{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:VAVY4CU4R4BYDZED7ANVWXM76A","short_pith_number":"pith:VAVY4CU4","schema_version":"1.0","canonical_sha256":"a82b8e0a9c8f0381e483f81b5b5d9ff0073ebf8cc7cb7ae7a85d5f57d5d995d1","source":{"kind":"arxiv","id":"2412.14210","version":1},"attestation_state":"computed","paper":{"title":"Mobilizing Waldo: Evaluating Multimodal AI for Public Mobilization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CY","cs.SI"],"primary_cat":"cs.HC","authors_text":"Manuel Cebrian, Niccolo Pescetelli, Petter Holme","submitted_at":"2024-12-18T00:10:11Z","abstract_excerpt":"Advancements in multimodal Large Language Models (LLMs), such as OpenAI's GPT-4o, offer significant potential for mediating human interactions across various contexts. However, their use in areas such as persuasion, influence, and recruitment raises ethical and security concerns. To evaluate these models ethically in public influence and persuasion scenarios, we developed a prompting strategy using \"Where's Waldo?\" images as proxies for complex, crowded gatherings. This approach provides a controlled, replicable environment to assess the model's ability to process intricate visual information,"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2412.14210","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2024-12-18T00:10:11Z","cross_cats_sorted":["cs.CY","cs.SI"],"title_canon_sha256":"f028959ffe609349fd0ce7932431fdee8cf61be1377a98974a57ee506f55a23a","abstract_canon_sha256":"159e85ff451848a62f11a16f09eec2749e3d10219c7b5f0d57e0875c01b9f7f0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:51:41.865860Z","signature_b64":"ZAynlw+zypetLFgVKXTPhkx9k5oaSVuJYmIqO2VXRr0o3dBEcSQPNqO7jubXiFrXrMzlimCrSYb/YY+ftKS6Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a82b8e0a9c8f0381e483f81b5b5d9ff0073ebf8cc7cb7ae7a85d5f57d5d995d1","last_reissued_at":"2026-07-05T09:51:41.865434Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:51:41.865434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Mobilizing Waldo: Evaluating Multimodal AI for Public Mobilization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CY","cs.SI"],"primary_cat":"cs.HC","authors_text":"Manuel Cebrian, Niccolo Pescetelli, Petter Holme","submitted_at":"2024-12-18T00:10:11Z","abstract_excerpt":"Advancements in multimodal Large Language Models (LLMs), such as OpenAI's GPT-4o, offer significant potential for mediating human interactions across various contexts. However, their use in areas such as persuasion, influence, and recruitment raises ethical and security concerns. To evaluate these models ethically in public influence and persuasion scenarios, we developed a prompting strategy using \"Where's Waldo?\" images as proxies for complex, crowded gatherings. This approach provides a controlled, replicable environment to assess the model's ability to process intricate visual information,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.14210","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/2412.14210/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2412.14210","created_at":"2026-07-05T09:51:41.865500+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.14210v1","created_at":"2026-07-05T09:51:41.865500+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.14210","created_at":"2026-07-05T09:51:41.865500+00:00"},{"alias_kind":"pith_short_12","alias_value":"VAVY4CU4R4BY","created_at":"2026-07-05T09:51:41.865500+00:00"},{"alias_kind":"pith_short_16","alias_value":"VAVY4CU4R4BYDZED","created_at":"2026-07-05T09:51:41.865500+00:00"},{"alias_kind":"pith_short_8","alias_value":"VAVY4CU4","created_at":"2026-07-05T09:51:41.865500+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VAVY4CU4R4BYDZED7ANVWXM76A","json":"https://pith.science/pith/VAVY4CU4R4BYDZED7ANVWXM76A.json","graph_json":"https://pith.science/api/pith-number/VAVY4CU4R4BYDZED7ANVWXM76A/graph.json","events_json":"https://pith.science/api/pith-number/VAVY4CU4R4BYDZED7ANVWXM76A/events.json","paper":"https://pith.science/paper/VAVY4CU4"},"agent_actions":{"view_html":"https://pith.science/pith/VAVY4CU4R4BYDZED7ANVWXM76A","download_json":"https://pith.science/pith/VAVY4CU4R4BYDZED7ANVWXM76A.json","view_paper":"https://pith.science/paper/VAVY4CU4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.14210&json=true","fetch_graph":"https://pith.science/api/pith-number/VAVY4CU4R4BYDZED7ANVWXM76A/graph.json","fetch_events":"https://pith.science/api/pith-number/VAVY4CU4R4BYDZED7ANVWXM76A/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VAVY4CU4R4BYDZED7ANVWXM76A/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VAVY4CU4R4BYDZED7ANVWXM76A/action/storage_attestation","attest_author":"https://pith.science/pith/VAVY4CU4R4BYDZED7ANVWXM76A/action/author_attestation","sign_citation":"https://pith.science/pith/VAVY4CU4R4BYDZED7ANVWXM76A/action/citation_signature","submit_replication":"https://pith.science/pith/VAVY4CU4R4BYDZED7ANVWXM76A/action/replication_record"}},"created_at":"2026-07-05T09:51:41.865500+00:00","updated_at":"2026-07-05T09:51:41.865500+00:00"}