{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:5MKCTK7KDYTLK7FGX7ASPYFSFB","short_pith_number":"pith:5MKCTK7K","canonical_record":{"source":{"id":"2401.17123","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:53:34Z","cross_cats_sorted":["cs.AI","q-bio.QM"],"title_canon_sha256":"cce02f93ad07a356ed8e242ff009baae882fcb52eb49645d1484e0690434ceed","abstract_canon_sha256":"ed3cea8c73ec4f8ee31e38e81e782edee5393150465108575bc2471bbb5aadc4"},"schema_version":"1.0"},"canonical_sha256":"eb1429abea1e26b57ca6bfc127e0b2287eed436930245be49891459d4e859c2c","source":{"kind":"arxiv","id":"2401.17123","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.17123","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"arxiv_version","alias_value":"2401.17123v1","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.17123","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"pith_short_12","alias_value":"5MKCTK7KDYTL","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"pith_short_16","alias_value":"5MKCTK7KDYTLK7FG","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"pith_short_8","alias_value":"5MKCTK7K","created_at":"2026-07-05T07:39:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:5MKCTK7KDYTLK7FGX7ASPYFSFB","target":"record","payload":{"canonical_record":{"source":{"id":"2401.17123","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:53:34Z","cross_cats_sorted":["cs.AI","q-bio.QM"],"title_canon_sha256":"cce02f93ad07a356ed8e242ff009baae882fcb52eb49645d1484e0690434ceed","abstract_canon_sha256":"ed3cea8c73ec4f8ee31e38e81e782edee5393150465108575bc2471bbb5aadc4"},"schema_version":"1.0"},"canonical_sha256":"eb1429abea1e26b57ca6bfc127e0b2287eed436930245be49891459d4e859c2c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:39:19.668415Z","signature_b64":"oUo1bm22WP/vfGM32WITqjhDWKHncZstIlBIQTfKGiQCfcRMc89zD/i9VAR9j53kKxlzB2zTST1XLiLjUapXBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eb1429abea1e26b57ca6bfc127e0b2287eed436930245be49891459d4e859c2c","last_reissued_at":"2026-07-05T07:39:19.668025Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:39:19.668025Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.17123","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":"2026-07-05T07:39:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GiOERyqb3+0omgqZmF5PABIRkSk8BrSafbT9RKoFfuAF42FWWVumzxZSU4zbIB2c1uW+zJJCYXpKcI7ra1N7BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T12:03:37.057365Z"},"content_sha256":"e5e1660bee059463be9e0213d2163e2f020976f0363d3720d6d51441d9f8d53b","schema_version":"1.0","event_id":"sha256:e5e1660bee059463be9e0213d2163e2f020976f0363d3720d6d51441d9f8d53b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:5MKCTK7KDYTLK7FGX7ASPYFSFB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","q-bio.QM"],"primary_cat":"cs.LG","authors_text":"Bolei Zhou, Chengpeng Wang, Hanchen Wang, Jian Tang, Jiarui Lu, Shengchao Liu, Weili Nie, Zhuoxinran Li","submitted_at":"2024-01-29T18:53:34Z","abstract_excerpt":"Deep generative models (DGMs) have been widely developed for graph data. However, much less investigation has been carried out on understanding the latent space of such pretrained graph DGMs. These understandings possess the potential to provide constructive guidelines for crucial tasks, such as graph controllable generation. Thus in this work, we are interested in studying this problem and propose GraphCG, a method for the unsupervised discovery of steerable factors in the latent space of pretrained graph DGMs. We first examine the representation space of three pretrained graph DGMs with six "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.17123","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/2401.17123/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":"2026-07-05T07:39:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QTNOJ9qJGUtTLGG7263mcQ8xE3k8Rovo3KYA8vbkOvmydOVqKA6zyD3theQTUOcRkjenHwlWiziCi63/JE81Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T12:03:37.059588Z"},"content_sha256":"074525045c956dfd83175fcd872fc1e2716820cfd16da6a8b51715037901fc27","schema_version":"1.0","event_id":"sha256:074525045c956dfd83175fcd872fc1e2716820cfd16da6a8b51715037901fc27"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5MKCTK7KDYTLK7FGX7ASPYFSFB/bundle.json","state_url":"https://pith.science/pith/5MKCTK7KDYTLK7FGX7ASPYFSFB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5MKCTK7KDYTLK7FGX7ASPYFSFB/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":"2026-08-05T12:03:37Z","links":{"resolver":"https://pith.science/pith/5MKCTK7KDYTLK7FGX7ASPYFSFB","bundle":"https://pith.science/pith/5MKCTK7KDYTLK7FGX7ASPYFSFB/bundle.json","state":"https://pith.science/pith/5MKCTK7KDYTLK7FGX7ASPYFSFB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5MKCTK7KDYTLK7FGX7ASPYFSFB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5MKCTK7KDYTLK7FGX7ASPYFSFB","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":"ed3cea8c73ec4f8ee31e38e81e782edee5393150465108575bc2471bbb5aadc4","cross_cats_sorted":["cs.AI","q-bio.QM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:53:34Z","title_canon_sha256":"cce02f93ad07a356ed8e242ff009baae882fcb52eb49645d1484e0690434ceed"},"schema_version":"1.0","source":{"id":"2401.17123","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.17123","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"arxiv_version","alias_value":"2401.17123v1","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.17123","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"pith_short_12","alias_value":"5MKCTK7KDYTL","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"pith_short_16","alias_value":"5MKCTK7KDYTLK7FG","created_at":"2026-07-05T07:39:19Z"},{"alias_kind":"pith_short_8","alias_value":"5MKCTK7K","created_at":"2026-07-05T07:39:19Z"}],"graph_snapshots":[{"event_id":"sha256:074525045c956dfd83175fcd872fc1e2716820cfd16da6a8b51715037901fc27","target":"graph","created_at":"2026-07-05T07:39:19Z","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/2401.17123/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep generative models (DGMs) have been widely developed for graph data. However, much less investigation has been carried out on understanding the latent space of such pretrained graph DGMs. These understandings possess the potential to provide constructive guidelines for crucial tasks, such as graph controllable generation. Thus in this work, we are interested in studying this problem and propose GraphCG, a method for the unsupervised discovery of steerable factors in the latent space of pretrained graph DGMs. We first examine the representation space of three pretrained graph DGMs with six ","authors_text":"Bolei Zhou, Chengpeng Wang, Hanchen Wang, Jian Tang, Jiarui Lu, Shengchao Liu, Weili Nie, Zhuoxinran Li","cross_cats":["cs.AI","q-bio.QM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:53:34Z","title":"Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.17123","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:e5e1660bee059463be9e0213d2163e2f020976f0363d3720d6d51441d9f8d53b","target":"record","created_at":"2026-07-05T07:39:19Z","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":"ed3cea8c73ec4f8ee31e38e81e782edee5393150465108575bc2471bbb5aadc4","cross_cats_sorted":["cs.AI","q-bio.QM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:53:34Z","title_canon_sha256":"cce02f93ad07a356ed8e242ff009baae882fcb52eb49645d1484e0690434ceed"},"schema_version":"1.0","source":{"id":"2401.17123","kind":"arxiv","version":1}},"canonical_sha256":"eb1429abea1e26b57ca6bfc127e0b2287eed436930245be49891459d4e859c2c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eb1429abea1e26b57ca6bfc127e0b2287eed436930245be49891459d4e859c2c","first_computed_at":"2026-07-05T07:39:19.668025Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:39:19.668025Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oUo1bm22WP/vfGM32WITqjhDWKHncZstIlBIQTfKGiQCfcRMc89zD/i9VAR9j53kKxlzB2zTST1XLiLjUapXBw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:39:19.668415Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.17123","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e5e1660bee059463be9e0213d2163e2f020976f0363d3720d6d51441d9f8d53b","sha256:074525045c956dfd83175fcd872fc1e2716820cfd16da6a8b51715037901fc27"],"state_sha256":"00de0bf5c6e59390129b70508719df470c88cdd4f8d281e49cd5cd12ca50c93e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G2Zlp/KbDHX/baXP/auVXn6J8r2NHwJyhYsDPLV3wnmV/5VMGBYkUVHWTaVrQDosvAFLrCQ3w+rW6Qud6WQLCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T12:03:37.068391Z","bundle_sha256":"24f523e2e00334c535f8a1ed766545f500bbe2c3a8c206250ba0bb383e2befdd"}}