{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:SVGKOGZUQXRNGK7ED6M3RDT43A","short_pith_number":"pith:SVGKOGZU","canonical_record":{"source":{"id":"2306.02429","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2023-06-04T18:21:53Z","cross_cats_sorted":[],"title_canon_sha256":"0bfd25944b3cb12f194d2cb7d389e5460be907451f788db832426652b668c3a4","abstract_canon_sha256":"e7bbad42fc72382430e44245e1aca99e67ec07d6f8196f1186e96234fda75c0d"},"schema_version":"1.0"},"canonical_sha256":"954ca71b3485e2d32be41f99b88e7cd82e4d38db97900373e71150b7c5196e07","source":{"kind":"arxiv","id":"2306.02429","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.02429","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"arxiv_version","alias_value":"2306.02429v2","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.02429","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"pith_short_12","alias_value":"SVGKOGZUQXRN","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"pith_short_16","alias_value":"SVGKOGZUQXRNGK7E","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"pith_short_8","alias_value":"SVGKOGZU","created_at":"2026-07-05T07:55:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:SVGKOGZUQXRNGK7ED6M3RDT43A","target":"record","payload":{"canonical_record":{"source":{"id":"2306.02429","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2023-06-04T18:21:53Z","cross_cats_sorted":[],"title_canon_sha256":"0bfd25944b3cb12f194d2cb7d389e5460be907451f788db832426652b668c3a4","abstract_canon_sha256":"e7bbad42fc72382430e44245e1aca99e67ec07d6f8196f1186e96234fda75c0d"},"schema_version":"1.0"},"canonical_sha256":"954ca71b3485e2d32be41f99b88e7cd82e4d38db97900373e71150b7c5196e07","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:55:44.660068Z","signature_b64":"/7vD09pCE1Ey98ziWueU3uBqeRV0AuGS+Hh/4SM296Dt2+LaAckXVZIundNllyiHyK0mBYqXREEPfCLpHCHvCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"954ca71b3485e2d32be41f99b88e7cd82e4d38db97900373e71150b7c5196e07","last_reissued_at":"2026-07-05T07:55:44.659671Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:55:44.659671Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.02429","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":"2026-07-05T07:55:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EaoO+iy73RO3OkY2Vjpeeffb0p0y7Rku/PVCY99aX1Y+EgLteiVEBcU3IJPlLIbjP9lkEhdMhgMACq4g+1sQDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T11:43:51.777474Z"},"content_sha256":"3671cdd31bfa9d166ab4d68fb5d44ad58dd765a59f803e6909a366b889b96d13","schema_version":"1.0","event_id":"sha256:3671cdd31bfa9d166ab4d68fb5d44ad58dd765a59f803e6909a366b889b96d13"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:SVGKOGZUQXRNGK7ED6M3RDT43A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Inexact Conditional Gradient Method for Constrained Bilevel Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Aryan Mokhtari, Erfan Yazdandoost Hamedani, Nazanin Abolfazli, Ruichen Jiang","submitted_at":"2023-06-04T18:21:53Z","abstract_excerpt":"Bilevel optimization is an important class of optimization problems where one optimization problem is nested within another. While various methods have emerged to address unconstrained general bilevel optimization problems, there has been a noticeable gap in research when it comes to methods tailored for the constrained scenario. The few methods that do accommodate constrained problems, often exhibit slow convergence rates or demand a high computational cost per iteration. To tackle this issue, our paper introduces a novel single-loop projection-free method employing a nested approximation tec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.02429","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/2306.02429/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":"2026-07-05T07:55:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rlMbnFq/gIsCXSdysLyKsNspXX8o8URS7K8lHut6QVkU9a8zWIUU2jh9C2IBzaqoxbxh9l+vGjZIHMLTmCnhBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T11:43:51.777994Z"},"content_sha256":"ca5ed495ffcd1b3331442583ceeaf50670366302d42995184598fc70661c90d3","schema_version":"1.0","event_id":"sha256:ca5ed495ffcd1b3331442583ceeaf50670366302d42995184598fc70661c90d3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SVGKOGZUQXRNGK7ED6M3RDT43A/bundle.json","state_url":"https://pith.science/pith/SVGKOGZUQXRNGK7ED6M3RDT43A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SVGKOGZUQXRNGK7ED6M3RDT43A/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":"2026-08-11T11:43:51Z","links":{"resolver":"https://pith.science/pith/SVGKOGZUQXRNGK7ED6M3RDT43A","bundle":"https://pith.science/pith/SVGKOGZUQXRNGK7ED6M3RDT43A/bundle.json","state":"https://pith.science/pith/SVGKOGZUQXRNGK7ED6M3RDT43A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SVGKOGZUQXRNGK7ED6M3RDT43A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:SVGKOGZUQXRNGK7ED6M3RDT43A","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":"e7bbad42fc72382430e44245e1aca99e67ec07d6f8196f1186e96234fda75c0d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2023-06-04T18:21:53Z","title_canon_sha256":"0bfd25944b3cb12f194d2cb7d389e5460be907451f788db832426652b668c3a4"},"schema_version":"1.0","source":{"id":"2306.02429","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.02429","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"arxiv_version","alias_value":"2306.02429v2","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.02429","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"pith_short_12","alias_value":"SVGKOGZUQXRN","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"pith_short_16","alias_value":"SVGKOGZUQXRNGK7E","created_at":"2026-07-05T07:55:44Z"},{"alias_kind":"pith_short_8","alias_value":"SVGKOGZU","created_at":"2026-07-05T07:55:44Z"}],"graph_snapshots":[{"event_id":"sha256:ca5ed495ffcd1b3331442583ceeaf50670366302d42995184598fc70661c90d3","target":"graph","created_at":"2026-07-05T07:55:44Z","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/2306.02429/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Bilevel optimization is an important class of optimization problems where one optimization problem is nested within another. While various methods have emerged to address unconstrained general bilevel optimization problems, there has been a noticeable gap in research when it comes to methods tailored for the constrained scenario. The few methods that do accommodate constrained problems, often exhibit slow convergence rates or demand a high computational cost per iteration. To tackle this issue, our paper introduces a novel single-loop projection-free method employing a nested approximation tec","authors_text":"Aryan Mokhtari, Erfan Yazdandoost Hamedani, Nazanin Abolfazli, Ruichen Jiang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2023-06-04T18:21:53Z","title":"An Inexact Conditional Gradient Method for Constrained Bilevel Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.02429","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":"sha256:3671cdd31bfa9d166ab4d68fb5d44ad58dd765a59f803e6909a366b889b96d13","target":"record","created_at":"2026-07-05T07:55:44Z","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":"e7bbad42fc72382430e44245e1aca99e67ec07d6f8196f1186e96234fda75c0d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2023-06-04T18:21:53Z","title_canon_sha256":"0bfd25944b3cb12f194d2cb7d389e5460be907451f788db832426652b668c3a4"},"schema_version":"1.0","source":{"id":"2306.02429","kind":"arxiv","version":2}},"canonical_sha256":"954ca71b3485e2d32be41f99b88e7cd82e4d38db97900373e71150b7c5196e07","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"954ca71b3485e2d32be41f99b88e7cd82e4d38db97900373e71150b7c5196e07","first_computed_at":"2026-07-05T07:55:44.659671Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:55:44.659671Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/7vD09pCE1Ey98ziWueU3uBqeRV0AuGS+Hh/4SM296Dt2+LaAckXVZIundNllyiHyK0mBYqXREEPfCLpHCHvCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:55:44.660068Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.02429","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3671cdd31bfa9d166ab4d68fb5d44ad58dd765a59f803e6909a366b889b96d13","sha256:ca5ed495ffcd1b3331442583ceeaf50670366302d42995184598fc70661c90d3"],"state_sha256":"4db02303aefc20fda044f9adaf9523e5cec89ec1d9b813958146c9a092b182e3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+qn4taLxi05CL/9rahvIhrl/bcBvBPt45nAjZg8NXJ3tY8LugTGpbTeDYE9yQooDyCGOcJZDyZ625biEEVe/DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T11:43:51.782960Z","bundle_sha256":"3d2bc7f246bdee407f72dde605909a9f6e81fbec56ed76ea35a6b54440be359d"}}