{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:QHJ36CKUITRKT7PAMCMPTFID2W","short_pith_number":"pith:QHJ36CKU","canonical_record":{"source":{"id":"2605.27023","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-26T13:42:41Z","cross_cats_sorted":[],"title_canon_sha256":"31527227682fb259d56a8d86b3776b321cca7d0d20e377c4d0ce6763ffd8f3b1","abstract_canon_sha256":"9c889de1ddccaee893c4c9ce58b80ef5f7a219e175720c254bf80cff38231fe3"},"schema_version":"1.0"},"canonical_sha256":"81d3bf095444e2a9fde06098f99503d58dcc9528c1dabfc97228a597e7b7e08f","source":{"kind":"arxiv","id":"2605.27023","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.27023","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"arxiv_version","alias_value":"2605.27023v1","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.27023","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"pith_short_12","alias_value":"QHJ36CKUITRK","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"pith_short_16","alias_value":"QHJ36CKUITRKT7PA","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"pith_short_8","alias_value":"QHJ36CKU","created_at":"2026-05-27T01:06:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:QHJ36CKUITRKT7PAMCMPTFID2W","target":"record","payload":{"canonical_record":{"source":{"id":"2605.27023","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-26T13:42:41Z","cross_cats_sorted":[],"title_canon_sha256":"31527227682fb259d56a8d86b3776b321cca7d0d20e377c4d0ce6763ffd8f3b1","abstract_canon_sha256":"9c889de1ddccaee893c4c9ce58b80ef5f7a219e175720c254bf80cff38231fe3"},"schema_version":"1.0"},"canonical_sha256":"81d3bf095444e2a9fde06098f99503d58dcc9528c1dabfc97228a597e7b7e08f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-27T01:06:24.668756Z","signature_b64":"19vFP4jrxN20fwi9aVL2nQ0W2qdRYbS13lYNOk52TD8kyZeX0GFzWmSPghp8wYizkqyaulI/bnk5L1sFGJznAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"81d3bf095444e2a9fde06098f99503d58dcc9528c1dabfc97228a597e7b7e08f","last_reissued_at":"2026-05-27T01:06:24.668207Z","signature_status":"signed_v1","first_computed_at":"2026-05-27T01:06:24.668207Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.27023","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":"2026-05-27T01:06:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WYUe+XHevjbC+S5VRSPhQWNiamKlRK2MEJGBAsTjVgMhG5eQe9jv6FFuOleDvvVrsJoyBGxD+VQe6dgQaTJTCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T02:41:19.698108Z"},"content_sha256":"8b613b9e9bc679ff15f15307ae54029cfe16a0f4e44192b977afbf89bcdc79c4","schema_version":"1.0","event_id":"sha256:8b613b9e9bc679ff15f15307ae54029cfe16a0f4e44192b977afbf89bcdc79c4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:QHJ36CKUITRKT7PAMCMPTFID2W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Boosting Knowledge Graph Foundation Models via Enhanced Negative Sampling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bin Wang, Wenjin Xu, Xiaochun Yang, Yinan Liu, Zhiyuan Zha","submitted_at":"2026-05-26T13:42:41Z","abstract_excerpt":"Knowledge graphs (KGs) have become the core backbone of numerous downstream tasks such as question answering and recommender systems. However, despite all this, KGs are often very incomplete. To perform zero-shot knowledge graph completion in unseen KGs, which have different relational vocabularies from those used for pre-training, KG foundation models (KGFMs) receive a wide range of attention. Existing KGFMs often perform training using random negative triples, which are constructed by replacing the head or tail entity of a positive triple with a random entity. However, these negative triples"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.27023","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/2605.27023/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":"2026-05-27T01:06:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WHxdYNQfHFGzWrrbu405V48BUrQYM9pWvBVWgJk6cgaroQg0yEYhDYSHvVnL2jJCzZKyz+hf1avbtP8upLvsCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T02:41:19.698516Z"},"content_sha256":"d8a844a89fdadaa079ba30830416c7613cee66b9511a7c967928d90399b6e58d","schema_version":"1.0","event_id":"sha256:d8a844a89fdadaa079ba30830416c7613cee66b9511a7c967928d90399b6e58d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QHJ36CKUITRKT7PAMCMPTFID2W/bundle.json","state_url":"https://pith.science/pith/QHJ36CKUITRKT7PAMCMPTFID2W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QHJ36CKUITRKT7PAMCMPTFID2W/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":"2026-06-04T02:41:19Z","links":{"resolver":"https://pith.science/pith/QHJ36CKUITRKT7PAMCMPTFID2W","bundle":"https://pith.science/pith/QHJ36CKUITRKT7PAMCMPTFID2W/bundle.json","state":"https://pith.science/pith/QHJ36CKUITRKT7PAMCMPTFID2W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QHJ36CKUITRKT7PAMCMPTFID2W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:QHJ36CKUITRKT7PAMCMPTFID2W","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":"9c889de1ddccaee893c4c9ce58b80ef5f7a219e175720c254bf80cff38231fe3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-26T13:42:41Z","title_canon_sha256":"31527227682fb259d56a8d86b3776b321cca7d0d20e377c4d0ce6763ffd8f3b1"},"schema_version":"1.0","source":{"id":"2605.27023","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.27023","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"arxiv_version","alias_value":"2605.27023v1","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.27023","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"pith_short_12","alias_value":"QHJ36CKUITRK","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"pith_short_16","alias_value":"QHJ36CKUITRKT7PA","created_at":"2026-05-27T01:06:24Z"},{"alias_kind":"pith_short_8","alias_value":"QHJ36CKU","created_at":"2026-05-27T01:06:24Z"}],"graph_snapshots":[{"event_id":"sha256:d8a844a89fdadaa079ba30830416c7613cee66b9511a7c967928d90399b6e58d","target":"graph","created_at":"2026-05-27T01:06:24Z","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/2605.27023/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Knowledge graphs (KGs) have become the core backbone of numerous downstream tasks such as question answering and recommender systems. However, despite all this, KGs are often very incomplete. To perform zero-shot knowledge graph completion in unseen KGs, which have different relational vocabularies from those used for pre-training, KG foundation models (KGFMs) receive a wide range of attention. Existing KGFMs often perform training using random negative triples, which are constructed by replacing the head or tail entity of a positive triple with a random entity. However, these negative triples","authors_text":"Bin Wang, Wenjin Xu, Xiaochun Yang, Yinan Liu, Zhiyuan Zha","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-26T13:42:41Z","title":"Boosting Knowledge Graph Foundation Models via Enhanced Negative Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.27023","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":"sha256:8b613b9e9bc679ff15f15307ae54029cfe16a0f4e44192b977afbf89bcdc79c4","target":"record","created_at":"2026-05-27T01:06:24Z","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":"9c889de1ddccaee893c4c9ce58b80ef5f7a219e175720c254bf80cff38231fe3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-26T13:42:41Z","title_canon_sha256":"31527227682fb259d56a8d86b3776b321cca7d0d20e377c4d0ce6763ffd8f3b1"},"schema_version":"1.0","source":{"id":"2605.27023","kind":"arxiv","version":1}},"canonical_sha256":"81d3bf095444e2a9fde06098f99503d58dcc9528c1dabfc97228a597e7b7e08f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"81d3bf095444e2a9fde06098f99503d58dcc9528c1dabfc97228a597e7b7e08f","first_computed_at":"2026-05-27T01:06:24.668207Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-27T01:06:24.668207Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"19vFP4jrxN20fwi9aVL2nQ0W2qdRYbS13lYNOk52TD8kyZeX0GFzWmSPghp8wYizkqyaulI/bnk5L1sFGJznAA==","signature_status":"signed_v1","signed_at":"2026-05-27T01:06:24.668756Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.27023","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8b613b9e9bc679ff15f15307ae54029cfe16a0f4e44192b977afbf89bcdc79c4","sha256:d8a844a89fdadaa079ba30830416c7613cee66b9511a7c967928d90399b6e58d"],"state_sha256":"d47f9378828dc52a4425f11d4d1b4fd846763dfbd3e9b23edba551272c643d18"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XR0FemOp5dTMzHVdB4AzanqicIsWE92wtJ3b2/fKjPnTiRBSW19UGL8eC25BWljVw2z2C8fRmeuu4C6BjL7pCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T02:41:19.701373Z","bundle_sha256":"1eb169e08bfd35870de91462954994d6c9df12b048049a3b3013dd584fd20c70"}}