{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:ZFKTRDEVQ2E5T4ZDELF7IKMILP","short_pith_number":"pith:ZFKTRDEV","schema_version":"1.0","canonical_sha256":"c955388c958689d9f32322cbf429885bd9d9f2bbd6bb12ca7ebe192915da76bd","source":{"kind":"arxiv","id":"2409.02241","version":2},"attestation_state":"computed","paper":{"title":"What Makes a Face Look like a Hat: Decoupling Low-level and High-level Visual Properties with Image Triplets","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"q-bio.NC","authors_text":"Ian Ballard, Ioannis Pappas, Maytus Piriyajitakonkij, Sirawaj Itthipuripat","submitted_at":"2024-09-03T19:14:01Z","abstract_excerpt":"In visual decision making, high-level features, such as object categories, have a strong influence on choice. However, the impact of low-level features on behavior is less understood partly due to the high correlation between high- and low-level features in the stimuli presented (e.g., objects of the same category are more likely to share low-level features). To disentangle these effects, we propose a method that de-correlates low- and high-level visual properties in a novel set of stimuli. Our method uses two Convolutional Neural Networks (CNNs) as candidate models of the ventral visual strea"},"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":"2409.02241","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.NC","submitted_at":"2024-09-03T19:14:01Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"d7057864e71d7da848ba1282a7b4c48bffae404da8d1582350fa736e8d70416d","abstract_canon_sha256":"817950d87328b70f3a01e051ee7051b894818eaa8b4c60fc55243fc2f99bc6c5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:06:09.100713Z","signature_b64":"VppicCdFqVQQLkGYkdbRR9oRwSeyeMBbfpZOkW7DOyIFJ5viCRmJYsneNbqFQb21CiseWbhtYq0d8R1v3XqNCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c955388c958689d9f32322cbf429885bd9d9f2bbd6bb12ca7ebe192915da76bd","last_reissued_at":"2026-07-05T09:06:09.100288Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:06:09.100288Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"What Makes a Face Look like a Hat: Decoupling Low-level and High-level Visual Properties with Image Triplets","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"q-bio.NC","authors_text":"Ian Ballard, Ioannis Pappas, Maytus Piriyajitakonkij, Sirawaj Itthipuripat","submitted_at":"2024-09-03T19:14:01Z","abstract_excerpt":"In visual decision making, high-level features, such as object categories, have a strong influence on choice. However, the impact of low-level features on behavior is less understood partly due to the high correlation between high- and low-level features in the stimuli presented (e.g., objects of the same category are more likely to share low-level features). To disentangle these effects, we propose a method that de-correlates low- and high-level visual properties in a novel set of stimuli. Our method uses two Convolutional Neural Networks (CNNs) as candidate models of the ventral visual strea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.02241","kind":"arxiv","version":2},"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/2409.02241/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":"2409.02241","created_at":"2026-07-05T09:06:09.100361+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.02241v2","created_at":"2026-07-05T09:06:09.100361+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.02241","created_at":"2026-07-05T09:06:09.100361+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZFKTRDEVQ2E5","created_at":"2026-07-05T09:06:09.100361+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZFKTRDEVQ2E5T4ZD","created_at":"2026-07-05T09:06:09.100361+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZFKTRDEV","created_at":"2026-07-05T09:06:09.100361+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/ZFKTRDEVQ2E5T4ZDELF7IKMILP","json":"https://pith.science/pith/ZFKTRDEVQ2E5T4ZDELF7IKMILP.json","graph_json":"https://pith.science/api/pith-number/ZFKTRDEVQ2E5T4ZDELF7IKMILP/graph.json","events_json":"https://pith.science/api/pith-number/ZFKTRDEVQ2E5T4ZDELF7IKMILP/events.json","paper":"https://pith.science/paper/ZFKTRDEV"},"agent_actions":{"view_html":"https://pith.science/pith/ZFKTRDEVQ2E5T4ZDELF7IKMILP","download_json":"https://pith.science/pith/ZFKTRDEVQ2E5T4ZDELF7IKMILP.json","view_paper":"https://pith.science/paper/ZFKTRDEV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.02241&json=true","fetch_graph":"https://pith.science/api/pith-number/ZFKTRDEVQ2E5T4ZDELF7IKMILP/graph.json","fetch_events":"https://pith.science/api/pith-number/ZFKTRDEVQ2E5T4ZDELF7IKMILP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZFKTRDEVQ2E5T4ZDELF7IKMILP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZFKTRDEVQ2E5T4ZDELF7IKMILP/action/storage_attestation","attest_author":"https://pith.science/pith/ZFKTRDEVQ2E5T4ZDELF7IKMILP/action/author_attestation","sign_citation":"https://pith.science/pith/ZFKTRDEVQ2E5T4ZDELF7IKMILP/action/citation_signature","submit_replication":"https://pith.science/pith/ZFKTRDEVQ2E5T4ZDELF7IKMILP/action/replication_record"}},"created_at":"2026-07-05T09:06:09.100361+00:00","updated_at":"2026-07-05T09:06:09.100361+00:00"}