{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:S7XVWCGYUDHNNE6EXFIWTOT3LF","short_pith_number":"pith:S7XVWCGY","canonical_record":{"source":{"id":"2110.14854","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T02:26:18Z","cross_cats_sorted":[],"title_canon_sha256":"5879c563d066b2ad9cc54dda9cfe10c7c918d2df3ec453bfcade3f8424465344","abstract_canon_sha256":"7c1caa6443275f566b96bac4abd921e57d99edc65c82d4a089f115ee85ae3449"},"schema_version":"1.0"},"canonical_sha256":"97ef5b08d8a0ced693c4b95169ba7b5965a879f4793d6120b492df073918bbbd","source":{"kind":"arxiv","id":"2110.14854","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.14854","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"arxiv_version","alias_value":"2110.14854v1","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.14854","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"pith_short_12","alias_value":"S7XVWCGYUDHN","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"pith_short_16","alias_value":"S7XVWCGYUDHNNE6E","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"pith_short_8","alias_value":"S7XVWCGY","created_at":"2026-07-05T03:26:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:S7XVWCGYUDHNNE6EXFIWTOT3LF","target":"record","payload":{"canonical_record":{"source":{"id":"2110.14854","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T02:26:18Z","cross_cats_sorted":[],"title_canon_sha256":"5879c563d066b2ad9cc54dda9cfe10c7c918d2df3ec453bfcade3f8424465344","abstract_canon_sha256":"7c1caa6443275f566b96bac4abd921e57d99edc65c82d4a089f115ee85ae3449"},"schema_version":"1.0"},"canonical_sha256":"97ef5b08d8a0ced693c4b95169ba7b5965a879f4793d6120b492df073918bbbd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:26:48.335942Z","signature_b64":"bqHyQPkg8vNdUGdVtrDusDiAAnBmN6NG/lxXyF1mxuXS4osGjnumF/OslRlGdCCmXOTxdNlf/ujiFBoc0rwOAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97ef5b08d8a0ced693c4b95169ba7b5965a879f4793d6120b492df073918bbbd","last_reissued_at":"2026-07-05T03:26:48.335295Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:26:48.335295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.14854","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":"2026-07-05T03:26:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VGa42mNPDQGpIJ4jxdgQpctKVbZvAowSsQrH1cvdq5QhIJRhISq2qtcEKpCHrlhUt3QzNbH0gDaoNpxVcS+LCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:46:56.490883Z"},"content_sha256":"3744fbd42116f9bf188605412b8184c82f53d4235a420656e744811b212da9f2","schema_version":"1.0","event_id":"sha256:3744fbd42116f9bf188605412b8184c82f53d4235a420656e744811b212da9f2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:S7XVWCGYUDHNNE6EXFIWTOT3LF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RIM: Reliable Influence-based Active Learning on Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Bin Cui, Jiulong Shan, Meng Cao, Ping Huang, Wentao Zhang, Yexin Wang, Zhenbang You, Zhi Yang","submitted_at":"2021-10-28T02:26:18Z","abstract_excerpt":"Message passing is the core of most graph models such as Graph Convolutional Network (GCN) and Label Propagation (LP), which usually require a large number of clean labeled data to smooth out the neighborhood over the graph. However, the labeling process can be tedious, costly, and error-prone in practice. In this paper, we propose to unify active learning (AL) and message passing towards minimizing labeling costs, e.g., making use of few and unreliable labels that can be obtained cheaply. We make two contributions towards that end. First, we open up a perspective by drawing a connection betwe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.14854","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/2110.14854/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":"2026-07-05T03:26:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gUkdbxKNHg1GxbGZLSjc4/7jiKj/3GzUAXn0m/34OMg7H5j0jrA8d0QKZfF0u2o74DRYz0sg+jhjYje8Pj00DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:46:56.491256Z"},"content_sha256":"4327d09baee1c63ccf5be6bdee9bd596b8dfc67ba10cb77a345837c83a7ddcd1","schema_version":"1.0","event_id":"sha256:4327d09baee1c63ccf5be6bdee9bd596b8dfc67ba10cb77a345837c83a7ddcd1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S7XVWCGYUDHNNE6EXFIWTOT3LF/bundle.json","state_url":"https://pith.science/pith/S7XVWCGYUDHNNE6EXFIWTOT3LF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S7XVWCGYUDHNNE6EXFIWTOT3LF/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":"2026-07-06T17:46:56Z","links":{"resolver":"https://pith.science/pith/S7XVWCGYUDHNNE6EXFIWTOT3LF","bundle":"https://pith.science/pith/S7XVWCGYUDHNNE6EXFIWTOT3LF/bundle.json","state":"https://pith.science/pith/S7XVWCGYUDHNNE6EXFIWTOT3LF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S7XVWCGYUDHNNE6EXFIWTOT3LF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:S7XVWCGYUDHNNE6EXFIWTOT3LF","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":"7c1caa6443275f566b96bac4abd921e57d99edc65c82d4a089f115ee85ae3449","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T02:26:18Z","title_canon_sha256":"5879c563d066b2ad9cc54dda9cfe10c7c918d2df3ec453bfcade3f8424465344"},"schema_version":"1.0","source":{"id":"2110.14854","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.14854","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"arxiv_version","alias_value":"2110.14854v1","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.14854","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"pith_short_12","alias_value":"S7XVWCGYUDHN","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"pith_short_16","alias_value":"S7XVWCGYUDHNNE6E","created_at":"2026-07-05T03:26:48Z"},{"alias_kind":"pith_short_8","alias_value":"S7XVWCGY","created_at":"2026-07-05T03:26:48Z"}],"graph_snapshots":[{"event_id":"sha256:4327d09baee1c63ccf5be6bdee9bd596b8dfc67ba10cb77a345837c83a7ddcd1","target":"graph","created_at":"2026-07-05T03:26:48Z","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/2110.14854/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Message passing is the core of most graph models such as Graph Convolutional Network (GCN) and Label Propagation (LP), which usually require a large number of clean labeled data to smooth out the neighborhood over the graph. However, the labeling process can be tedious, costly, and error-prone in practice. In this paper, we propose to unify active learning (AL) and message passing towards minimizing labeling costs, e.g., making use of few and unreliable labels that can be obtained cheaply. We make two contributions towards that end. First, we open up a perspective by drawing a connection betwe","authors_text":"Bin Cui, Jiulong Shan, Meng Cao, Ping Huang, Wentao Zhang, Yexin Wang, Zhenbang You, Zhi Yang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T02:26:18Z","title":"RIM: Reliable Influence-based Active Learning on Graphs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.14854","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":"sha256:3744fbd42116f9bf188605412b8184c82f53d4235a420656e744811b212da9f2","target":"record","created_at":"2026-07-05T03:26:48Z","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":"7c1caa6443275f566b96bac4abd921e57d99edc65c82d4a089f115ee85ae3449","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T02:26:18Z","title_canon_sha256":"5879c563d066b2ad9cc54dda9cfe10c7c918d2df3ec453bfcade3f8424465344"},"schema_version":"1.0","source":{"id":"2110.14854","kind":"arxiv","version":1}},"canonical_sha256":"97ef5b08d8a0ced693c4b95169ba7b5965a879f4793d6120b492df073918bbbd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97ef5b08d8a0ced693c4b95169ba7b5965a879f4793d6120b492df073918bbbd","first_computed_at":"2026-07-05T03:26:48.335295Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:26:48.335295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bqHyQPkg8vNdUGdVtrDusDiAAnBmN6NG/lxXyF1mxuXS4osGjnumF/OslRlGdCCmXOTxdNlf/ujiFBoc0rwOAg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:26:48.335942Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.14854","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3744fbd42116f9bf188605412b8184c82f53d4235a420656e744811b212da9f2","sha256:4327d09baee1c63ccf5be6bdee9bd596b8dfc67ba10cb77a345837c83a7ddcd1"],"state_sha256":"d3461158b2a5dbb6d9b52b26c0d597753962e1d6c49c2d6dc437b707c400b8db"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XmX8FQaaQYObvvbKXkTSu6C5w7WlEv7Co+oD+55zksM69BnCaclMD4C9iOXUh8jqhsEAgSgZNrUu4jYIE6VNAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T17:46:56.493409Z","bundle_sha256":"a7a093e8d83926c74c3837532319dc285c322553d2e0a0b68f75199c867a0713"}}