{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:BAUYJYRK3J6534XKZYJMR344MJ","short_pith_number":"pith:BAUYJYRK","schema_version":"1.0","canonical_sha256":"082984e22ada7dddf2eace12c8ef9c6251fa3cc588711fb9b70d5b7127443cff","source":{"kind":"arxiv","id":"2605.19483","version":1},"attestation_state":"computed","paper":{"title":"Adynamical systems view of training generativemodels and the memorization phenomenon","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chiranjib Bhattacharya, Siva Athreya, Vivek S. Borkar","submitted_at":"2026-05-19T07:34:58Z","abstract_excerpt":"Using recent works of one of the authors (VSB) on collapse in generative models and two time scale dynamics in stochastic gradient descent in high dimensions, we give a system theoretic explanation of the memorization phenomenon in generative models. This relies purely on the dynamic aspects of the training phase. Specifically, we use a result of Austin [2016] to motivate a stylized model for the loss function for stochastic gradient descent (SGD) wherein the loss function has a strong dependence on some variables and weak dependence on the rest in a precise sense. This naturally leads to two "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.19483","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T07:34:58Z","cross_cats_sorted":[],"title_canon_sha256":"5701b345a418de83245c4326d0c6a6b774f3111606849b8959519f38a1ada6eb","abstract_canon_sha256":"08b68e3b021fd749041f390022f66dc4b392d14bd22b276774c5c2bbdd50a9b5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T01:05:47.978885Z","signature_b64":"VlPWdKg4AM6K5t7MaiuInrNHvzpTUGs+WB5U2I2agSWCyymlelglG/WDf9c5FbrEoR7kY6vuWBcD+akAlE1nDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"082984e22ada7dddf2eace12c8ef9c6251fa3cc588711fb9b70d5b7127443cff","last_reissued_at":"2026-05-20T01:05:47.978210Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T01:05:47.978210Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adynamical systems view of training generativemodels and the memorization phenomenon","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chiranjib Bhattacharya, Siva Athreya, Vivek S. Borkar","submitted_at":"2026-05-19T07:34:58Z","abstract_excerpt":"Using recent works of one of the authors (VSB) on collapse in generative models and two time scale dynamics in stochastic gradient descent in high dimensions, we give a system theoretic explanation of the memorization phenomenon in generative models. This relies purely on the dynamic aspects of the training phase. Specifically, we use a result of Austin [2016] to motivate a stylized model for the loss function for stochastic gradient descent (SGD) wherein the loss function has a strong dependence on some variables and weak dependence on the rest in a precise sense. This naturally leads to two "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19483","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.19483/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.19483","created_at":"2026-05-20T01:05:47.978300+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.19483v1","created_at":"2026-05-20T01:05:47.978300+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19483","created_at":"2026-05-20T01:05:47.978300+00:00"},{"alias_kind":"pith_short_12","alias_value":"BAUYJYRK3J65","created_at":"2026-05-20T01:05:47.978300+00:00"},{"alias_kind":"pith_short_16","alias_value":"BAUYJYRK3J6534XK","created_at":"2026-05-20T01:05:47.978300+00:00"},{"alias_kind":"pith_short_8","alias_value":"BAUYJYRK","created_at":"2026-05-20T01:05:47.978300+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BAUYJYRK3J6534XKZYJMR344MJ","json":"https://pith.science/pith/BAUYJYRK3J6534XKZYJMR344MJ.json","graph_json":"https://pith.science/api/pith-number/BAUYJYRK3J6534XKZYJMR344MJ/graph.json","events_json":"https://pith.science/api/pith-number/BAUYJYRK3J6534XKZYJMR344MJ/events.json","paper":"https://pith.science/paper/BAUYJYRK"},"agent_actions":{"view_html":"https://pith.science/pith/BAUYJYRK3J6534XKZYJMR344MJ","download_json":"https://pith.science/pith/BAUYJYRK3J6534XKZYJMR344MJ.json","view_paper":"https://pith.science/paper/BAUYJYRK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.19483&json=true","fetch_graph":"https://pith.science/api/pith-number/BAUYJYRK3J6534XKZYJMR344MJ/graph.json","fetch_events":"https://pith.science/api/pith-number/BAUYJYRK3J6534XKZYJMR344MJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BAUYJYRK3J6534XKZYJMR344MJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BAUYJYRK3J6534XKZYJMR344MJ/action/storage_attestation","attest_author":"https://pith.science/pith/BAUYJYRK3J6534XKZYJMR344MJ/action/author_attestation","sign_citation":"https://pith.science/pith/BAUYJYRK3J6534XKZYJMR344MJ/action/citation_signature","submit_replication":"https://pith.science/pith/BAUYJYRK3J6534XKZYJMR344MJ/action/replication_record"}},"created_at":"2026-05-20T01:05:47.978300+00:00","updated_at":"2026-05-20T01:05:47.978300+00:00"}