{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:OVGMHULJ7OKVRGWDXVIJHPHMRV","short_pith_number":"pith:OVGMHULJ","canonical_record":{"source":{"id":"2304.04300","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-09T19:21:46Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e75b284501823c8416b4a7e86986d9cc15ea4ad60634fa69e1982b3051231ed0","abstract_canon_sha256":"f33efc865c20586ec751447814d7087614e4d6ccf28f3fb2df850f597756b77c"},"schema_version":"1.0"},"canonical_sha256":"754cc3d169fb95589ac3bd5093bcec8d41c368ce44a086379b50429b9d71fc70","source":{"kind":"arxiv","id":"2304.04300","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.04300","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"arxiv_version","alias_value":"2304.04300v1","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.04300","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"pith_short_12","alias_value":"OVGMHULJ7OKV","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"pith_short_16","alias_value":"OVGMHULJ7OKVRGWD","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"pith_short_8","alias_value":"OVGMHULJ","created_at":"2026-07-05T05:59:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:OVGMHULJ7OKVRGWDXVIJHPHMRV","target":"record","payload":{"canonical_record":{"source":{"id":"2304.04300","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-09T19:21:46Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e75b284501823c8416b4a7e86986d9cc15ea4ad60634fa69e1982b3051231ed0","abstract_canon_sha256":"f33efc865c20586ec751447814d7087614e4d6ccf28f3fb2df850f597756b77c"},"schema_version":"1.0"},"canonical_sha256":"754cc3d169fb95589ac3bd5093bcec8d41c368ce44a086379b50429b9d71fc70","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:59:24.804650Z","signature_b64":"Fuobz+yhFm67r+fLuaQraejNSdikKCQxG79jk3scdk/lDXFC8qO80T5I0wAg2BmLafunvhm2yVp30xY9NmGyAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"754cc3d169fb95589ac3bd5093bcec8d41c368ce44a086379b50429b9d71fc70","last_reissued_at":"2026-07-05T05:59:24.804249Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:59:24.804249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.04300","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":"2026-07-05T05:59:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qAEfUuKaFFMWS94oUCNRRhcag6/a8kjNVroVkq6EJfCv2VJoOjhF8eFcHoYG7s3fdP8FM90TeIc7d5Ah7rxWBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T04:59:39.656931Z"},"content_sha256":"56140704ef9e3157838a8df8fc19bc3741238f014688105b97da4398fc8b22e8","schema_version":"1.0","event_id":"sha256:56140704ef9e3157838a8df8fc19bc3741238f014688105b97da4398fc8b22e8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:OVGMHULJ7OKVRGWDXVIJHPHMRV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Class-Imbalanced Learning on Graphs: A Survey","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Nitesh V. Chawla, Nuno Moniz, Yihong Ma, Yijun Tian","submitted_at":"2023-04-09T19:21:46Z","abstract_excerpt":"The rapid advancement in data-driven research has increased the demand for effective graph data analysis. However, real-world data often exhibits class imbalance, leading to poor performance of machine learning models. To overcome this challenge, class-imbalanced learning on graphs (CILG) has emerged as a promising solution that combines the strengths of graph representation learning and class-imbalanced learning. In recent years, significant progress has been made in CILG. Anticipating that such a trend will continue, this survey aims to offer a comprehensive understanding of the current stat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.04300","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/2304.04300/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":"2026-07-05T05:59:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jCyq1oPzdvR2nr5qXj5g16r3TJAnaO1RfDZO6PXTEEmlI/UqN15sFfFLt/H0ymszdMrJ2Fq9DjgjV0yrYa/qCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T04:59:39.657396Z"},"content_sha256":"e516931390e5c1dbb014296be4ae798c5a495d4c0db8afdf6d1bae6d3d999450","schema_version":"1.0","event_id":"sha256:e516931390e5c1dbb014296be4ae798c5a495d4c0db8afdf6d1bae6d3d999450"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OVGMHULJ7OKVRGWDXVIJHPHMRV/bundle.json","state_url":"https://pith.science/pith/OVGMHULJ7OKVRGWDXVIJHPHMRV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OVGMHULJ7OKVRGWDXVIJHPHMRV/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":"2026-08-05T04:59:39Z","links":{"resolver":"https://pith.science/pith/OVGMHULJ7OKVRGWDXVIJHPHMRV","bundle":"https://pith.science/pith/OVGMHULJ7OKVRGWDXVIJHPHMRV/bundle.json","state":"https://pith.science/pith/OVGMHULJ7OKVRGWDXVIJHPHMRV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OVGMHULJ7OKVRGWDXVIJHPHMRV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:OVGMHULJ7OKVRGWDXVIJHPHMRV","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":"f33efc865c20586ec751447814d7087614e4d6ccf28f3fb2df850f597756b77c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-09T19:21:46Z","title_canon_sha256":"e75b284501823c8416b4a7e86986d9cc15ea4ad60634fa69e1982b3051231ed0"},"schema_version":"1.0","source":{"id":"2304.04300","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.04300","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"arxiv_version","alias_value":"2304.04300v1","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.04300","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"pith_short_12","alias_value":"OVGMHULJ7OKV","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"pith_short_16","alias_value":"OVGMHULJ7OKVRGWD","created_at":"2026-07-05T05:59:24Z"},{"alias_kind":"pith_short_8","alias_value":"OVGMHULJ","created_at":"2026-07-05T05:59:24Z"}],"graph_snapshots":[{"event_id":"sha256:e516931390e5c1dbb014296be4ae798c5a495d4c0db8afdf6d1bae6d3d999450","target":"graph","created_at":"2026-07-05T05:59:24Z","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/2304.04300/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The rapid advancement in data-driven research has increased the demand for effective graph data analysis. However, real-world data often exhibits class imbalance, leading to poor performance of machine learning models. To overcome this challenge, class-imbalanced learning on graphs (CILG) has emerged as a promising solution that combines the strengths of graph representation learning and class-imbalanced learning. In recent years, significant progress has been made in CILG. Anticipating that such a trend will continue, this survey aims to offer a comprehensive understanding of the current stat","authors_text":"Nitesh V. Chawla, Nuno Moniz, Yihong Ma, Yijun Tian","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-09T19:21:46Z","title":"Class-Imbalanced Learning on Graphs: A Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.04300","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":"sha256:56140704ef9e3157838a8df8fc19bc3741238f014688105b97da4398fc8b22e8","target":"record","created_at":"2026-07-05T05:59:24Z","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":"f33efc865c20586ec751447814d7087614e4d6ccf28f3fb2df850f597756b77c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-09T19:21:46Z","title_canon_sha256":"e75b284501823c8416b4a7e86986d9cc15ea4ad60634fa69e1982b3051231ed0"},"schema_version":"1.0","source":{"id":"2304.04300","kind":"arxiv","version":1}},"canonical_sha256":"754cc3d169fb95589ac3bd5093bcec8d41c368ce44a086379b50429b9d71fc70","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"754cc3d169fb95589ac3bd5093bcec8d41c368ce44a086379b50429b9d71fc70","first_computed_at":"2026-07-05T05:59:24.804249Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:59:24.804249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Fuobz+yhFm67r+fLuaQraejNSdikKCQxG79jk3scdk/lDXFC8qO80T5I0wAg2BmLafunvhm2yVp30xY9NmGyAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:59:24.804650Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.04300","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:56140704ef9e3157838a8df8fc19bc3741238f014688105b97da4398fc8b22e8","sha256:e516931390e5c1dbb014296be4ae798c5a495d4c0db8afdf6d1bae6d3d999450"],"state_sha256":"aaeeba939205027e642bedaa4a76d8846142c03420ffd3192458a8b4145296f7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WjzZrn9diZ9VuklAW0qjLLS4zRo57H0p5vMZ8Dn/1EtIOMXQN5dKkq19derkZOnM4vESOir6o8bTW4qMj8lnAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T04:59:39.660771Z","bundle_sha256":"f2c65940d030dc1637c15ebc2c8fcc4e58668fdad4fc343963b17dc94517d1a2"}}