{"id":"https://openalex.org/W4412944918","doi":"https://doi.org/10.18653/v1/2025.acl-long.1041","title":"Neuron Empirical Gradient: Discovering and Quantifying Neurons\u2019 Global Linear Controllability","display_name":"Neuron Empirical Gradient: Discovering and Quantifying Neurons\u2019 Global Linear Controllability","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412944918","doi":"https://doi.org/10.18653/v1/2025.acl-long.1041"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-long.1041","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1041","pdf_url":"https://aclanthology.org/2025.acl-long.1041.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":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-long.1041.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037145565","display_name":"Wayne Xin Zhao","orcid":"https://orcid.org/0000-0002-8333-6196"},"institutions":[{"id":"https://openalex.org/I74640424","display_name":"Advanced Institute of Industrial Technology","ror":"https://ror.org/04f9apy08","country_code":"JP","type":"education","lineage":["https://openalex.org/I74640424"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xin Zhao","raw_affiliation_strings":["The University of Tokyo Institute of Industrial Science , The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo Institute of Industrial Science , The University of Tokyo","institution_ids":["https://openalex.org/I74640424","https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090583754","display_name":"Zehui Jiang","orcid":"https://orcid.org/0000-0002-6787-2300"},"institutions":[{"id":"https://openalex.org/I74640424","display_name":"Advanced Institute of Industrial Technology","ror":"https://ror.org/04f9apy08","country_code":"JP","type":"education","lineage":["https://openalex.org/I74640424"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zehui Jiang","raw_affiliation_strings":["The University of Tokyo Institute of Industrial Science , The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo Institute of Industrial Science , The University of Tokyo","institution_ids":["https://openalex.org/I74640424","https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036170005","display_name":"Naoki Yoshinaga","orcid":null},"institutions":[{"id":"https://openalex.org/I74640424","display_name":"Advanced Institute of Industrial Technology","ror":"https://ror.org/04f9apy08","country_code":"JP","type":"education","lineage":["https://openalex.org/I74640424"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoki Yoshinaga","raw_affiliation_strings":["The University of Tokyo Institute of Industrial Science , The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo Institute of Industrial Science , The University of Tokyo","institution_ids":["https://openalex.org/I74640424","https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.15950162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"21446","last_page":"21477"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9467999935150146,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9467999935150146,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9049000144004822,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/controllability","display_name":"Controllability","score":0.849444568157196},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5459384918212891},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3635643720626831},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27352285385131836},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.1483403444290161}],"concepts":[{"id":"https://openalex.org/C48209547","wikidata":"https://www.wikidata.org/wiki/Q1331104","display_name":"Controllability","level":2,"score":0.849444568157196},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5459384918212891},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3635643720626831},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27352285385131836},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.1483403444290161}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.acl-long.1041","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1041","pdf_url":"https://aclanthology.org/2025.acl-long.1041.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":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.acl-long.1041","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1041","pdf_url":"https://aclanthology.org/2025.acl-long.1041.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":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412944918.pdf","grobid_xml":"https://content.openalex.org/works/W4412944918.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2036697162","https://openalex.org/W2140812588","https://openalex.org/W2411113819","https://openalex.org/W2072887367","https://openalex.org/W2332386680","https://openalex.org/W2561315646","https://openalex.org/W2248621902"],"abstract_inverted_index":{"While":[0],"feed-forward":[1],"neurons":[2,18],"in":[3,33,72,88],"pre-trained":[4],"language":[5,96],"models":[6],"(PLMs)":[7],"can":[8],"encode":[9],"knowledge,":[10],"past":[11],"research":[12],"targeted":[13],"a":[14,39,52,107],"small":[15],"subset":[16],"of":[17,27,57,85,124],"that":[19,92],"heavily":[20],"influence":[21],"outputs.This":[22],"leaves":[23],"the":[24,64,121],"broader":[25],"role":[26],"neuron":[28,44,49,65,86,103],"activations":[29,45,73],"unclear,":[30],"limiting":[31],"progress":[32],"areas":[34],"like":[35],"knowledge":[36,53,110],"editing.We":[37],"uncover":[38],"global":[40],"linear":[41,59],"relationship":[42],"between":[43],"and":[46,131,134],"outputs":[47],"using":[48],"interventions":[50],"on":[51,105],"probing":[54],"dataset.The":[55],"gradient":[56,67],"this":[58],"relationship,":[60],"which":[61],"we":[62,79],"call":[63],"empirical":[66],"(NEG),":[68],"captures":[69,95],"how":[70],"changes":[71],"affect":[74],"predictions.To":[75],"compute":[76],"NEG":[77,93],"efficiently,":[78],"propose":[80],"NeurGrad,":[81],"enabling":[82],"large-scale":[83],"analysis":[84,119],"behavior":[87],"PLMs.We":[89],"also":[90],"show":[91],"effectively":[94],"skills":[97],"across":[98],"diverse":[99],"prompts":[100],"through":[101],"skill":[102,126],"probing.Experiments":[104],"MCEval8k,":[106],"multi-genre":[108],"multiple-choice":[109],"benchmark,":[111],"support":[112],"NEG's":[113],"ability":[114],"to":[115],"represent":[116],"model":[117],"knowledge.Further":[118],"highlights":[120],"key":[122],"properties":[123],"NEG-based":[125],"representation:":[127],"efficiency,":[128],"robustness,":[129],"flexibility,":[130],"interdependency.The":[132],"code":[133],"data":[135],"are":[136],"released.":[137]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}