{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:KCXTEYBH3BSKBHLYP7ZLBZCTRR","short_pith_number":"pith:KCXTEYBH","canonical_record":{"source":{"id":"2412.05843","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-08T07:41:44Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"862cf1a70abe6c528cba9e9def7dc6bdead52c1b8316ae46283e9d439d739513","abstract_canon_sha256":"9cb3e6d3530036648cedc8424fd90e17df9b7dd51119cebd8eebc95f79b8e50e"},"schema_version":"1.0"},"canonical_sha256":"50af326027d864a09d787ff2b0e4538c5b05c300059b9a6642bc76cfd0b5c567","source":{"kind":"arxiv","id":"2412.05843","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.05843","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"arxiv_version","alias_value":"2412.05843v1","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.05843","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"pith_short_12","alias_value":"KCXTEYBH3BSK","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"pith_short_16","alias_value":"KCXTEYBH3BSKBHLY","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"pith_short_8","alias_value":"KCXTEYBH","created_at":"2026-07-05T09:46:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:KCXTEYBH3BSKBHLYP7ZLBZCTRR","target":"record","payload":{"canonical_record":{"source":{"id":"2412.05843","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-08T07:41:44Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"862cf1a70abe6c528cba9e9def7dc6bdead52c1b8316ae46283e9d439d739513","abstract_canon_sha256":"9cb3e6d3530036648cedc8424fd90e17df9b7dd51119cebd8eebc95f79b8e50e"},"schema_version":"1.0"},"canonical_sha256":"50af326027d864a09d787ff2b0e4538c5b05c300059b9a6642bc76cfd0b5c567","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:46:10.406334Z","signature_b64":"zYiAlR960pppAKTIsq4WMQKE83B/OHVzH5fe8PHcmvR3PlbHl3crZ2zbG48ouAWye+KC7zXBK2U1mqY3+n8TDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"50af326027d864a09d787ff2b0e4538c5b05c300059b9a6642bc76cfd0b5c567","last_reissued_at":"2026-07-05T09:46:10.405838Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:46:10.405838Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.05843","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":"2026-07-05T09:46:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z8lg5nPZqMM8kub1dO5bevNQKCiZXxNS9LFpAQ47IbC6b5IciwPget3TJ6vfk8tRh+bNFZYW1vVKDVFtG9wsDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T16:10:46.873624Z"},"content_sha256":"a5c887bbd60b42231278823141b8390fafec65f09fbabb2b6aebabc1526d0db3","schema_version":"1.0","event_id":"sha256:a5c887bbd60b42231278823141b8390fafec65f09fbabb2b6aebabc1526d0db3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:KCXTEYBH3BSKBHLYP7ZLBZCTRR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Self-Learning Multimodal Approach for Fake News Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Baochen Hu, Hao Chen, Hui Guo, Jinrong Hu, Shu Hu, Siwei Lyu, Xin Wang, Xi Wu","submitted_at":"2024-12-08T07:41:44Z","abstract_excerpt":"The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While machine learning techniques have been widely applied to detect fake news, the scarcity of labeled datasets remains a critical challenge. Misinformation frequently appears as paired text and images, where a news article or headline is accompanied by a related visuals. In this paper, we introduce a self-learning multimodal model for fake news classification. The model leverages contrastive learning, a robust method for fea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.05843","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/2412.05843/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":"2026-07-05T09:46:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"64P2qH2gktU8q5hVrPxGqN9FpH3unXGaxbTDx+aKtQ2/vQ76bwpQiZRxqOV27K1H6zZaa/DDVjPz8lmlBUbFBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T16:10:46.874123Z"},"content_sha256":"62599ae932939a667dc2dab740317fab161a931884a8513e716a93b570673ed9","schema_version":"1.0","event_id":"sha256:62599ae932939a667dc2dab740317fab161a931884a8513e716a93b570673ed9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KCXTEYBH3BSKBHLYP7ZLBZCTRR/bundle.json","state_url":"https://pith.science/pith/KCXTEYBH3BSKBHLYP7ZLBZCTRR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KCXTEYBH3BSKBHLYP7ZLBZCTRR/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":"2026-08-13T16:10:46Z","links":{"resolver":"https://pith.science/pith/KCXTEYBH3BSKBHLYP7ZLBZCTRR","bundle":"https://pith.science/pith/KCXTEYBH3BSKBHLYP7ZLBZCTRR/bundle.json","state":"https://pith.science/pith/KCXTEYBH3BSKBHLYP7ZLBZCTRR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KCXTEYBH3BSKBHLYP7ZLBZCTRR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KCXTEYBH3BSKBHLYP7ZLBZCTRR","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":"9cb3e6d3530036648cedc8424fd90e17df9b7dd51119cebd8eebc95f79b8e50e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-08T07:41:44Z","title_canon_sha256":"862cf1a70abe6c528cba9e9def7dc6bdead52c1b8316ae46283e9d439d739513"},"schema_version":"1.0","source":{"id":"2412.05843","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.05843","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"arxiv_version","alias_value":"2412.05843v1","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.05843","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"pith_short_12","alias_value":"KCXTEYBH3BSK","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"pith_short_16","alias_value":"KCXTEYBH3BSKBHLY","created_at":"2026-07-05T09:46:10Z"},{"alias_kind":"pith_short_8","alias_value":"KCXTEYBH","created_at":"2026-07-05T09:46:10Z"}],"graph_snapshots":[{"event_id":"sha256:62599ae932939a667dc2dab740317fab161a931884a8513e716a93b570673ed9","target":"graph","created_at":"2026-07-05T09:46:10Z","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/2412.05843/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While machine learning techniques have been widely applied to detect fake news, the scarcity of labeled datasets remains a critical challenge. Misinformation frequently appears as paired text and images, where a news article or headline is accompanied by a related visuals. In this paper, we introduce a self-learning multimodal model for fake news classification. The model leverages contrastive learning, a robust method for fea","authors_text":"Baochen Hu, Hao Chen, Hui Guo, Jinrong Hu, Shu Hu, Siwei Lyu, Xin Wang, Xi Wu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-08T07:41:44Z","title":"A Self-Learning Multimodal Approach for Fake News Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.05843","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:a5c887bbd60b42231278823141b8390fafec65f09fbabb2b6aebabc1526d0db3","target":"record","created_at":"2026-07-05T09:46:10Z","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":"9cb3e6d3530036648cedc8424fd90e17df9b7dd51119cebd8eebc95f79b8e50e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-08T07:41:44Z","title_canon_sha256":"862cf1a70abe6c528cba9e9def7dc6bdead52c1b8316ae46283e9d439d739513"},"schema_version":"1.0","source":{"id":"2412.05843","kind":"arxiv","version":1}},"canonical_sha256":"50af326027d864a09d787ff2b0e4538c5b05c300059b9a6642bc76cfd0b5c567","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"50af326027d864a09d787ff2b0e4538c5b05c300059b9a6642bc76cfd0b5c567","first_computed_at":"2026-07-05T09:46:10.405838Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:46:10.405838Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zYiAlR960pppAKTIsq4WMQKE83B/OHVzH5fe8PHcmvR3PlbHl3crZ2zbG48ouAWye+KC7zXBK2U1mqY3+n8TDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:46:10.406334Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.05843","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a5c887bbd60b42231278823141b8390fafec65f09fbabb2b6aebabc1526d0db3","sha256:62599ae932939a667dc2dab740317fab161a931884a8513e716a93b570673ed9"],"state_sha256":"6dad99f7b1ed14c81aaf1a7a896ca84699592a72e3bc01616b9dc7259541aca6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S1YF46mzRjWJOJ9bqXjVMjnX3lVLuWzjxf9HpYvbgC9swt4oCl4sGj3f6cceFhkKwiE1Y6gAZ8PhItaGBiCjDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T16:10:46.879676Z","bundle_sha256":"8fa95c6835826b449a8e62646db053d0c12eac66a57e339d7e96908950251b3a"}}