name":"fine-tuning","score":0.6869999766349792}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6546972393989563},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5863412618637085},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.545341968536377},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5450028777122498},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3892694413661957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3320425748825073},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.247697651386261},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.10257008671760559},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1006927490234375},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2407.19346","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.19346","pdf_url":"https://arxiv.org/pdf/2407.19346","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2407.19346","doi":"https://doi.org/10.48550/arxiv.2407.19346","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2407.19346","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,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2407.19346","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.19346","pdf_url":"https://arxiv.org/pdf/2407.19346","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401201608.pdf","grobid_xml":"https://content.openalex.org/works/W4401201608.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W3211323961"],"related_works":["https://openalex.org/W7133240241","https://openalex.org/W7160510650","https://openalex.org/W4377864715","https://openalex.org/W4415796687","https://openalex.org/W4412888595","https://openalex.org/W4415796768","https://openalex.org/W4389518997","https://openalex.org/W4413855556","https://openalex.org/W4414694875","https://openalex.org/W4401043027"],"abstract_inverted_index":{"Simple":[0],"function":[1,24,54],"classes":[2,25],"have":[3],"emerged":[4],"as":[5,52],"toy":[6],"problems":[7],"to":[8,35,61,69],"better":[9],"understand":[10,72],"in-context-learning":[11],"in":[12],"transformer-based":[13],"architectures":[14],"used":[15],"for":[16],"large":[17],"language":[18],"models.":[19],"But":[20],"previously":[21],"proposed":[22],"simple":[23],"like":[26,38],"linear":[27],"regression":[28,51],"or":[29],"multi-layer-perceptrons":[30],"lack":[31],"the":[32],"structure":[33],"required":[34],"explore":[36],"things":[37],"prompting":[39,63],"and":[40,64,71],"alignment":[41],"within":[42],"models":[43],"capable":[44],"of":[45],"in-context-learning.":[46],"We":[47],"propose":[48],"univariate":[49],"polynomial":[50],"a":[53],"class":[55],"that":[56],"is":[57,74],"just":[58],"rich":[59],"enough":[60],"study":[62],"alignment,":[65],"while":[66],"allowing":[67],"us":[68],"visualize":[70],"what":[73],"going":[75],"on":[76],"clearly.":[77]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2024-08-01T00:00:00"}