{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4N6ZAPSW2RKOLSFUEKIMH3UYFR","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":"602b94d431fa3adf74eabe17634d42e99c792ecb8c1a46f50ce1e7182d3b788f","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-01-26T04:20:34Z","title_canon_sha256":"e8c52217f8ad21e91722e12df2d16a4b83f45c48cc164ddf1dddac7661c69840"},"schema_version":"1.0","source":{"id":"2501.15393","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.15393","created_at":"2026-07-05T10:05:28Z"},{"alias_kind":"arxiv_version","alias_value":"2501.15393v1","created_at":"2026-07-05T10:05:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.15393","created_at":"2026-07-05T10:05:28Z"},{"alias_kind":"pith_short_12","alias_value":"4N6ZAPSW2RKO","created_at":"2026-07-05T10:05:28Z"},{"alias_kind":"pith_short_16","alias_value":"4N6ZAPSW2RKOLSFU","created_at":"2026-07-05T10:05:28Z"},{"alias_kind":"pith_short_8","alias_value":"4N6ZAPSW","created_at":"2026-07-05T10:05:28Z"}],"graph_snapshots":[{"event_id":"sha256:23b9dfe910c13425138b93e51cb3614d6cef3cd29a8ff2df8cebca010e672d3e","target":"graph","created_at":"2026-07-05T10:05:28Z","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/2501.15393/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal Knowledge Graph Completion (MMKGC) aims to address the critical issue of missing knowledge in multimodal knowledge graphs (MMKGs) for their better applications. However, both the previous MMGKC and negative sampling (NS) approaches ignore the employment of multimodal information to generate diverse and high-quality negative triples from various semantic levels and hardness levels, thereby limiting the effectiveness of training MMKGC models. Thus, we propose a novel Diffusion-based Hierarchical Negative Sampling (DHNS) scheme tailored for MMKGC tasks, which tackles the challenge of g","authors_text":"Guanglin Niu, Xiaowei Zhang","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-01-26T04:20:34Z","title":"Diffusion-based Hierarchical Negative Sampling for Multimodal Knowledge Graph Completion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.15393","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:c722450a7b9d5543e77f52d98e3d11a532f9b5e16922652edb6efc25d4ba13ac","target":"record","created_at":"2026-07-05T10:05:28Z","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":"602b94d431fa3adf74eabe17634d42e99c792ecb8c1a46f50ce1e7182d3b788f","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-01-26T04:20:34Z","title_canon_sha256":"e8c52217f8ad21e91722e12df2d16a4b83f45c48cc164ddf1dddac7661c69840"},"schema_version":"1.0","source":{"id":"2501.15393","kind":"arxiv","version":1}},"canonical_sha256":"e37d903e56d454e5c8b42290c3ee982c4288ad62c75eb3e67a6de33aabea9636","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e37d903e56d454e5c8b42290c3ee982c4288ad62c75eb3e67a6de33aabea9636","first_computed_at":"2026-07-05T10:05:28.647650Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:05:28.647650Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PmAjWQqMN5cC4ugQLpFUPbAWFhxEisox2hNDQHYruweygK7r02lzcX6HQIi8p77yBgcBKzwigdnQ3mubGfNABQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:05:28.648117Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.15393","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c722450a7b9d5543e77f52d98e3d11a532f9b5e16922652edb6efc25d4ba13ac","sha256:23b9dfe910c13425138b93e51cb3614d6cef3cd29a8ff2df8cebca010e672d3e"],"state_sha256":"495cad0dc8a2cc4c20d1a22acab16eee975c740e6c7c4cedc3c1293712d9b474"}