{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:L6LV7AT423R4H26SDUDIMNNQDZ","short_pith_number":"pith:L6LV7AT4","canonical_record":{"source":{"id":"1508.05128","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-08-20T21:18:25Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"5cea9efde2c9ccf5e80d35c140f4f9eab721244295d22773bc6200bbf1c709d6","abstract_canon_sha256":"997a3223378fe28696053c40ac3b38dc22e74c7bd22baac3038008e1402d9636"},"schema_version":"1.0"},"canonical_sha256":"5f975f827cd6e3c3ebd21d068635b01e69fd82de3955821ae2cc81473dde0054","source":{"kind":"arxiv","id":"1508.05128","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1508.05128","created_at":"2026-05-18T01:30:23Z"},{"alias_kind":"arxiv_version","alias_value":"1508.05128v2","created_at":"2026-05-18T01:30:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1508.05128","created_at":"2026-05-18T01:30:23Z"},{"alias_kind":"pith_short_12","alias_value":"L6LV7AT423R4","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_16","alias_value":"L6LV7AT423R4H26S","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_8","alias_value":"L6LV7AT4","created_at":"2026-05-18T12:29:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:L6LV7AT423R4H26SDUDIMNNQDZ","target":"record","payload":{"canonical_record":{"source":{"id":"1508.05128","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-08-20T21:18:25Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"5cea9efde2c9ccf5e80d35c140f4f9eab721244295d22773bc6200bbf1c709d6","abstract_canon_sha256":"997a3223378fe28696053c40ac3b38dc22e74c7bd22baac3038008e1402d9636"},"schema_version":"1.0"},"canonical_sha256":"5f975f827cd6e3c3ebd21d068635b01e69fd82de3955821ae2cc81473dde0054","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:30:23.221564Z","signature_b64":"tcPvt5XaaWrs4i6CGNFEaWR3XCIL2NgSBcW8ICqBlYcBm99De/FafNPJGAc7QQepO7qJu2ruSjQ11oRA+lFsBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f975f827cd6e3c3ebd21d068635b01e69fd82de3955821ae2cc81473dde0054","last_reissued_at":"2026-05-18T01:30:23.220803Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:30:23.220803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1508.05128","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":"2026-05-18T01:30:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9fCqodFGfd2ZOszbjoDwMb0xY0TvBvPWwJW8tZIq9SHbPoPNo/nJfCcz386IyyTK6e/Tcw4P26/+N3Y0sE8dAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T13:43:11.803464Z"},"content_sha256":"c3ae6040346ca7ba8d7d8ae291318071c48f9579edbaa57e59f0dde64c77592d","schema_version":"1.0","event_id":"sha256:c3ae6040346ca7ba8d7d8ae291318071c48f9579edbaa57e59f0dde64c77592d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:L6LV7AT423R4H26SDUDIMNNQDZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Lifted Relational Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"cs.AI","authors_text":"Filip Zelezny, Gustav Sourek, Ondrej Kuzelka, Vojtech Aschenbrenner","submitted_at":"2015-08-20T21:18:25Z","abstract_excerpt":"We propose a method combining relational-logic representations with neural network learning. A general lifted architecture, possibly reflecting some background domain knowledge, is described through relational rules which may be handcrafted or learned. The relational rule-set serves as a template for unfolding possibly deep neural networks whose structures also reflect the structures of given training or testing relational examples. Different networks corresponding to different examples share their weights, which co-evolve during training by stochastic gradient descent algorithm. The framework"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1508.05128","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":""},"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":"2026-05-18T01:30:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X6zwg7cQOkf7gbWNzllMOZPOzC7dN3Zjvjgmf6KwoP4dgpWhT6kQ0A6VpGX8j1C9GGCL6NJEgdqyc/t1lAhkBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T13:43:11.803986Z"},"content_sha256":"4a5363a6fd88a96a97418077a6da2d16a767db662984abd5376fe33a44e7e16a","schema_version":"1.0","event_id":"sha256:4a5363a6fd88a96a97418077a6da2d16a767db662984abd5376fe33a44e7e16a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L6LV7AT423R4H26SDUDIMNNQDZ/bundle.json","state_url":"https://pith.science/pith/L6LV7AT423R4H26SDUDIMNNQDZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L6LV7AT423R4H26SDUDIMNNQDZ/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":"2026-05-25T13:43:11Z","links":{"resolver":"https://pith.science/pith/L6LV7AT423R4H26SDUDIMNNQDZ","bundle":"https://pith.science/pith/L6LV7AT423R4H26SDUDIMNNQDZ/bundle.json","state":"https://pith.science/pith/L6LV7AT423R4H26SDUDIMNNQDZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L6LV7AT423R4H26SDUDIMNNQDZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:L6LV7AT423R4H26SDUDIMNNQDZ","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":"997a3223378fe28696053c40ac3b38dc22e74c7bd22baac3038008e1402d9636","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-08-20T21:18:25Z","title_canon_sha256":"5cea9efde2c9ccf5e80d35c140f4f9eab721244295d22773bc6200bbf1c709d6"},"schema_version":"1.0","source":{"id":"1508.05128","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1508.05128","created_at":"2026-05-18T01:30:23Z"},{"alias_kind":"arxiv_version","alias_value":"1508.05128v2","created_at":"2026-05-18T01:30:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1508.05128","created_at":"2026-05-18T01:30:23Z"},{"alias_kind":"pith_short_12","alias_value":"L6LV7AT423R4","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_16","alias_value":"L6LV7AT423R4H26S","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_8","alias_value":"L6LV7AT4","created_at":"2026-05-18T12:29:29Z"}],"graph_snapshots":[{"event_id":"sha256:4a5363a6fd88a96a97418077a6da2d16a767db662984abd5376fe33a44e7e16a","target":"graph","created_at":"2026-05-18T01:30:23Z","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"},"paper":{"abstract_excerpt":"We propose a method combining relational-logic representations with neural network learning. A general lifted architecture, possibly reflecting some background domain knowledge, is described through relational rules which may be handcrafted or learned. The relational rule-set serves as a template for unfolding possibly deep neural networks whose structures also reflect the structures of given training or testing relational examples. Different networks corresponding to different examples share their weights, which co-evolve during training by stochastic gradient descent algorithm. The framework","authors_text":"Filip Zelezny, Gustav Sourek, Ondrej Kuzelka, Vojtech Aschenbrenner","cross_cats":["cs.LG","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-08-20T21:18:25Z","title":"Lifted Relational Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1508.05128","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:c3ae6040346ca7ba8d7d8ae291318071c48f9579edbaa57e59f0dde64c77592d","target":"record","created_at":"2026-05-18T01:30:23Z","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":"997a3223378fe28696053c40ac3b38dc22e74c7bd22baac3038008e1402d9636","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-08-20T21:18:25Z","title_canon_sha256":"5cea9efde2c9ccf5e80d35c140f4f9eab721244295d22773bc6200bbf1c709d6"},"schema_version":"1.0","source":{"id":"1508.05128","kind":"arxiv","version":2}},"canonical_sha256":"5f975f827cd6e3c3ebd21d068635b01e69fd82de3955821ae2cc81473dde0054","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5f975f827cd6e3c3ebd21d068635b01e69fd82de3955821ae2cc81473dde0054","first_computed_at":"2026-05-18T01:30:23.220803Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:30:23.220803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tcPvt5XaaWrs4i6CGNFEaWR3XCIL2NgSBcW8ICqBlYcBm99De/FafNPJGAc7QQepO7qJu2ruSjQ11oRA+lFsBw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:30:23.221564Z","signed_message":"canonical_sha256_bytes"},"source_id":"1508.05128","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c3ae6040346ca7ba8d7d8ae291318071c48f9579edbaa57e59f0dde64c77592d","sha256:4a5363a6fd88a96a97418077a6da2d16a767db662984abd5376fe33a44e7e16a"],"state_sha256":"c80548500189dd325476cedd0675456b941c16177440f767db5138b675c56130"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OVMLRrppKUhvDjlIslZjLrsX3oxjwQkwgwTgESIbYA5vPvHSwBRkIlOh4BvrPbIjK9Khdrq0SxwGXhytiY3KDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T13:43:11.806866Z","bundle_sha256":"26e7e113bc3b43926edd93c360fb242c8b3765d6bd25bedf1fdef85e43b9ddaf"}}