{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:XU5EKCIFARUWB6J7XPHYSEL2I5","short_pith_number":"pith:XU5EKCIF","canonical_record":{"source":{"id":"2407.00556","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MM","submitted_at":"2024-06-30T01:18:37Z","cross_cats_sorted":[],"title_canon_sha256":"fdcae96f4e5fd2b3d1927a30ab0acf1b8bfe297681fda56c78f684d51e1a492a","abstract_canon_sha256":"7f16fdf27544e5889b6bef387ed22d7861179a3f16634df71e5c84d3e418829c"},"schema_version":"1.0"},"canonical_sha256":"bd3a450905046960f93fbbcf89117a47419610eceb9fdae50b99154f303d0a19","source":{"kind":"arxiv","id":"2407.00556","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.00556","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"arxiv_version","alias_value":"2407.00556v1","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.00556","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"pith_short_12","alias_value":"XU5EKCIFARUW","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"pith_short_16","alias_value":"XU5EKCIFARUWB6J7","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"pith_short_8","alias_value":"XU5EKCIF","created_at":"2026-07-05T08:38:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:XU5EKCIFARUWB6J7XPHYSEL2I5","target":"record","payload":{"canonical_record":{"source":{"id":"2407.00556","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MM","submitted_at":"2024-06-30T01:18:37Z","cross_cats_sorted":[],"title_canon_sha256":"fdcae96f4e5fd2b3d1927a30ab0acf1b8bfe297681fda56c78f684d51e1a492a","abstract_canon_sha256":"7f16fdf27544e5889b6bef387ed22d7861179a3f16634df71e5c84d3e418829c"},"schema_version":"1.0"},"canonical_sha256":"bd3a450905046960f93fbbcf89117a47419610eceb9fdae50b99154f303d0a19","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:38:21.314515Z","signature_b64":"WFsXjOmNgRkNoZ/tCmhPh6DI7wm0d80//5L0coZclKuMeDL5043+FXumSy3cBafHGo5fJvSPYZD7Y8tUBOWSAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bd3a450905046960f93fbbcf89117a47419610eceb9fdae50b99154f303d0a19","last_reissued_at":"2026-07-05T08:38:21.314101Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:38:21.314101Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.00556","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":"2026-07-05T08:38:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1xE3DcfTYvAt5bOKqVMIAwPQsxm50eGL5j5+06oPibn34MUtfnZ4MiE96bQftUPxRffada7MzYMnj1MvDEfuDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T21:34:17.315680Z"},"content_sha256":"5b40b9e32893f607db93a54d77dc32f2b35441958f80f26efb4b7bbe61a370de","schema_version":"1.0","event_id":"sha256:5b40b9e32893f607db93a54d77dc32f2b35441958f80f26efb4b7bbe61a370de"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:XU5EKCIFARUWB6J7XPHYSEL2I5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisiting Vision-Language Features Adaptation and Inconsistency for Social Media Popularity Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.MM","authors_text":"Chia-Ming Lee, Chi-Han Tsai, Chih-Chung Hsu, Chih-Yu Jian, Yi-Shiuan Chou, Yu-Fan Lin","submitted_at":"2024-06-30T01:18:37Z","abstract_excerpt":"Social media popularity (SMP) prediction is a complex task involving multi-modal data integration. While pre-trained vision-language models (VLMs) like CLIP have been widely adopted for this task, their effectiveness in capturing the unique characteristics of social media content remains unexplored. This paper critically examines the applicability of CLIP-based features in SMP prediction, focusing on the overlooked phenomenon of semantic inconsistency between images and text in social media posts. Through extensive analysis, we demonstrate that this inconsistency increases with post popularity"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.00556","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/2407.00556/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":"2026-07-05T08:38:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"moNwpGHXFR8ui5kjt3owdkj+FM2DB3WZFiGO76NaP2MT/mEyfgHYQGPTtQ6BzEFTS4QsBS8BBjrR2EuM0Q6oBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T21:34:17.316183Z"},"content_sha256":"4da786489b1eda8f5a358f1462515a45b87d431e40bd10a77c3021db9454ceac","schema_version":"1.0","event_id":"sha256:4da786489b1eda8f5a358f1462515a45b87d431e40bd10a77c3021db9454ceac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XU5EKCIFARUWB6J7XPHYSEL2I5/bundle.json","state_url":"https://pith.science/pith/XU5EKCIFARUWB6J7XPHYSEL2I5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XU5EKCIFARUWB6J7XPHYSEL2I5/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":"2026-08-08T21:34:17Z","links":{"resolver":"https://pith.science/pith/XU5EKCIFARUWB6J7XPHYSEL2I5","bundle":"https://pith.science/pith/XU5EKCIFARUWB6J7XPHYSEL2I5/bundle.json","state":"https://pith.science/pith/XU5EKCIFARUWB6J7XPHYSEL2I5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XU5EKCIFARUWB6J7XPHYSEL2I5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XU5EKCIFARUWB6J7XPHYSEL2I5","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":"7f16fdf27544e5889b6bef387ed22d7861179a3f16634df71e5c84d3e418829c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MM","submitted_at":"2024-06-30T01:18:37Z","title_canon_sha256":"fdcae96f4e5fd2b3d1927a30ab0acf1b8bfe297681fda56c78f684d51e1a492a"},"schema_version":"1.0","source":{"id":"2407.00556","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.00556","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"arxiv_version","alias_value":"2407.00556v1","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.00556","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"pith_short_12","alias_value":"XU5EKCIFARUW","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"pith_short_16","alias_value":"XU5EKCIFARUWB6J7","created_at":"2026-07-05T08:38:21Z"},{"alias_kind":"pith_short_8","alias_value":"XU5EKCIF","created_at":"2026-07-05T08:38:21Z"}],"graph_snapshots":[{"event_id":"sha256:4da786489b1eda8f5a358f1462515a45b87d431e40bd10a77c3021db9454ceac","target":"graph","created_at":"2026-07-05T08:38:21Z","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/2407.00556/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Social media popularity (SMP) prediction is a complex task involving multi-modal data integration. While pre-trained vision-language models (VLMs) like CLIP have been widely adopted for this task, their effectiveness in capturing the unique characteristics of social media content remains unexplored. This paper critically examines the applicability of CLIP-based features in SMP prediction, focusing on the overlooked phenomenon of semantic inconsistency between images and text in social media posts. Through extensive analysis, we demonstrate that this inconsistency increases with post popularity","authors_text":"Chia-Ming Lee, Chi-Han Tsai, Chih-Chung Hsu, Chih-Yu Jian, Yi-Shiuan Chou, Yu-Fan Lin","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MM","submitted_at":"2024-06-30T01:18:37Z","title":"Revisiting Vision-Language Features Adaptation and Inconsistency for Social Media Popularity Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.00556","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":"sha256:5b40b9e32893f607db93a54d77dc32f2b35441958f80f26efb4b7bbe61a370de","target":"record","created_at":"2026-07-05T08:38:21Z","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":"7f16fdf27544e5889b6bef387ed22d7861179a3f16634df71e5c84d3e418829c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MM","submitted_at":"2024-06-30T01:18:37Z","title_canon_sha256":"fdcae96f4e5fd2b3d1927a30ab0acf1b8bfe297681fda56c78f684d51e1a492a"},"schema_version":"1.0","source":{"id":"2407.00556","kind":"arxiv","version":1}},"canonical_sha256":"bd3a450905046960f93fbbcf89117a47419610eceb9fdae50b99154f303d0a19","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bd3a450905046960f93fbbcf89117a47419610eceb9fdae50b99154f303d0a19","first_computed_at":"2026-07-05T08:38:21.314101Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:38:21.314101Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WFsXjOmNgRkNoZ/tCmhPh6DI7wm0d80//5L0coZclKuMeDL5043+FXumSy3cBafHGo5fJvSPYZD7Y8tUBOWSAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:38:21.314515Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.00556","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5b40b9e32893f607db93a54d77dc32f2b35441958f80f26efb4b7bbe61a370de","sha256:4da786489b1eda8f5a358f1462515a45b87d431e40bd10a77c3021db9454ceac"],"state_sha256":"16b5b8a8939688b43214cad8c7b333027572c0dda39f4943869a1bd9743d3cfb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6OYR5jrJ2d4mH/fxISQxXZ23WVezlUy8+Tnm3JWZDjrdTRkLAsMAeV6Il61pWoMPncaR52UBSxDy6nHYR+tyCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T21:34:17.319795Z","bundle_sha256":"9d7d1d624c49c14f06d0409e88de21409ab265d0f8686dd98e2ce6d87109169d"}}