{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:WP7L7NE3W7SGHXI4K2GWI4V36X","short_pith_number":"pith:WP7L7NE3","canonical_record":{"source":{"id":"2603.02970","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-03-03T13:24:36Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"9899751fc22b9a1e74460b6b420cc091af6f889920dbf10e71b63eb5e9f169a3","abstract_canon_sha256":"1eab336ab73b2c5fecbf62d8e01ba1206ef95a119dd0e08ca3a75b24e2a4c6be"},"schema_version":"1.0"},"canonical_sha256":"b3febfb49bb7e463dd1c568d6472bbf5f21a4474643b5b1b6219a203c0218778","source":{"kind":"arxiv","id":"2603.02970","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.02970","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"arxiv_version","alias_value":"2603.02970v2","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.02970","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"pith_short_12","alias_value":"WP7L7NE3W7SG","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"pith_short_16","alias_value":"WP7L7NE3W7SGHXI4","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"pith_short_8","alias_value":"WP7L7NE3","created_at":"2026-06-08T01:05:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:WP7L7NE3W7SGHXI4K2GWI4V36X","target":"record","payload":{"canonical_record":{"source":{"id":"2603.02970","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-03-03T13:24:36Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"9899751fc22b9a1e74460b6b420cc091af6f889920dbf10e71b63eb5e9f169a3","abstract_canon_sha256":"1eab336ab73b2c5fecbf62d8e01ba1206ef95a119dd0e08ca3a75b24e2a4c6be"},"schema_version":"1.0"},"canonical_sha256":"b3febfb49bb7e463dd1c568d6472bbf5f21a4474643b5b1b6219a203c0218778","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-08T01:05:09.353924Z","signature_b64":"Pn0x+XKBhWwCXklqkZ0TaSQjhj3W6ylIPHqA86dGLyk2vZr+a2OVQH/1geT0xj1XxqJYkByAbZkFFEB9+7uMAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3febfb49bb7e463dd1c568d6472bbf5f21a4474643b5b1b6219a203c0218778","last_reissued_at":"2026-06-08T01:05:09.353397Z","signature_status":"signed_v1","first_computed_at":"2026-06-08T01:05:09.353397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2603.02970","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":"2026-06-08T01:05:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DYk9Ni89KzjoR60kgI7LXDScqGZr40p3ule52Luzhm0LRR45JfOGdt5jjLOpj7CsV3ipz+k05l6lbYcpUYeKBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T09:09:41.032975Z"},"content_sha256":"6e1f66c4ec95de8027f2f46e796e09e2b2c59af10d197a695e743a5b7fb0a595","schema_version":"1.0","event_id":"sha256:6e1f66c4ec95de8027f2f46e796e09e2b2c59af10d197a695e743a5b7fb0a595"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:WP7L7NE3W7SGHXI4K2GWI4V36X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LAGO: A Local-Global Optimization Framework Combining Trust Region Methods and Bayesian Optimization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.LG","authors_text":"Eliott Van Dieren, Fabio Nobile, Tommaso Vanzan","submitted_at":"2026-03-03T13:24:36Z","abstract_excerpt":"We introduce LAGO, a LocAl-Global Optimization framework coupling Bayesian Optimization (BO) and gradient-based trust region local refinement through an adaptive competition mechanism for smooth expensive-to-evaluate objective functions with available gradients. At each iteration, global and local optimization strategies independently propose candidate points, and the next evaluation is selected based on predicted improvement. LAGO separates global exploration from local refinement at the proposal level: the BO acquisition function is optimized outside the active trust region, while local cand"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.02970","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/2603.02970/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":"2026-06-08T01:05:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mDagfFVAJ3uROMWOQhzWEahdEWg5L+0r3tu1m2D7jdsJVkQhdgbYinDupGEuD/7tXmjSG/Id6ClU4bDFLmAZDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T09:09:41.033374Z"},"content_sha256":"0c5dc2efca4b2d2296392d282d7ebf46afefc16e7998def42866bf81e18b5143","schema_version":"1.0","event_id":"sha256:0c5dc2efca4b2d2296392d282d7ebf46afefc16e7998def42866bf81e18b5143"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WP7L7NE3W7SGHXI4K2GWI4V36X/bundle.json","state_url":"https://pith.science/pith/WP7L7NE3W7SGHXI4K2GWI4V36X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WP7L7NE3W7SGHXI4K2GWI4V36X/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":"2026-06-11T09:09:41Z","links":{"resolver":"https://pith.science/pith/WP7L7NE3W7SGHXI4K2GWI4V36X","bundle":"https://pith.science/pith/WP7L7NE3W7SGHXI4K2GWI4V36X/bundle.json","state":"https://pith.science/pith/WP7L7NE3W7SGHXI4K2GWI4V36X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WP7L7NE3W7SGHXI4K2GWI4V36X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WP7L7NE3W7SGHXI4K2GWI4V36X","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":"1eab336ab73b2c5fecbf62d8e01ba1206ef95a119dd0e08ca3a75b24e2a4c6be","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-03-03T13:24:36Z","title_canon_sha256":"9899751fc22b9a1e74460b6b420cc091af6f889920dbf10e71b63eb5e9f169a3"},"schema_version":"1.0","source":{"id":"2603.02970","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.02970","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"arxiv_version","alias_value":"2603.02970v2","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.02970","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"pith_short_12","alias_value":"WP7L7NE3W7SG","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"pith_short_16","alias_value":"WP7L7NE3W7SGHXI4","created_at":"2026-06-08T01:05:09Z"},{"alias_kind":"pith_short_8","alias_value":"WP7L7NE3","created_at":"2026-06-08T01:05:09Z"}],"graph_snapshots":[{"event_id":"sha256:0c5dc2efca4b2d2296392d282d7ebf46afefc16e7998def42866bf81e18b5143","target":"graph","created_at":"2026-06-08T01:05:09Z","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/2603.02970/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce LAGO, a LocAl-Global Optimization framework coupling Bayesian Optimization (BO) and gradient-based trust region local refinement through an adaptive competition mechanism for smooth expensive-to-evaluate objective functions with available gradients. At each iteration, global and local optimization strategies independently propose candidate points, and the next evaluation is selected based on predicted improvement. LAGO separates global exploration from local refinement at the proposal level: the BO acquisition function is optimized outside the active trust region, while local cand","authors_text":"Eliott Van Dieren, Fabio Nobile, Tommaso Vanzan","cross_cats":["math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-03-03T13:24:36Z","title":"LAGO: A Local-Global Optimization Framework Combining Trust Region Methods and Bayesian Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.02970","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":"sha256:6e1f66c4ec95de8027f2f46e796e09e2b2c59af10d197a695e743a5b7fb0a595","target":"record","created_at":"2026-06-08T01:05:09Z","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":"1eab336ab73b2c5fecbf62d8e01ba1206ef95a119dd0e08ca3a75b24e2a4c6be","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-03-03T13:24:36Z","title_canon_sha256":"9899751fc22b9a1e74460b6b420cc091af6f889920dbf10e71b63eb5e9f169a3"},"schema_version":"1.0","source":{"id":"2603.02970","kind":"arxiv","version":2}},"canonical_sha256":"b3febfb49bb7e463dd1c568d6472bbf5f21a4474643b5b1b6219a203c0218778","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b3febfb49bb7e463dd1c568d6472bbf5f21a4474643b5b1b6219a203c0218778","first_computed_at":"2026-06-08T01:05:09.353397Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-08T01:05:09.353397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Pn0x+XKBhWwCXklqkZ0TaSQjhj3W6ylIPHqA86dGLyk2vZr+a2OVQH/1geT0xj1XxqJYkByAbZkFFEB9+7uMAA==","signature_status":"signed_v1","signed_at":"2026-06-08T01:05:09.353924Z","signed_message":"canonical_sha256_bytes"},"source_id":"2603.02970","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6e1f66c4ec95de8027f2f46e796e09e2b2c59af10d197a695e743a5b7fb0a595","sha256:0c5dc2efca4b2d2296392d282d7ebf46afefc16e7998def42866bf81e18b5143"],"state_sha256":"dcf11efba55315dd39a3506234cdbacebd82814e457186cfcc7fa7322c89643c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LgXRsL2sqBznQ4IfKIJeq/B7q7tqPuATQlBif58l42bw2k+tBYjrfX1kkV15eoV0Lxfl0+PrYWX/RzhjREdGBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T09:09:41.035581Z","bundle_sha256":"015cb822c836eb430e558d541079cb9167a8b37552da7134f2ba76d2da2547bf"}}