{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:WBDGKQUAIA6FBYEGRNGDNB2BZC","short_pith_number":"pith:WBDGKQUA","schema_version":"1.0","canonical_sha256":"b046654280403c50e0868b4c368741c89c3224061c1a955c61fe77e598092460","source":{"kind":"arxiv","id":"2505.22158","version":1},"attestation_state":"computed","paper":{"title":"The informativeness of the gradient revisited","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Rustem Takhanov","submitted_at":"2025-05-28T09:23:37Z","abstract_excerpt":"In the past decade gradient-based deep learning has revolutionized several applications. However, this rapid advancement has highlighted the need for a deeper theoretical understanding of its limitations. Research has shown that, in many practical learning tasks, the information contained in the gradient is so minimal that gradient-based methods require an exceedingly large number of iterations to achieve success. The informativeness of the gradient is typically measured by its variance with respect to the random selection of a target function from a hypothesis class.\n  We use this framework a"},"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":"2505.22158","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-28T09:23:37Z","cross_cats_sorted":[],"title_canon_sha256":"5181f3dc01eaedb40ff5c9d8eacb44eb021c533a6ecd740e5cc52e33ce9c0c68","abstract_canon_sha256":"5e33bbc4d8d6af632d7367053550786ddb289cdd0468f001a8211fff809aad17"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:11:47.742514Z","signature_b64":"dEa+pyfqCPZWKK3Iy5ZTy4IFuw1yYMcTZE+5uy0FaprkXnH8qgU+psuGWIRQKCbRKnVSVbt0BPI25EZPwCEnCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b046654280403c50e0868b4c368741c89c3224061c1a955c61fe77e598092460","last_reissued_at":"2026-07-05T11:11:47.741919Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:11:47.741919Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The informativeness of the gradient revisited","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Rustem Takhanov","submitted_at":"2025-05-28T09:23:37Z","abstract_excerpt":"In the past decade gradient-based deep learning has revolutionized several applications. However, this rapid advancement has highlighted the need for a deeper theoretical understanding of its limitations. Research has shown that, in many practical learning tasks, the information contained in the gradient is so minimal that gradient-based methods require an exceedingly large number of iterations to achieve success. The informativeness of the gradient is typically measured by its variance with respect to the random selection of a target function from a hypothesis class.\n  We use this framework a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.22158","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/2505.22158/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":"2505.22158","created_at":"2026-07-05T11:11:47.742001+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.22158v1","created_at":"2026-07-05T11:11:47.742001+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.22158","created_at":"2026-07-05T11:11:47.742001+00:00"},{"alias_kind":"pith_short_12","alias_value":"WBDGKQUAIA6F","created_at":"2026-07-05T11:11:47.742001+00:00"},{"alias_kind":"pith_short_16","alias_value":"WBDGKQUAIA6FBYEG","created_at":"2026-07-05T11:11:47.742001+00:00"},{"alias_kind":"pith_short_8","alias_value":"WBDGKQUA","created_at":"2026-07-05T11:11:47.742001+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/WBDGKQUAIA6FBYEGRNGDNB2BZC","json":"https://pith.science/pith/WBDGKQUAIA6FBYEGRNGDNB2BZC.json","graph_json":"https://pith.science/api/pith-number/WBDGKQUAIA6FBYEGRNGDNB2BZC/graph.json","events_json":"https://pith.science/api/pith-number/WBDGKQUAIA6FBYEGRNGDNB2BZC/events.json","paper":"https://pith.science/paper/WBDGKQUA"},"agent_actions":{"view_html":"https://pith.science/pith/WBDGKQUAIA6FBYEGRNGDNB2BZC","download_json":"https://pith.science/pith/WBDGKQUAIA6FBYEGRNGDNB2BZC.json","view_paper":"https://pith.science/paper/WBDGKQUA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.22158&json=true","fetch_graph":"https://pith.science/api/pith-number/WBDGKQUAIA6FBYEGRNGDNB2BZC/graph.json","fetch_events":"https://pith.science/api/pith-number/WBDGKQUAIA6FBYEGRNGDNB2BZC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WBDGKQUAIA6FBYEGRNGDNB2BZC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WBDGKQUAIA6FBYEGRNGDNB2BZC/action/storage_attestation","attest_author":"https://pith.science/pith/WBDGKQUAIA6FBYEGRNGDNB2BZC/action/author_attestation","sign_citation":"https://pith.science/pith/WBDGKQUAIA6FBYEGRNGDNB2BZC/action/citation_signature","submit_replication":"https://pith.science/pith/WBDGKQUAIA6FBYEGRNGDNB2BZC/action/replication_record"}},"created_at":"2026-07-05T11:11:47.742001+00:00","updated_at":"2026-07-05T11:11:47.742001+00:00"}