{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:PT7T23CLYQIVK6NCA2A5FSU7VN","short_pith_number":"pith:PT7T23CL","canonical_record":{"source":{"id":"2501.13851","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-23T17:18:30Z","cross_cats_sorted":[],"title_canon_sha256":"08a1572c8627903734457b2b62a3786cbc0f70773d8dce7e068e075d68b142ba","abstract_canon_sha256":"5beaf248f4c1686135be2eca719e4e0b58d5d053753e78343b2f72c82a9c78c8"},"schema_version":"1.0"},"canonical_sha256":"7cff3d6c4bc4115579a20681d2ca9fab7ee3e360958bbf7a27f8618f125d86a8","source":{"kind":"arxiv","id":"2501.13851","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.13851","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"arxiv_version","alias_value":"2501.13851v1","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.13851","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"pith_short_12","alias_value":"PT7T23CLYQIV","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"pith_short_16","alias_value":"PT7T23CLYQIVK6NC","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"pith_short_8","alias_value":"PT7T23CL","created_at":"2026-07-05T10:04:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:PT7T23CLYQIVK6NCA2A5FSU7VN","target":"record","payload":{"canonical_record":{"source":{"id":"2501.13851","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-23T17:18:30Z","cross_cats_sorted":[],"title_canon_sha256":"08a1572c8627903734457b2b62a3786cbc0f70773d8dce7e068e075d68b142ba","abstract_canon_sha256":"5beaf248f4c1686135be2eca719e4e0b58d5d053753e78343b2f72c82a9c78c8"},"schema_version":"1.0"},"canonical_sha256":"7cff3d6c4bc4115579a20681d2ca9fab7ee3e360958bbf7a27f8618f125d86a8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:04:35.210175Z","signature_b64":"wdPDiamS29swk5xN0Blv04uQaIGzlIOy4OCmvgB6a9NQiORU4JydUCgsmZ3bSvtblnuSEggW0YA5H5bQ0JNXCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7cff3d6c4bc4115579a20681d2ca9fab7ee3e360958bbf7a27f8618f125d86a8","last_reissued_at":"2026-07-05T10:04:35.209676Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:04:35.209676Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.13851","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":"2026-07-05T10:04:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AEHuodGK5Kru05Qkja8XCwb8HxZB0798gF+zHhs3zmXfuSY26Z0HLL1686wp6UfGznOQ6PeFgxhh5FGkDHn0AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T23:08:25.894552Z"},"content_sha256":"1ea0aa58535eed136632b2f0dc1141f3cb5664e3e9b84597d5730de01466770c","schema_version":"1.0","event_id":"sha256:1ea0aa58535eed136632b2f0dc1141f3cb5664e3e9b84597d5730de01466770c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:PT7T23CLYQIVK6NCA2A5FSU7VN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Large Vision-Language Models for Knowledge-Grounded Data Annotation of Memes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Peter Ebert Christensen, Serge Belongie, Shiling Deng","submitted_at":"2025-01-23T17:18:30Z","abstract_excerpt":"Memes have emerged as a powerful form of communication, integrating visual and textual elements to convey humor, satire, and cultural messages. Existing research has focused primarily on aspects such as emotion classification, meme generation, propagation, interpretation, figurative language, and sociolinguistics, but has often overlooked deeper meme comprehension and meme-text retrieval. To address these gaps, this study introduces ClassicMemes-50-templates (CM50), a large-scale dataset consisting of over 33,000 memes, centered around 50 popular meme templates. We also present an automated kn"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.13851","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/2501.13851/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":"2026-07-05T10:04:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CZfR5HOZ8YNgMhpuux79TAPoHA/oCFU/A/61poX79iIVfHo7hoKI5Jf/ovjHcmJ8qcAoXJI/FRv7iuYfAYLoDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T23:08:25.895035Z"},"content_sha256":"1b6850f64617b57a3a550d9644886da3571f8ba52062952b046439db72e06d19","schema_version":"1.0","event_id":"sha256:1b6850f64617b57a3a550d9644886da3571f8ba52062952b046439db72e06d19"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PT7T23CLYQIVK6NCA2A5FSU7VN/bundle.json","state_url":"https://pith.science/pith/PT7T23CLYQIVK6NCA2A5FSU7VN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PT7T23CLYQIVK6NCA2A5FSU7VN/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":"2026-08-10T23:08:25Z","links":{"resolver":"https://pith.science/pith/PT7T23CLYQIVK6NCA2A5FSU7VN","bundle":"https://pith.science/pith/PT7T23CLYQIVK6NCA2A5FSU7VN/bundle.json","state":"https://pith.science/pith/PT7T23CLYQIVK6NCA2A5FSU7VN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PT7T23CLYQIVK6NCA2A5FSU7VN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:PT7T23CLYQIVK6NCA2A5FSU7VN","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":"5beaf248f4c1686135be2eca719e4e0b58d5d053753e78343b2f72c82a9c78c8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-23T17:18:30Z","title_canon_sha256":"08a1572c8627903734457b2b62a3786cbc0f70773d8dce7e068e075d68b142ba"},"schema_version":"1.0","source":{"id":"2501.13851","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.13851","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"arxiv_version","alias_value":"2501.13851v1","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.13851","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"pith_short_12","alias_value":"PT7T23CLYQIV","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"pith_short_16","alias_value":"PT7T23CLYQIVK6NC","created_at":"2026-07-05T10:04:35Z"},{"alias_kind":"pith_short_8","alias_value":"PT7T23CL","created_at":"2026-07-05T10:04:35Z"}],"graph_snapshots":[{"event_id":"sha256:1b6850f64617b57a3a550d9644886da3571f8ba52062952b046439db72e06d19","target":"graph","created_at":"2026-07-05T10:04:35Z","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/2501.13851/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Memes have emerged as a powerful form of communication, integrating visual and textual elements to convey humor, satire, and cultural messages. Existing research has focused primarily on aspects such as emotion classification, meme generation, propagation, interpretation, figurative language, and sociolinguistics, but has often overlooked deeper meme comprehension and meme-text retrieval. To address these gaps, this study introduces ClassicMemes-50-templates (CM50), a large-scale dataset consisting of over 33,000 memes, centered around 50 popular meme templates. We also present an automated kn","authors_text":"Peter Ebert Christensen, Serge Belongie, Shiling Deng","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-23T17:18:30Z","title":"Large Vision-Language Models for Knowledge-Grounded Data Annotation of Memes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.13851","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":"sha256:1ea0aa58535eed136632b2f0dc1141f3cb5664e3e9b84597d5730de01466770c","target":"record","created_at":"2026-07-05T10:04:35Z","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":"5beaf248f4c1686135be2eca719e4e0b58d5d053753e78343b2f72c82a9c78c8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-23T17:18:30Z","title_canon_sha256":"08a1572c8627903734457b2b62a3786cbc0f70773d8dce7e068e075d68b142ba"},"schema_version":"1.0","source":{"id":"2501.13851","kind":"arxiv","version":1}},"canonical_sha256":"7cff3d6c4bc4115579a20681d2ca9fab7ee3e360958bbf7a27f8618f125d86a8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7cff3d6c4bc4115579a20681d2ca9fab7ee3e360958bbf7a27f8618f125d86a8","first_computed_at":"2026-07-05T10:04:35.209676Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:04:35.209676Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wdPDiamS29swk5xN0Blv04uQaIGzlIOy4OCmvgB6a9NQiORU4JydUCgsmZ3bSvtblnuSEggW0YA5H5bQ0JNXCg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:04:35.210175Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.13851","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1ea0aa58535eed136632b2f0dc1141f3cb5664e3e9b84597d5730de01466770c","sha256:1b6850f64617b57a3a550d9644886da3571f8ba52062952b046439db72e06d19"],"state_sha256":"4a4e34564e6b61a112cdf7bbd96ff4173a32531c8cfc5b520aedf9358cfc9e3c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HP/1ZlxrOJPrwll2nj9J1O8ariPZVFFmq3Z/qBWrkbdVvALJMoJmzi2lz6tHkdOQtom5a6txGXaF2Mc0dhwRBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T23:08:25.899879Z","bundle_sha256":"cc54d23bd29b7718d4a1fbb61179a6da3d2278c3df9f1d5d5c7429cd7bb68020"}}