{"id":"https://openalex.org/W7161746107","doi":"https://doi.org/10.48550/arxiv.2605.17659","title":"Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes","display_name":"Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes","publication_year":2026,"publication_date":"2026-05-17","ids":{"openalex":"https://openalex.org/W7161746107","doi":"https://doi.org/10.48550/arxiv.2605.17659"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17659","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.17659","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055858527","display_name":"Egor Shvetsov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shvetsov, Egor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136466728","display_name":"Aleksandr Serkov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Serkov, Aleksandr","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136487438","display_name":"Shokorov Viacheslav","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Viacheslav, Shokorov","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136485107","display_name":"Redko Dmitry","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dmitry, Redko","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136475540","display_name":"Vladislav Goloshchapov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Goloshchapov, Vladislav","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5088950452","display_name":"Evgeny Burnaev","orcid":"https://orcid.org/0000-0001-8424-0690"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Burnaev, Evgeny","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.18449999392032623,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.18449999392032623,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.11919999867677689,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.11309999972581863,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.484499990940094},{"id":"https://openalex.org/keywords/activation-function","display_name":"Activation function","score":0.42260000109672546},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4108999967575073},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.2980000078678131},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2962000072002411}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.484499990940094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4837000072002411},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.42260000109672546},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4108999967575073},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.4002000093460083},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.382099986076355},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3183000087738037},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.30640000104904175},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C2776848632","wikidata":"https://www.wikidata.org/wiki/Q853463","display_name":"Clipping (morphology)","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.27090001106262207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.258899986743927},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.25839999318122864}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17659","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.17659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17659","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,73],"design":[1],"of":[2,157],"modern":[3],"neural":[4],"architectures":[5,85],"has":[6],"converged":[7],"through":[8],"incremental":[9],"empirical":[10],"choices,":[11],"yet":[12],"the":[13,33,51,114,154,168],"mechanisms":[14],"governing":[15],"their":[16],"training":[17],"dynamics":[18],"remain":[19],"only":[20],"partially":[21],"understood.":[22],"We":[23,43,112],"identify":[24,121],"and":[25,38,82,91,120,165],"analyze":[26],"a":[27,122,133],"negative":[28,68],"weight":[29,101],"drift":[30,74,102],"induced":[31],"by":[32],"interaction":[34],"between":[35],"standard":[36],"losses":[37],"positively":[39],"biased":[40],"activation":[41,93,104,128,143],"functions.":[42],"prove":[44],"that":[45],"under":[46],"MSE":[47],"or":[48],"cross-entropy":[49],"loss,":[50],"gradient":[52],"with":[53,99],"respect":[54],"to":[55,77,108],"positive":[56],"pre-activations":[57],"is":[58,75,175],"non-negative":[59],"in":[60,110,137,145],"expectation":[61],"at":[62,177],"initialization,":[63],"driving":[64],"downstream":[65],"weights":[66],"toward":[67],"values":[69],"during":[70],"early":[71],"training.":[72],"intrinsic":[76],"optimization":[78],"rather":[79],"than":[80],"data,":[81],"persists":[83],"across":[84,117],"(MLP,":[86],"ResNet,":[87],"ViT,":[88],"GPT-nano,":[89,138],"MP-SENe)":[90],"asymmetric":[92],"functions":[94],"(ReLU,":[95],"GELU,":[96],"SiLU).":[97],"Coupled":[98],"ReLU,":[100],"produces":[103],"sparsity":[105],"reaching":[106],"up":[107],"90\\%":[109],"GPT-nano.":[111,173],"characterize":[113],"sparsity-accuracy":[115],"tradeoff":[116],"79":[118],"configurations":[119],"sharp":[123],"accuracy":[124],"cliff":[125],"above":[126],"$\\sim$70\\%":[127],"sparsity.":[129],"While":[130],"ReLU$^2$":[131,160],"achieves":[132,167],"good":[134],"sparsity--accuracy":[135],"ratio":[136],"it":[139],"pathologically":[140],"amplifies":[141],"identified":[142],"spikes":[144],"intermediate":[146],"transformer":[147],"layers.":[148],"Clipping":[149],"resolves":[150],"this":[151],"while":[152],"preserving":[153],"representational":[155],"benefits":[156],"squaring:":[158],"clipped":[159],"outperforms":[161],"its":[162],"unclipped":[163],"version,":[164],"GELU$^2$":[166],"lowest":[169],"validation":[170],"loss":[171],"on":[172],"Code":[174],"available":[176],"https://github.com/On-Point-RND/BugOrFeature.":[178]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-20T00:00:00"}
