{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:M2ZMWGBS4DXFTPF4G2W4IY5IW6","short_pith_number":"pith:M2ZMWGBS","canonical_record":{"source":{"id":"2608.03075","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2026-08-04T03:39:43Z","cross_cats_sorted":[],"title_canon_sha256":"ab162b84ae8486ccf683a561e5a12f622d9594144bcaee17b57cbe1df4a13466","abstract_canon_sha256":"a8034559dd0745235bbf670d1316534e26e2b422673828a5c09fea2bde86cbbd"},"schema_version":"1.0"},"canonical_sha256":"66b2cb1832e0ee59bcbc36adc463a8b78164ff333a6c93315ba635bf5ed54e12","source":{"kind":"arxiv","id":"2608.03075","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.03075","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"arxiv_version","alias_value":"2608.03075v1","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.03075","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"pith_short_12","alias_value":"M2ZMWGBS4DXF","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"pith_short_16","alias_value":"M2ZMWGBS4DXFTPF4","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"pith_short_8","alias_value":"M2ZMWGBS","created_at":"2026-08-05T00:45:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:M2ZMWGBS4DXFTPF4G2W4IY5IW6","target":"record","payload":{"canonical_record":{"source":{"id":"2608.03075","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2026-08-04T03:39:43Z","cross_cats_sorted":[],"title_canon_sha256":"ab162b84ae8486ccf683a561e5a12f622d9594144bcaee17b57cbe1df4a13466","abstract_canon_sha256":"a8034559dd0745235bbf670d1316534e26e2b422673828a5c09fea2bde86cbbd"},"schema_version":"1.0"},"canonical_sha256":"66b2cb1832e0ee59bcbc36adc463a8b78164ff333a6c93315ba635bf5ed54e12","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-05T00:45:16.464817Z","signature_b64":"SvK36E9c6MZr/W/7VEwyFMHq7aEGgE5XvO+dsLsWn0qmpR+mOQcr0nxjxymziyeH0A8+z4eoLEWojwXdr6T+CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"66b2cb1832e0ee59bcbc36adc463a8b78164ff333a6c93315ba635bf5ed54e12","last_reissued_at":"2026-08-05T00:45:16.462488Z","signature_status":"signed_v1","first_computed_at":"2026-08-05T00:45:16.462488Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.03075","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-05T00:45:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nybGIejZ50Z3RG/tBeP/5ebxiEXzom28Diypgl2VvbNh8vR1cDgso1/NZ2AZxl0kdAJOsK4lEYLr65nIBmU4Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T11:35:01.927424Z"},"content_sha256":"a8d96fbbdc37e6f6f7eeda317b2c3729f517e81c5a160c6f1ad2af83095e81e9","schema_version":"1.0","event_id":"sha256:a8d96fbbdc37e6f6f7eeda317b2c3729f517e81c5a160c6f1ad2af83095e81e9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:M2ZMWGBS4DXFTPF4G2W4IY5IW6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Oracle-Based Distributionally Robust Optimization under Optimal Transport Ambiguity Sets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Guixian Chen, Salar Fattahi, Soroosh Shafiee","submitted_at":"2026-08-04T03:39:43Z","abstract_excerpt":"Distributionally robust optimization (DRO) with optimal transport ambiguity sets is traditionally solved by reformulating the minimax problem into a single-level convex program. While theoretically tractable, these reformulations introduce numerous auxiliary variables and demanding conic constraints that scale poorly in practice. In this paper, we address this challenge by reducing the inner worst-case expectation problem exactly to a scalar budget allocation task. This structural insight yields an efficient algorithm that bypasses large lifted reformulations, alongside a fast post-processing "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.03075","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/2608.03075/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":"2026-08-05T00:45:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M3zqqwzxBXAGIQqxMLLi3ZnSn04HfttgO0EBHtTKqKG+BeIkM7D7XM5SMjl4Cy24lpaTF9p6+NZ+dfJ1gkoVBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T11:35:01.927826Z"},"content_sha256":"1c38f39c666dc3b55fd80ef3c4f236a4e24bb39786135d38b477612442ad9baa","schema_version":"1.0","event_id":"sha256:1c38f39c666dc3b55fd80ef3c4f236a4e24bb39786135d38b477612442ad9baa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M2ZMWGBS4DXFTPF4G2W4IY5IW6/bundle.json","state_url":"https://pith.science/pith/M2ZMWGBS4DXFTPF4G2W4IY5IW6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M2ZMWGBS4DXFTPF4G2W4IY5IW6/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":"2026-08-19T11:35:01Z","links":{"resolver":"https://pith.science/pith/M2ZMWGBS4DXFTPF4G2W4IY5IW6","bundle":"https://pith.science/pith/M2ZMWGBS4DXFTPF4G2W4IY5IW6/bundle.json","state":"https://pith.science/pith/M2ZMWGBS4DXFTPF4G2W4IY5IW6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M2ZMWGBS4DXFTPF4G2W4IY5IW6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:M2ZMWGBS4DXFTPF4G2W4IY5IW6","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":"a8034559dd0745235bbf670d1316534e26e2b422673828a5c09fea2bde86cbbd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2026-08-04T03:39:43Z","title_canon_sha256":"ab162b84ae8486ccf683a561e5a12f622d9594144bcaee17b57cbe1df4a13466"},"schema_version":"1.0","source":{"id":"2608.03075","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.03075","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"arxiv_version","alias_value":"2608.03075v1","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.03075","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"pith_short_12","alias_value":"M2ZMWGBS4DXF","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"pith_short_16","alias_value":"M2ZMWGBS4DXFTPF4","created_at":"2026-08-05T00:45:16Z"},{"alias_kind":"pith_short_8","alias_value":"M2ZMWGBS","created_at":"2026-08-05T00:45:16Z"}],"graph_snapshots":[{"event_id":"sha256:1c38f39c666dc3b55fd80ef3c4f236a4e24bb39786135d38b477612442ad9baa","target":"graph","created_at":"2026-08-05T00:45:16Z","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/2608.03075/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Distributionally robust optimization (DRO) with optimal transport ambiguity sets is traditionally solved by reformulating the minimax problem into a single-level convex program. While theoretically tractable, these reformulations introduce numerous auxiliary variables and demanding conic constraints that scale poorly in practice. In this paper, we address this challenge by reducing the inner worst-case expectation problem exactly to a scalar budget allocation task. This structural insight yields an efficient algorithm that bypasses large lifted reformulations, alongside a fast post-processing ","authors_text":"Guixian Chen, Salar Fattahi, Soroosh Shafiee","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2026-08-04T03:39:43Z","title":"Oracle-Based Distributionally Robust Optimization under Optimal Transport Ambiguity Sets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.03075","kind":"arxiv","version":1},"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:a8d96fbbdc37e6f6f7eeda317b2c3729f517e81c5a160c6f1ad2af83095e81e9","target":"record","created_at":"2026-08-05T00:45:16Z","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":"a8034559dd0745235bbf670d1316534e26e2b422673828a5c09fea2bde86cbbd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2026-08-04T03:39:43Z","title_canon_sha256":"ab162b84ae8486ccf683a561e5a12f622d9594144bcaee17b57cbe1df4a13466"},"schema_version":"1.0","source":{"id":"2608.03075","kind":"arxiv","version":1}},"canonical_sha256":"66b2cb1832e0ee59bcbc36adc463a8b78164ff333a6c93315ba635bf5ed54e12","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"66b2cb1832e0ee59bcbc36adc463a8b78164ff333a6c93315ba635bf5ed54e12","first_computed_at":"2026-08-05T00:45:16.462488Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-05T00:45:16.462488Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SvK36E9c6MZr/W/7VEwyFMHq7aEGgE5XvO+dsLsWn0qmpR+mOQcr0nxjxymziyeH0A8+z4eoLEWojwXdr6T+CQ==","signature_status":"signed_v1","signed_at":"2026-08-05T00:45:16.464817Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.03075","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a8d96fbbdc37e6f6f7eeda317b2c3729f517e81c5a160c6f1ad2af83095e81e9","sha256:1c38f39c666dc3b55fd80ef3c4f236a4e24bb39786135d38b477612442ad9baa"],"state_sha256":"9f35161ff0414d5c289b6b95687886fbb1c605188bf8c0f7abf1ab859b702bf7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bSMKAUf0vWNrFEXwiiC/k3LqG3LdNzZTLkhip4PAfCWE5SFB/PDMMf4JvKuaV09B5ROakr3u26pOwV6+xU83Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T11:35:01.930231Z","bundle_sha256":"29ebc1fd05ea743890e2177a02d55140fc4d873610120a564a1e2b939ed27ef6"}}