{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:WZY3RVPTGPNL5GFPPYBXVE7XZD","short_pith_number":"pith:WZY3RVPT","canonical_record":{"source":{"id":"2301.08840","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-21T00:52:32Z","cross_cats_sorted":[],"title_canon_sha256":"07f8923c03a932584cfba6f9cf98c0bdfd35abbd78dda0132b90cf2fb02e750f","abstract_canon_sha256":"adf83d3f990ae21a91b2e9c1c4eb08cde1ddbc45e8637a13ceabb584634922e1"},"schema_version":"1.0"},"canonical_sha256":"b671b8d5f333dabe98af7e037a93f7c8dde9b803357bdc5bf9fa126468574df9","source":{"kind":"arxiv","id":"2301.08840","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.08840","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"arxiv_version","alias_value":"2301.08840v3","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.08840","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"pith_short_12","alias_value":"WZY3RVPTGPNL","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"pith_short_16","alias_value":"WZY3RVPTGPNL5GFP","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"pith_short_8","alias_value":"WZY3RVPT","created_at":"2026-07-05T06:11:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:WZY3RVPTGPNL5GFPPYBXVE7XZD","target":"record","payload":{"canonical_record":{"source":{"id":"2301.08840","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-21T00:52:32Z","cross_cats_sorted":[],"title_canon_sha256":"07f8923c03a932584cfba6f9cf98c0bdfd35abbd78dda0132b90cf2fb02e750f","abstract_canon_sha256":"adf83d3f990ae21a91b2e9c1c4eb08cde1ddbc45e8637a13ceabb584634922e1"},"schema_version":"1.0"},"canonical_sha256":"b671b8d5f333dabe98af7e037a93f7c8dde9b803357bdc5bf9fa126468574df9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:11:02.792739Z","signature_b64":"U2l8ei04xU19Qg/HCsZHyvqZCefAosjaJ7ZEs+3bhmxa7Z3X2MzvZKUlneu9dxXmjen2ivhHEsh6jA//P7MJAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b671b8d5f333dabe98af7e037a93f7c8dde9b803357bdc5bf9fa126468574df9","last_reissued_at":"2026-07-05T06:11:02.792282Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:11:02.792282Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.08840","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:11:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VWbXr83/6hYqiAptOCm7znv28uZmiH1Sa6idOGmDwQfy9L+NJCFvxsc4E2HJBQaSC7zPL1LXb5jUR6r+yLXGBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T21:02:51.316779Z"},"content_sha256":"87a7d3bb8dfa2527521ad1f6cd28dcc5a1f469c1e829e0203ea553d599139b53","schema_version":"1.0","event_id":"sha256:87a7d3bb8dfa2527521ad1f6cd28dcc5a1f469c1e829e0203ea553d599139b53"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:WZY3RVPTGPNL5GFPPYBXVE7XZD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Compact Optimization Learning for AC Optimal Power Flow","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Pascal Van Hentenryck, Seonho Park, Terrence W.K. Mak, Wenbo Chen","submitted_at":"2023-01-21T00:52:32Z","abstract_excerpt":"This paper reconsiders end-to-end learning approaches to the Optimal Power Flow (OPF). Existing methods, which learn the input/output mapping of the OPF, suffer from scalability issues due to the high dimensionality of the output space. This paper first shows that the space of optimal solutions can be significantly compressed using principal component analysis (PCA). It then proposes Compact Learning, a new method that learns in a subspace of the principal components before translating the vectors into the original output space. This compression reduces the number of trainable parameters subst"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.08840","kind":"arxiv","version":3},"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/2301.08840/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":"2026-07-05T06:11:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Iah3GdaOkZTpZWAs/B/fgvMdGQfi3L3iyv4J10mrKHe6jtDpteERr6ZKZK10qv/zDMM40BLTukSWFWYtY7exAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T21:02:51.317718Z"},"content_sha256":"2c8e50a52f5e45a6633136f0cd72e7543de37fa0a86d3ba5b1aa81e2c69e8a6c","schema_version":"1.0","event_id":"sha256:2c8e50a52f5e45a6633136f0cd72e7543de37fa0a86d3ba5b1aa81e2c69e8a6c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WZY3RVPTGPNL5GFPPYBXVE7XZD/bundle.json","state_url":"https://pith.science/pith/WZY3RVPTGPNL5GFPPYBXVE7XZD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WZY3RVPTGPNL5GFPPYBXVE7XZD/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":"2026-08-10T21:02:51Z","links":{"resolver":"https://pith.science/pith/WZY3RVPTGPNL5GFPPYBXVE7XZD","bundle":"https://pith.science/pith/WZY3RVPTGPNL5GFPPYBXVE7XZD/bundle.json","state":"https://pith.science/pith/WZY3RVPTGPNL5GFPPYBXVE7XZD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WZY3RVPTGPNL5GFPPYBXVE7XZD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:WZY3RVPTGPNL5GFPPYBXVE7XZD","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":"adf83d3f990ae21a91b2e9c1c4eb08cde1ddbc45e8637a13ceabb584634922e1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-21T00:52:32Z","title_canon_sha256":"07f8923c03a932584cfba6f9cf98c0bdfd35abbd78dda0132b90cf2fb02e750f"},"schema_version":"1.0","source":{"id":"2301.08840","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.08840","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"arxiv_version","alias_value":"2301.08840v3","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.08840","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"pith_short_12","alias_value":"WZY3RVPTGPNL","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"pith_short_16","alias_value":"WZY3RVPTGPNL5GFP","created_at":"2026-07-05T06:11:02Z"},{"alias_kind":"pith_short_8","alias_value":"WZY3RVPT","created_at":"2026-07-05T06:11:02Z"}],"graph_snapshots":[{"event_id":"sha256:2c8e50a52f5e45a6633136f0cd72e7543de37fa0a86d3ba5b1aa81e2c69e8a6c","target":"graph","created_at":"2026-07-05T06:11:02Z","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/2301.08840/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper reconsiders end-to-end learning approaches to the Optimal Power Flow (OPF). Existing methods, which learn the input/output mapping of the OPF, suffer from scalability issues due to the high dimensionality of the output space. This paper first shows that the space of optimal solutions can be significantly compressed using principal component analysis (PCA). It then proposes Compact Learning, a new method that learns in a subspace of the principal components before translating the vectors into the original output space. This compression reduces the number of trainable parameters subst","authors_text":"Pascal Van Hentenryck, Seonho Park, Terrence W.K. Mak, Wenbo Chen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-21T00:52:32Z","title":"Compact Optimization Learning for AC Optimal Power Flow"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.08840","kind":"arxiv","version":3},"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":"sha256:87a7d3bb8dfa2527521ad1f6cd28dcc5a1f469c1e829e0203ea553d599139b53","target":"record","created_at":"2026-07-05T06:11:02Z","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":"adf83d3f990ae21a91b2e9c1c4eb08cde1ddbc45e8637a13ceabb584634922e1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-21T00:52:32Z","title_canon_sha256":"07f8923c03a932584cfba6f9cf98c0bdfd35abbd78dda0132b90cf2fb02e750f"},"schema_version":"1.0","source":{"id":"2301.08840","kind":"arxiv","version":3}},"canonical_sha256":"b671b8d5f333dabe98af7e037a93f7c8dde9b803357bdc5bf9fa126468574df9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b671b8d5f333dabe98af7e037a93f7c8dde9b803357bdc5bf9fa126468574df9","first_computed_at":"2026-07-05T06:11:02.792282Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:11:02.792282Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"U2l8ei04xU19Qg/HCsZHyvqZCefAosjaJ7ZEs+3bhmxa7Z3X2MzvZKUlneu9dxXmjen2ivhHEsh6jA//P7MJAw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:11:02.792739Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.08840","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:87a7d3bb8dfa2527521ad1f6cd28dcc5a1f469c1e829e0203ea553d599139b53","sha256:2c8e50a52f5e45a6633136f0cd72e7543de37fa0a86d3ba5b1aa81e2c69e8a6c"],"state_sha256":"c023391bc2ffbdfcae7747ca25d89f6a222db12dfdc7802efbd1c3f589064ac5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LOvzk7pFhpZNyT2hhKGdlFpYQqkzpycSKKD029fnoTMDaPd7d/Q5xYKC6rGz6on9dYs1WD/3tScY8KQmRxrnCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T21:02:51.334006Z","bundle_sha256":"8beaa37d0fcd18b9019f674d549c821ffed8d5fcc7d25fc83de3e9227e84ba33"}}