{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:BT3Q3BY7WE7PTIE7GZGFD43BNV","short_pith_number":"pith:BT3Q3BY7","canonical_record":{"source":{"id":"2507.09823","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2025-07-13T23:07:45Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"aeb54191fda8f298f975b809b238db3b301837afa3cc0e8acdacfbe46e419984","abstract_canon_sha256":"aa88f9c3d4e3e32c00f56dafa043880471bc1824bdf6d8fae783b0969fa0f35c"},"schema_version":"1.0"},"canonical_sha256":"0cf70d871fb13ef9a09f364c51f3616d417783ec52ffd728585fca927f2afe67","source":{"kind":"arxiv","id":"2507.09823","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.09823","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"arxiv_version","alias_value":"2507.09823v2","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.09823","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"pith_short_12","alias_value":"BT3Q3BY7WE7P","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"pith_short_16","alias_value":"BT3Q3BY7WE7PTIE7","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"pith_short_8","alias_value":"BT3Q3BY7","created_at":"2026-07-05T12:01:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:BT3Q3BY7WE7PTIE7GZGFD43BNV","target":"record","payload":{"canonical_record":{"source":{"id":"2507.09823","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2025-07-13T23:07:45Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"aeb54191fda8f298f975b809b238db3b301837afa3cc0e8acdacfbe46e419984","abstract_canon_sha256":"aa88f9c3d4e3e32c00f56dafa043880471bc1824bdf6d8fae783b0969fa0f35c"},"schema_version":"1.0"},"canonical_sha256":"0cf70d871fb13ef9a09f364c51f3616d417783ec52ffd728585fca927f2afe67","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:01:45.936255Z","signature_b64":"4uM7wa/DDyzlbUtRWDuVKQRchytM1EGKwCaHXHZj92PHQWNYAdhWK2g63upiczh3wOYK62uUpAHtGOCuo22hCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0cf70d871fb13ef9a09f364c51f3616d417783ec52ffd728585fca927f2afe67","last_reissued_at":"2026-07-05T12:01:45.935727Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:01:45.935727Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.09823","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T12:01:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9WxZmEktJTRdtiZHF9HltydkWP7Q17oY1xl2G9ExebnzDk4jBgozt3jH0K5l882IwGfH7pwHrMODjpgoDdLWBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T04:53:39.316503Z"},"content_sha256":"e1be83c96d0dad3321938cd97dab1976dd7c54a004eb2e02ab721c2e6c762f8f","schema_version":"1.0","event_id":"sha256:e1be83c96d0dad3321938cd97dab1976dd7c54a004eb2e02ab721c2e6c762f8f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:BT3Q3BY7WE7PTIE7GZGFD43BNV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Nesterov Finds GRAAL: Optimal and Adaptive Gradient Method for Convex Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"math.OC","authors_text":"Dmitry Kovalev, Ekaterina Borodich","submitted_at":"2025-07-13T23:07:45Z","abstract_excerpt":"In this paper, we focus on the problem of minimizing a continuously differentiable convex objective function, $\\min_x f(x)$. Recently, Malitsky (2020); Alacaoglu et al.(2023) developed an adaptive first-order method, GRAAL. This algorithm computes stepsizes by estimating the local curvature of the objective function without any line search procedures or hyperparameter tuning, and attains the standard iteration complexity $\\mathcal{O}(L\\lVert x_0-x^*\\rVert^2/\\epsilon)$ of fixed-stepsize gradient descent for $L$-smooth functions. However, a natural question arises: is it possible to accelerate t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.09823","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/2507.09823/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T12:01:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"biKawmUONZRF2daOUJfPSSHob4pAVhR/NtaToGs8IkqIkiCQd0XueL2SKA1C5GKzumHWk9VFCa0wW/ucN4H5Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T04:53:39.317003Z"},"content_sha256":"a3d5dccf6daaf822e1492632ad581f7ddb8590b83c6a3c7fd02d9be3e4141190","schema_version":"1.0","event_id":"sha256:a3d5dccf6daaf822e1492632ad581f7ddb8590b83c6a3c7fd02d9be3e4141190"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BT3Q3BY7WE7PTIE7GZGFD43BNV/bundle.json","state_url":"https://pith.science/pith/BT3Q3BY7WE7PTIE7GZGFD43BNV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BT3Q3BY7WE7PTIE7GZGFD43BNV/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T04:53:39Z","links":{"resolver":"https://pith.science/pith/BT3Q3BY7WE7PTIE7GZGFD43BNV","bundle":"https://pith.science/pith/BT3Q3BY7WE7PTIE7GZGFD43BNV/bundle.json","state":"https://pith.science/pith/BT3Q3BY7WE7PTIE7GZGFD43BNV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BT3Q3BY7WE7PTIE7GZGFD43BNV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:BT3Q3BY7WE7PTIE7GZGFD43BNV","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"aa88f9c3d4e3e32c00f56dafa043880471bc1824bdf6d8fae783b0969fa0f35c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2025-07-13T23:07:45Z","title_canon_sha256":"aeb54191fda8f298f975b809b238db3b301837afa3cc0e8acdacfbe46e419984"},"schema_version":"1.0","source":{"id":"2507.09823","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.09823","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"arxiv_version","alias_value":"2507.09823v2","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.09823","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"pith_short_12","alias_value":"BT3Q3BY7WE7P","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"pith_short_16","alias_value":"BT3Q3BY7WE7PTIE7","created_at":"2026-07-05T12:01:45Z"},{"alias_kind":"pith_short_8","alias_value":"BT3Q3BY7","created_at":"2026-07-05T12:01:45Z"}],"graph_snapshots":[{"event_id":"sha256:a3d5dccf6daaf822e1492632ad581f7ddb8590b83c6a3c7fd02d9be3e4141190","target":"graph","created_at":"2026-07-05T12:01:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2507.09823/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we focus on the problem of minimizing a continuously differentiable convex objective function, $\\min_x f(x)$. Recently, Malitsky (2020); Alacaoglu et al.(2023) developed an adaptive first-order method, GRAAL. This algorithm computes stepsizes by estimating the local curvature of the objective function without any line search procedures or hyperparameter tuning, and attains the standard iteration complexity $\\mathcal{O}(L\\lVert x_0-x^*\\rVert^2/\\epsilon)$ of fixed-stepsize gradient descent for $L$-smooth functions. However, a natural question arises: is it possible to accelerate t","authors_text":"Dmitry Kovalev, Ekaterina Borodich","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2025-07-13T23:07:45Z","title":"Nesterov Finds GRAAL: Optimal and Adaptive Gradient Method for Convex Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.09823","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:e1be83c96d0dad3321938cd97dab1976dd7c54a004eb2e02ab721c2e6c762f8f","target":"record","created_at":"2026-07-05T12:01:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"aa88f9c3d4e3e32c00f56dafa043880471bc1824bdf6d8fae783b0969fa0f35c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2025-07-13T23:07:45Z","title_canon_sha256":"aeb54191fda8f298f975b809b238db3b301837afa3cc0e8acdacfbe46e419984"},"schema_version":"1.0","source":{"id":"2507.09823","kind":"arxiv","version":2}},"canonical_sha256":"0cf70d871fb13ef9a09f364c51f3616d417783ec52ffd728585fca927f2afe67","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0cf70d871fb13ef9a09f364c51f3616d417783ec52ffd728585fca927f2afe67","first_computed_at":"2026-07-05T12:01:45.935727Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:01:45.935727Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4uM7wa/DDyzlbUtRWDuVKQRchytM1EGKwCaHXHZj92PHQWNYAdhWK2g63upiczh3wOYK62uUpAHtGOCuo22hCg==","signature_status":"signed_v1","signed_at":"2026-07-05T12:01:45.936255Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.09823","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e1be83c96d0dad3321938cd97dab1976dd7c54a004eb2e02ab721c2e6c762f8f","sha256:a3d5dccf6daaf822e1492632ad581f7ddb8590b83c6a3c7fd02d9be3e4141190"],"state_sha256":"fff71cf00f507d01abeafdd2019576255f54ef566f32a96de00df9c2a35ea20d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sW8fO8dZoSP4x3hh7NfzS5yKHkHfe1VbXgkmS5x1aiH1gFwVR5Dh+MKf8n4M9hYhnH/L39bOWT3Rd5G8Cj2WBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T04:53:39.321554Z","bundle_sha256":"3a27bcc91e66e8777d6042efd2d98090af6c3abfd5b6458521f9e1506ff0d625"}}