{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:KUER2LYYI5TQRVWXBPJLZ6MSUL","short_pith_number":"pith:KUER2LYY","canonical_record":{"source":{"id":"2502.05827","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SI","submitted_at":"2025-02-09T09:27:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d9177c5c3478695583bb366305e4be387d429850d759bf0077da5c9d68181007","abstract_canon_sha256":"bb3c342ddb7aeebe47c2a5a7039d4fb367d3509a1685f567568b2cc86d8f0793"},"schema_version":"1.0"},"canonical_sha256":"55091d2f18476708d6d70bd2bcf992a2e5d6fb08f5ff9bf1a75836688742baee","source":{"kind":"arxiv","id":"2502.05827","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.05827","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"arxiv_version","alias_value":"2502.05827v2","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05827","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"pith_short_12","alias_value":"KUER2LYYI5TQ","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"pith_short_16","alias_value":"KUER2LYYI5TQRVWX","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"pith_short_8","alias_value":"KUER2LYY","created_at":"2026-07-05T10:15:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:KUER2LYYI5TQRVWXBPJLZ6MSUL","target":"record","payload":{"canonical_record":{"source":{"id":"2502.05827","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SI","submitted_at":"2025-02-09T09:27:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d9177c5c3478695583bb366305e4be387d429850d759bf0077da5c9d68181007","abstract_canon_sha256":"bb3c342ddb7aeebe47c2a5a7039d4fb367d3509a1685f567568b2cc86d8f0793"},"schema_version":"1.0"},"canonical_sha256":"55091d2f18476708d6d70bd2bcf992a2e5d6fb08f5ff9bf1a75836688742baee","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:15:48.898323Z","signature_b64":"y++jsOUQJrwIuX/ZViuNfkFD7sFBI9Yo0MJLEleOUjvLXaaV2og88VwsaCsjaeHz86jOatGBlhZM1KJGlfkGDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55091d2f18476708d6d70bd2bcf992a2e5d6fb08f5ff9bf1a75836688742baee","last_reissued_at":"2026-07-05T10:15:48.897785Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:15:48.897785Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.05827","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":"2026-07-05T10:15:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RVR7xms87e/3Fj5J+uCX3SJIOFJ6/OUhXl0HQwTboZ2UBqfa9MCpdCnf3Xy+EQ3GzmqPCOYG1wK2IDni9VlxBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T15:07:21.131643Z"},"content_sha256":"b4042c064925dafef3d8a344db1f047972cb183136a133676f0797a44fe656e3","schema_version":"1.0","event_id":"sha256:b4042c064925dafef3d8a344db1f047972cb183136a133676f0797a44fe656e3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:KUER2LYYI5TQRVWXBPJLZ6MSUL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HyGEN: Regularizing Negative Hyperedge Generation for Accurate Hyperedge Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.SI","authors_text":"Da Eun Lee, Sang-Wook Kim, Song Kyung Yu, Yunyong Ko","submitted_at":"2025-02-09T09:27:35Z","abstract_excerpt":"Hyperedge prediction is a fundamental task to predict future high-order relations based on the observed network structure. Existing hyperedge prediction methods, however, suffer from the data sparsity problem. To alleviate this problem, negative sampling methods can be used, which leverage non-existing hyperedges as contrastive information for model training. However, the following important challenges have been rarely studied: (C1) lack of guidance for generating negatives and (C2) possibility of producing false negatives. To address them, we propose a novel hyperedge prediction method, HyGEN"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05827","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/2502.05827/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":"2026-07-05T10:15:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SPNgNqcsY3WzVkDY61w1EEm4biaVQsbgj1wccHvvt73GRyX6zyLKHPT/NGSTR9mDJ/0TbKE/TxIHEdlTK3KgBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T15:07:21.132171Z"},"content_sha256":"5be32eac0bf199f6dd960e1fa989d06dbc26f1da142652364c3eb1e72a91eb0b","schema_version":"1.0","event_id":"sha256:5be32eac0bf199f6dd960e1fa989d06dbc26f1da142652364c3eb1e72a91eb0b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KUER2LYYI5TQRVWXBPJLZ6MSUL/bundle.json","state_url":"https://pith.science/pith/KUER2LYYI5TQRVWXBPJLZ6MSUL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KUER2LYYI5TQRVWXBPJLZ6MSUL/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":"2026-08-20T15:07:21Z","links":{"resolver":"https://pith.science/pith/KUER2LYYI5TQRVWXBPJLZ6MSUL","bundle":"https://pith.science/pith/KUER2LYYI5TQRVWXBPJLZ6MSUL/bundle.json","state":"https://pith.science/pith/KUER2LYYI5TQRVWXBPJLZ6MSUL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KUER2LYYI5TQRVWXBPJLZ6MSUL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:KUER2LYYI5TQRVWXBPJLZ6MSUL","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":"bb3c342ddb7aeebe47c2a5a7039d4fb367d3509a1685f567568b2cc86d8f0793","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SI","submitted_at":"2025-02-09T09:27:35Z","title_canon_sha256":"d9177c5c3478695583bb366305e4be387d429850d759bf0077da5c9d68181007"},"schema_version":"1.0","source":{"id":"2502.05827","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.05827","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"arxiv_version","alias_value":"2502.05827v2","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05827","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"pith_short_12","alias_value":"KUER2LYYI5TQ","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"pith_short_16","alias_value":"KUER2LYYI5TQRVWX","created_at":"2026-07-05T10:15:48Z"},{"alias_kind":"pith_short_8","alias_value":"KUER2LYY","created_at":"2026-07-05T10:15:48Z"}],"graph_snapshots":[{"event_id":"sha256:5be32eac0bf199f6dd960e1fa989d06dbc26f1da142652364c3eb1e72a91eb0b","target":"graph","created_at":"2026-07-05T10:15:48Z","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/2502.05827/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Hyperedge prediction is a fundamental task to predict future high-order relations based on the observed network structure. Existing hyperedge prediction methods, however, suffer from the data sparsity problem. To alleviate this problem, negative sampling methods can be used, which leverage non-existing hyperedges as contrastive information for model training. However, the following important challenges have been rarely studied: (C1) lack of guidance for generating negatives and (C2) possibility of producing false negatives. To address them, we propose a novel hyperedge prediction method, HyGEN","authors_text":"Da Eun Lee, Sang-Wook Kim, Song Kyung Yu, Yunyong Ko","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SI","submitted_at":"2025-02-09T09:27:35Z","title":"HyGEN: Regularizing Negative Hyperedge Generation for Accurate Hyperedge Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05827","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:b4042c064925dafef3d8a344db1f047972cb183136a133676f0797a44fe656e3","target":"record","created_at":"2026-07-05T10:15:48Z","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":"bb3c342ddb7aeebe47c2a5a7039d4fb367d3509a1685f567568b2cc86d8f0793","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SI","submitted_at":"2025-02-09T09:27:35Z","title_canon_sha256":"d9177c5c3478695583bb366305e4be387d429850d759bf0077da5c9d68181007"},"schema_version":"1.0","source":{"id":"2502.05827","kind":"arxiv","version":2}},"canonical_sha256":"55091d2f18476708d6d70bd2bcf992a2e5d6fb08f5ff9bf1a75836688742baee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"55091d2f18476708d6d70bd2bcf992a2e5d6fb08f5ff9bf1a75836688742baee","first_computed_at":"2026-07-05T10:15:48.897785Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:15:48.897785Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"y++jsOUQJrwIuX/ZViuNfkFD7sFBI9Yo0MJLEleOUjvLXaaV2og88VwsaCsjaeHz86jOatGBlhZM1KJGlfkGDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:15:48.898323Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.05827","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b4042c064925dafef3d8a344db1f047972cb183136a133676f0797a44fe656e3","sha256:5be32eac0bf199f6dd960e1fa989d06dbc26f1da142652364c3eb1e72a91eb0b"],"state_sha256":"2db5dad4935d3ca1ac9333f97202131b9789fe2baf37751b3b55042c7cc0e35a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Gkc+ppGkFGNctVf6BTzg0h82Sg6OioRzOhN5/3BoW21r3u0XEClXc+X/vQ3n4tI69Apcub629JQlpd69w9VuAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T15:07:21.136939Z","bundle_sha256":"9b25eac8b5330badae411d1f04a546806e7e11d26d10a526543d13e35fbee653"}}