{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:DLDRIOY7NWDPZGGPK2KGYILO2A","short_pith_number":"pith:DLDRIOY7","schema_version":"1.0","canonical_sha256":"1ac7143b1f6d86fc98cf56946c216ed01c0b9b600df4a8da59faaca1fa431b3d","source":{"kind":"arxiv","id":"2412.20302","version":2},"attestation_state":"computed","paper":{"title":"EXAdam: The Power of Adaptive Cross-Moments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","math.OC"],"primary_cat":"cs.LG","authors_text":"Ahmed M. Adly","submitted_at":"2024-12-29T00:11:54Z","abstract_excerpt":"This paper introduces EXAdam ($\\textbf{EX}$tended $\\textbf{Adam}$), a novel optimization algorithm that builds upon the widely-used Adam optimizer. EXAdam incorporates two key enhancements: (1) new debiasing terms for improved moment estimation and (2) a gradient-based acceleration mechanism for increased responsiveness to the current loss landscape. These innovations work synergistically to address limitations of the original Adam algorithm, potentially offering improved convergence properties, enhanced ability to escape saddle points, and potentially greater robustness to hyperparameter choi"},"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":"2412.20302","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-29T00:11:54Z","cross_cats_sorted":["cs.AI","math.OC"],"title_canon_sha256":"8f80af4b7da0cbf93732f04a5551688a606d90fb335de6130f20195b450c85e9","abstract_canon_sha256":"74d56457b7c5090ebfe9bce55d4f958f105c620956523ff333f71aadd60f7e18"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:03:55.148560Z","signature_b64":"LuI1lfCGxtFM4Jy6I6MvXTIr+ipkVlq+ywDQy86w6DCKMxMok/fh8Obg6Ixsl2iqDaVMOz5ymXjmox4Mnz98Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1ac7143b1f6d86fc98cf56946c216ed01c0b9b600df4a8da59faaca1fa431b3d","last_reissued_at":"2026-07-05T11:03:55.148088Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:03:55.148088Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"EXAdam: The Power of Adaptive Cross-Moments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","math.OC"],"primary_cat":"cs.LG","authors_text":"Ahmed M. Adly","submitted_at":"2024-12-29T00:11:54Z","abstract_excerpt":"This paper introduces EXAdam ($\\textbf{EX}$tended $\\textbf{Adam}$), a novel optimization algorithm that builds upon the widely-used Adam optimizer. EXAdam incorporates two key enhancements: (1) new debiasing terms for improved moment estimation and (2) a gradient-based acceleration mechanism for increased responsiveness to the current loss landscape. These innovations work synergistically to address limitations of the original Adam algorithm, potentially offering improved convergence properties, enhanced ability to escape saddle points, and potentially greater robustness to hyperparameter choi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.20302","kind":"arxiv","version":2},"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/2412.20302/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":"2412.20302","created_at":"2026-07-05T11:03:55.148147+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.20302v2","created_at":"2026-07-05T11:03:55.148147+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.20302","created_at":"2026-07-05T11:03:55.148147+00:00"},{"alias_kind":"pith_short_12","alias_value":"DLDRIOY7NWDP","created_at":"2026-07-05T11:03:55.148147+00:00"},{"alias_kind":"pith_short_16","alias_value":"DLDRIOY7NWDPZGGP","created_at":"2026-07-05T11:03:55.148147+00:00"},{"alias_kind":"pith_short_8","alias_value":"DLDRIOY7","created_at":"2026-07-05T11:03:55.148147+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/DLDRIOY7NWDPZGGPK2KGYILO2A","json":"https://pith.science/pith/DLDRIOY7NWDPZGGPK2KGYILO2A.json","graph_json":"https://pith.science/api/pith-number/DLDRIOY7NWDPZGGPK2KGYILO2A/graph.json","events_json":"https://pith.science/api/pith-number/DLDRIOY7NWDPZGGPK2KGYILO2A/events.json","paper":"https://pith.science/paper/DLDRIOY7"},"agent_actions":{"view_html":"https://pith.science/pith/DLDRIOY7NWDPZGGPK2KGYILO2A","download_json":"https://pith.science/pith/DLDRIOY7NWDPZGGPK2KGYILO2A.json","view_paper":"https://pith.science/paper/DLDRIOY7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.20302&json=true","fetch_graph":"https://pith.science/api/pith-number/DLDRIOY7NWDPZGGPK2KGYILO2A/graph.json","fetch_events":"https://pith.science/api/pith-number/DLDRIOY7NWDPZGGPK2KGYILO2A/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DLDRIOY7NWDPZGGPK2KGYILO2A/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DLDRIOY7NWDPZGGPK2KGYILO2A/action/storage_attestation","attest_author":"https://pith.science/pith/DLDRIOY7NWDPZGGPK2KGYILO2A/action/author_attestation","sign_citation":"https://pith.science/pith/DLDRIOY7NWDPZGGPK2KGYILO2A/action/citation_signature","submit_replication":"https://pith.science/pith/DLDRIOY7NWDPZGGPK2KGYILO2A/action/replication_record"}},"created_at":"2026-07-05T11:03:55.148147+00:00","updated_at":"2026-07-05T11:03:55.148147+00:00"}