{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:YHHTWR6E4PMEX26EGZCD7PEA6Z","short_pith_number":"pith:YHHTWR6E","canonical_record":{"source":{"id":"2308.04961","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SI","submitted_at":"2023-08-09T13:52:41Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"751dc90e3a81be49106728353fc1f8294fb4388831cca7d20d0f8832c1d8eddd","abstract_canon_sha256":"5d1bb768f8629cffa60a755c75e94586339201d9e3bf22226b03e3b2cbbfad58"},"schema_version":"1.0"},"canonical_sha256":"c1cf3b47c4e3d84bebc436443fbc80f657781b62af0b10dfa6d50a539c0ba159","source":{"kind":"arxiv","id":"2308.04961","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.04961","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"arxiv_version","alias_value":"2308.04961v1","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.04961","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"pith_short_12","alias_value":"YHHTWR6E4PME","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"pith_short_16","alias_value":"YHHTWR6E4PMEX26E","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"pith_short_8","alias_value":"YHHTWR6E","created_at":"2026-07-05T09:08:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:YHHTWR6E4PMEX26EGZCD7PEA6Z","target":"record","payload":{"canonical_record":{"source":{"id":"2308.04961","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SI","submitted_at":"2023-08-09T13:52:41Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"751dc90e3a81be49106728353fc1f8294fb4388831cca7d20d0f8832c1d8eddd","abstract_canon_sha256":"5d1bb768f8629cffa60a755c75e94586339201d9e3bf22226b03e3b2cbbfad58"},"schema_version":"1.0"},"canonical_sha256":"c1cf3b47c4e3d84bebc436443fbc80f657781b62af0b10dfa6d50a539c0ba159","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:08:20.514780Z","signature_b64":"UZryxNjkFkjHNcWSg2zF6ClC3yUyv/F8ATnYpj9LfkFrLkocgvdqfrJk4WLL1NIvJoN4ZJxTDlL9aWovzPuxBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c1cf3b47c4e3d84bebc436443fbc80f657781b62af0b10dfa6d50a539c0ba159","last_reissued_at":"2026-07-05T09:08:20.514279Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:08:20.514279Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.04961","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":"2026-07-05T09:08:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y8RyDSTMgCgr/6miEW9Ein+HvEvSR2sLdqGJQuu6MZPYAd1bwp8Ue7wmGeeSzmPd61iZSibzVWxeJGbm1ROGCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T04:08:11.726289Z"},"content_sha256":"90894ae22763c0c3103efde681aa90837e7f318e12e77c1950ea27a6a9b44d5e","schema_version":"1.0","event_id":"sha256:90894ae22763c0c3103efde681aa90837e7f318e12e77c1950ea27a6a9b44d5e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:YHHTWR6E4PMEX26EGZCD7PEA6Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CasCIFF: A Cross-Domain Information Fusion Framework Tailored for Cascade Prediction in Social Networks","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SI","authors_text":"Chaolong Jia, Hongjun Zhu, Kuo Chen, Shun Yuan, Xin Liu, Ying Qian","submitted_at":"2023-08-09T13:52:41Z","abstract_excerpt":"Existing approaches for information cascade prediction fall into three main categories: feature-driven methods, point process-based methods, and deep learning-based methods. Among them, deep learning-based methods, characterized by its superior learning and representation capabilities, mitigates the shortcomings inherent of the other methods. However, current deep learning methods still face several persistent challenges. In particular, accurate representation of user attributes remains problematic due to factors such as fake followers and complex network configurations. Previous algorithms th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.04961","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/2308.04961/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":"2026-07-05T09:08:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4odxdeBy1BSQ9igoTe0KPhAXB5FBo66SIqixdaIdRRQgQ20aO2B5UoyLfaOO0SkmJRwsT70RQIe1iL+B5iTYCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T04:08:11.726776Z"},"content_sha256":"f44b631cad8f8b0b4b5184cde5e9820df38d0caf115d5ba0f9199f1b4c3d28ed","schema_version":"1.0","event_id":"sha256:f44b631cad8f8b0b4b5184cde5e9820df38d0caf115d5ba0f9199f1b4c3d28ed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YHHTWR6E4PMEX26EGZCD7PEA6Z/bundle.json","state_url":"https://pith.science/pith/YHHTWR6E4PMEX26EGZCD7PEA6Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YHHTWR6E4PMEX26EGZCD7PEA6Z/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":"2026-08-23T04:08:11Z","links":{"resolver":"https://pith.science/pith/YHHTWR6E4PMEX26EGZCD7PEA6Z","bundle":"https://pith.science/pith/YHHTWR6E4PMEX26EGZCD7PEA6Z/bundle.json","state":"https://pith.science/pith/YHHTWR6E4PMEX26EGZCD7PEA6Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YHHTWR6E4PMEX26EGZCD7PEA6Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:YHHTWR6E4PMEX26EGZCD7PEA6Z","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":"5d1bb768f8629cffa60a755c75e94586339201d9e3bf22226b03e3b2cbbfad58","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SI","submitted_at":"2023-08-09T13:52:41Z","title_canon_sha256":"751dc90e3a81be49106728353fc1f8294fb4388831cca7d20d0f8832c1d8eddd"},"schema_version":"1.0","source":{"id":"2308.04961","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.04961","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"arxiv_version","alias_value":"2308.04961v1","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.04961","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"pith_short_12","alias_value":"YHHTWR6E4PME","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"pith_short_16","alias_value":"YHHTWR6E4PMEX26E","created_at":"2026-07-05T09:08:20Z"},{"alias_kind":"pith_short_8","alias_value":"YHHTWR6E","created_at":"2026-07-05T09:08:20Z"}],"graph_snapshots":[{"event_id":"sha256:f44b631cad8f8b0b4b5184cde5e9820df38d0caf115d5ba0f9199f1b4c3d28ed","target":"graph","created_at":"2026-07-05T09:08:20Z","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/2308.04961/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Existing approaches for information cascade prediction fall into three main categories: feature-driven methods, point process-based methods, and deep learning-based methods. Among them, deep learning-based methods, characterized by its superior learning and representation capabilities, mitigates the shortcomings inherent of the other methods. However, current deep learning methods still face several persistent challenges. In particular, accurate representation of user attributes remains problematic due to factors such as fake followers and complex network configurations. Previous algorithms th","authors_text":"Chaolong Jia, Hongjun Zhu, Kuo Chen, Shun Yuan, Xin Liu, Ying Qian","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SI","submitted_at":"2023-08-09T13:52:41Z","title":"CasCIFF: A Cross-Domain Information Fusion Framework Tailored for Cascade Prediction in Social Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.04961","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":"sha256:90894ae22763c0c3103efde681aa90837e7f318e12e77c1950ea27a6a9b44d5e","target":"record","created_at":"2026-07-05T09:08:20Z","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":"5d1bb768f8629cffa60a755c75e94586339201d9e3bf22226b03e3b2cbbfad58","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SI","submitted_at":"2023-08-09T13:52:41Z","title_canon_sha256":"751dc90e3a81be49106728353fc1f8294fb4388831cca7d20d0f8832c1d8eddd"},"schema_version":"1.0","source":{"id":"2308.04961","kind":"arxiv","version":1}},"canonical_sha256":"c1cf3b47c4e3d84bebc436443fbc80f657781b62af0b10dfa6d50a539c0ba159","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c1cf3b47c4e3d84bebc436443fbc80f657781b62af0b10dfa6d50a539c0ba159","first_computed_at":"2026-07-05T09:08:20.514279Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:08:20.514279Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UZryxNjkFkjHNcWSg2zF6ClC3yUyv/F8ATnYpj9LfkFrLkocgvdqfrJk4WLL1NIvJoN4ZJxTDlL9aWovzPuxBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:08:20.514780Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.04961","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:90894ae22763c0c3103efde681aa90837e7f318e12e77c1950ea27a6a9b44d5e","sha256:f44b631cad8f8b0b4b5184cde5e9820df38d0caf115d5ba0f9199f1b4c3d28ed"],"state_sha256":"5068f1eb66725fa2d6240e80245078e15dc86bd9b4df9f612bb4c15143cd9309"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S5vBOt55ubLI5Y49mYbH6tFn99GoGRHOH+neRk5RLXJFc51hEwzs9wjzXCD855lc7/zNKzE/9jja5YswTh39CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T04:08:11.730575Z","bundle_sha256":"1db56d7030f7c31f94b946e5733a114d06548549b075014dd37e7344ad02b847"}}