{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ZLDKLVZKDV6VOQOAWGZGTQ64MF","short_pith_number":"pith:ZLDKLVZK","canonical_record":{"source":{"id":"2408.04053","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T19:24:02Z","cross_cats_sorted":[],"title_canon_sha256":"b039492d55904124d1c0d9055644cc60ebd09de59118007d7fdf17b8644b08b0","abstract_canon_sha256":"73241e356e5f082fd60157ac862ae25021fb57b1178f9c6ad3176df9d97af418"},"schema_version":"1.0"},"canonical_sha256":"cac6a5d72a1d7d5741c0b1b269c3dc6142cb88164a44d915303cfdc10e48f87a","source":{"kind":"arxiv","id":"2408.04053","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.04053","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"arxiv_version","alias_value":"2408.04053v1","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.04053","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"pith_short_12","alias_value":"ZLDKLVZKDV6V","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"pith_short_16","alias_value":"ZLDKLVZKDV6VOQOA","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"pith_short_8","alias_value":"ZLDKLVZK","created_at":"2026-07-05T08:53:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ZLDKLVZKDV6VOQOAWGZGTQ64MF","target":"record","payload":{"canonical_record":{"source":{"id":"2408.04053","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T19:24:02Z","cross_cats_sorted":[],"title_canon_sha256":"b039492d55904124d1c0d9055644cc60ebd09de59118007d7fdf17b8644b08b0","abstract_canon_sha256":"73241e356e5f082fd60157ac862ae25021fb57b1178f9c6ad3176df9d97af418"},"schema_version":"1.0"},"canonical_sha256":"cac6a5d72a1d7d5741c0b1b269c3dc6142cb88164a44d915303cfdc10e48f87a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:53:27.463011Z","signature_b64":"5frvlbPCR4/uFRI6GO+3alsy7ncPAbQE7X1YN+VBkMgt4cWyBS//kcsCveOLgDyb8HUmi8VwqwrC/PrSRElPBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cac6a5d72a1d7d5741c0b1b269c3dc6142cb88164a44d915303cfdc10e48f87a","last_reissued_at":"2026-07-05T08:53:27.462598Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:53:27.462598Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.04053","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":"2026-07-05T08:53:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LUkfyZ9f1Z5xkfoVFfkM/Nllgmo3RkZgXWHZjZptEisOIujLQsMopwqewJXr4oRKrpma8UmZBfQ83Dh9BN4GBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T07:16:33.631815Z"},"content_sha256":"4095ca95ba53350f346a0986ecfc4604c0d58f386e11c7a370ecb15c23907a6f","schema_version":"1.0","event_id":"sha256:4095ca95ba53350f346a0986ecfc4604c0d58f386e11c7a370ecb15c23907a6f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ZLDKLVZKDV6VOQOAWGZGTQ64MF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Generative Models for Subgraph Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Erfaneh Mahmoudzadeh, Kiarash Zahirnia, Oliver Schulte, Parmis Naddaf","submitted_at":"2024-08-07T19:24:02Z","abstract_excerpt":"Graph Neural Networks (GNNs) are important across different domains, such as social network analysis and recommendation systems, due to their ability to model complex relational data. This paper introduces subgraph queries as a new task for deep graph learning. Unlike traditional graph prediction tasks that focus on individual components like link prediction or node classification, subgraph queries jointly predict the components of a target subgraph based on evidence that is represented by an observed subgraph. For instance, a subgraph query can predict a set of target links and/or node labels"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.04053","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/2408.04053/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":"2026-07-05T08:53:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZHpHT0mlUaP8odAGi3QNfmhrroa+2P/oxuHJQhddJsfgsDLoLAcJlf/B0g/2KiUqmgeS7+SkLHy52OYR0kOSAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T07:16:33.632507Z"},"content_sha256":"5eafc36a1772e7a1d4ef8708a0fe1f9e38917f15c0c004548acadc33fa388ed0","schema_version":"1.0","event_id":"sha256:5eafc36a1772e7a1d4ef8708a0fe1f9e38917f15c0c004548acadc33fa388ed0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZLDKLVZKDV6VOQOAWGZGTQ64MF/bundle.json","state_url":"https://pith.science/pith/ZLDKLVZKDV6VOQOAWGZGTQ64MF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZLDKLVZKDV6VOQOAWGZGTQ64MF/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":"2026-08-23T07:16:33Z","links":{"resolver":"https://pith.science/pith/ZLDKLVZKDV6VOQOAWGZGTQ64MF","bundle":"https://pith.science/pith/ZLDKLVZKDV6VOQOAWGZGTQ64MF/bundle.json","state":"https://pith.science/pith/ZLDKLVZKDV6VOQOAWGZGTQ64MF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZLDKLVZKDV6VOQOAWGZGTQ64MF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ZLDKLVZKDV6VOQOAWGZGTQ64MF","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":"73241e356e5f082fd60157ac862ae25021fb57b1178f9c6ad3176df9d97af418","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T19:24:02Z","title_canon_sha256":"b039492d55904124d1c0d9055644cc60ebd09de59118007d7fdf17b8644b08b0"},"schema_version":"1.0","source":{"id":"2408.04053","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.04053","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"arxiv_version","alias_value":"2408.04053v1","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.04053","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"pith_short_12","alias_value":"ZLDKLVZKDV6V","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"pith_short_16","alias_value":"ZLDKLVZKDV6VOQOA","created_at":"2026-07-05T08:53:27Z"},{"alias_kind":"pith_short_8","alias_value":"ZLDKLVZK","created_at":"2026-07-05T08:53:27Z"}],"graph_snapshots":[{"event_id":"sha256:5eafc36a1772e7a1d4ef8708a0fe1f9e38917f15c0c004548acadc33fa388ed0","target":"graph","created_at":"2026-07-05T08:53:27Z","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/2408.04053/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph Neural Networks (GNNs) are important across different domains, such as social network analysis and recommendation systems, due to their ability to model complex relational data. This paper introduces subgraph queries as a new task for deep graph learning. Unlike traditional graph prediction tasks that focus on individual components like link prediction or node classification, subgraph queries jointly predict the components of a target subgraph based on evidence that is represented by an observed subgraph. For instance, a subgraph query can predict a set of target links and/or node labels","authors_text":"Erfaneh Mahmoudzadeh, Kiarash Zahirnia, Oliver Schulte, Parmis Naddaf","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T19:24:02Z","title":"Deep Generative Models for Subgraph Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.04053","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":"sha256:4095ca95ba53350f346a0986ecfc4604c0d58f386e11c7a370ecb15c23907a6f","target":"record","created_at":"2026-07-05T08:53:27Z","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":"73241e356e5f082fd60157ac862ae25021fb57b1178f9c6ad3176df9d97af418","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T19:24:02Z","title_canon_sha256":"b039492d55904124d1c0d9055644cc60ebd09de59118007d7fdf17b8644b08b0"},"schema_version":"1.0","source":{"id":"2408.04053","kind":"arxiv","version":1}},"canonical_sha256":"cac6a5d72a1d7d5741c0b1b269c3dc6142cb88164a44d915303cfdc10e48f87a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cac6a5d72a1d7d5741c0b1b269c3dc6142cb88164a44d915303cfdc10e48f87a","first_computed_at":"2026-07-05T08:53:27.462598Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:53:27.462598Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5frvlbPCR4/uFRI6GO+3alsy7ncPAbQE7X1YN+VBkMgt4cWyBS//kcsCveOLgDyb8HUmi8VwqwrC/PrSRElPBw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:53:27.463011Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.04053","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4095ca95ba53350f346a0986ecfc4604c0d58f386e11c7a370ecb15c23907a6f","sha256:5eafc36a1772e7a1d4ef8708a0fe1f9e38917f15c0c004548acadc33fa388ed0"],"state_sha256":"e9f062a328967b757d60c4384f712f03ccbf1b7dd61df6735f87baf3218c7228"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"laR/0UtGtCk9su563gr/TTtb8vLdfh2zobUXSrjI+kGxLH1sGPbXNGaBNZJeZbIxc2xTXIJ1DNGGUHn40aKMAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T07:16:33.638233Z","bundle_sha256":"f0f0827f381b81ddaa588762a1bf5ad582892a3a7efadc5446f8557483a108a0"}}