{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:XJOXO6Y2JORP3NAVNUT2NUNCHN","short_pith_number":"pith:XJOXO6Y2","canonical_record":{"source":{"id":"2306.07735","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-13T12:40:39Z","cross_cats_sorted":[],"title_canon_sha256":"0a88b81a14ef81571f5b5f03fcf4d4337c3b5367e1dd04211ed5e2496a059655","abstract_canon_sha256":"df2e342649926abf79485104bdff519703f9dd9dc01c72916e9cf6ba1418afc1"},"schema_version":"1.0"},"canonical_sha256":"ba5d777b1a4ba2fdb4156d27a6d1a23b72c9a13bb441c85e24366fb663972a5a","source":{"kind":"arxiv","id":"2306.07735","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.07735","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"arxiv_version","alias_value":"2306.07735v2","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.07735","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"pith_short_12","alias_value":"XJOXO6Y2JORP","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"pith_short_16","alias_value":"XJOXO6Y2JORP3NAV","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"pith_short_8","alias_value":"XJOXO6Y2","created_at":"2026-07-05T07:39:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:XJOXO6Y2JORP3NAVNUT2NUNCHN","target":"record","payload":{"canonical_record":{"source":{"id":"2306.07735","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-13T12:40:39Z","cross_cats_sorted":[],"title_canon_sha256":"0a88b81a14ef81571f5b5f03fcf4d4337c3b5367e1dd04211ed5e2496a059655","abstract_canon_sha256":"df2e342649926abf79485104bdff519703f9dd9dc01c72916e9cf6ba1418afc1"},"schema_version":"1.0"},"canonical_sha256":"ba5d777b1a4ba2fdb4156d27a6d1a23b72c9a13bb441c85e24366fb663972a5a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:39:09.586763Z","signature_b64":"jpUyclPp5aaHJAzinAYPKFHIOStWNig56cQYwPvSqdwaOoEb2Dcm3l7TkWJ3gmMAlb50frK2arBWsBDZ/UyEBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba5d777b1a4ba2fdb4156d27a6d1a23b72c9a13bb441c85e24366fb663972a5a","last_reissued_at":"2026-07-05T07:39:09.586271Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:39:09.586271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.07735","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":"2026-07-05T07:39:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m+5XtU+ylhcpKGbRYcOwCt3oXESFyOM/qMWjQN0R6aL1ZSvIgPC5lEe5MUMPwZfAV5T6UFG7FqQTYAIaAzZjBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:36:20.066834Z"},"content_sha256":"c4dfcc37efcb338885a3dca3190cc6c8137af6d061689234c40c8ea173dd6f19","schema_version":"1.0","event_id":"sha256:c4dfcc37efcb338885a3dca3190cc6c8137af6d061689234c40c8ea173dd6f19"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:XJOXO6Y2JORP3NAVNUT2NUNCHN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Discrete Graph Auto-Encoder","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alexandros Kalousis, Magda Gregorova, Yoann Boget","submitted_at":"2023-06-13T12:40:39Z","abstract_excerpt":"Despite advances in generative methods, accurately modeling the distribution of graphs remains a challenging task primarily because of the absence of predefined or inherent unique graph representation. Two main strategies have emerged to tackle this issue: 1) restricting the number of possible representations by sorting the nodes, or 2) using permutation-invariant/equivariant functions, specifically Graph Neural Networks (GNNs).\n  In this paper, we introduce a new framework named Discrete Graph Auto-Encoder (DGAE), which leverages the strengths of both strategies and mitigate their respective "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.07735","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/2306.07735/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":"2026-07-05T07:39:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pyeY4nXF4JlCU2vgUpl1lcvaMIOumA3wGxAiHSm5fdjZ2EWgpjG0ZFqao+92ABbJWYg2R8LbcU7HvCKgmVBzCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:36:20.067514Z"},"content_sha256":"8e7ff00bbfd766092ad2dbf112de6507600a8bd068b7350304973e59b1ff14e3","schema_version":"1.0","event_id":"sha256:8e7ff00bbfd766092ad2dbf112de6507600a8bd068b7350304973e59b1ff14e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XJOXO6Y2JORP3NAVNUT2NUNCHN/bundle.json","state_url":"https://pith.science/pith/XJOXO6Y2JORP3NAVNUT2NUNCHN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XJOXO6Y2JORP3NAVNUT2NUNCHN/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":"2026-08-04T12:36:20Z","links":{"resolver":"https://pith.science/pith/XJOXO6Y2JORP3NAVNUT2NUNCHN","bundle":"https://pith.science/pith/XJOXO6Y2JORP3NAVNUT2NUNCHN/bundle.json","state":"https://pith.science/pith/XJOXO6Y2JORP3NAVNUT2NUNCHN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XJOXO6Y2JORP3NAVNUT2NUNCHN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:XJOXO6Y2JORP3NAVNUT2NUNCHN","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":"df2e342649926abf79485104bdff519703f9dd9dc01c72916e9cf6ba1418afc1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-13T12:40:39Z","title_canon_sha256":"0a88b81a14ef81571f5b5f03fcf4d4337c3b5367e1dd04211ed5e2496a059655"},"schema_version":"1.0","source":{"id":"2306.07735","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.07735","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"arxiv_version","alias_value":"2306.07735v2","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.07735","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"pith_short_12","alias_value":"XJOXO6Y2JORP","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"pith_short_16","alias_value":"XJOXO6Y2JORP3NAV","created_at":"2026-07-05T07:39:09Z"},{"alias_kind":"pith_short_8","alias_value":"XJOXO6Y2","created_at":"2026-07-05T07:39:09Z"}],"graph_snapshots":[{"event_id":"sha256:8e7ff00bbfd766092ad2dbf112de6507600a8bd068b7350304973e59b1ff14e3","target":"graph","created_at":"2026-07-05T07:39:09Z","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/2306.07735/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite advances in generative methods, accurately modeling the distribution of graphs remains a challenging task primarily because of the absence of predefined or inherent unique graph representation. Two main strategies have emerged to tackle this issue: 1) restricting the number of possible representations by sorting the nodes, or 2) using permutation-invariant/equivariant functions, specifically Graph Neural Networks (GNNs).\n  In this paper, we introduce a new framework named Discrete Graph Auto-Encoder (DGAE), which leverages the strengths of both strategies and mitigate their respective ","authors_text":"Alexandros Kalousis, Magda Gregorova, Yoann Boget","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-13T12:40:39Z","title":"Discrete Graph Auto-Encoder"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.07735","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:c4dfcc37efcb338885a3dca3190cc6c8137af6d061689234c40c8ea173dd6f19","target":"record","created_at":"2026-07-05T07:39:09Z","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":"df2e342649926abf79485104bdff519703f9dd9dc01c72916e9cf6ba1418afc1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-13T12:40:39Z","title_canon_sha256":"0a88b81a14ef81571f5b5f03fcf4d4337c3b5367e1dd04211ed5e2496a059655"},"schema_version":"1.0","source":{"id":"2306.07735","kind":"arxiv","version":2}},"canonical_sha256":"ba5d777b1a4ba2fdb4156d27a6d1a23b72c9a13bb441c85e24366fb663972a5a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ba5d777b1a4ba2fdb4156d27a6d1a23b72c9a13bb441c85e24366fb663972a5a","first_computed_at":"2026-07-05T07:39:09.586271Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:39:09.586271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jpUyclPp5aaHJAzinAYPKFHIOStWNig56cQYwPvSqdwaOoEb2Dcm3l7TkWJ3gmMAlb50frK2arBWsBDZ/UyEBw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:39:09.586763Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.07735","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4dfcc37efcb338885a3dca3190cc6c8137af6d061689234c40c8ea173dd6f19","sha256:8e7ff00bbfd766092ad2dbf112de6507600a8bd068b7350304973e59b1ff14e3"],"state_sha256":"2110a8810378bf75327f3a4415cbe5d6435fd5131cc5efd580cbf20944bea161"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O54UlIsL79stG5djnK/64tpHEa6FlwC8fiZf7+wCUMyWGTUu5gHxiEsPirzhIi0NUMnsNd9Vuj18sSTpj+NjDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T12:36:20.073009Z","bundle_sha256":"d859913db89bf9abff1a99ff97ccbd6a21964c43379d6676024129bb17107fb2"}}