{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:IAYYYFXYNORYIV6EEDE5ZJK4PR","short_pith_number":"pith:IAYYYFXY","schema_version":"1.0","canonical_sha256":"40318c16f86ba38457c420c9dca55c7c5e3317da0ac7dd35e8d2cc8ccb667c30","source":{"kind":"arxiv","id":"1706.05850","version":3},"attestation_state":"computed","paper":{"title":"Rapid Probabilistic Interest Learning from Domain-Specific Pairwise Image Comparisons","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Michael Burke, Purity Molala, Raesetje Sefala, Siyabonga Mbonambi","submitted_at":"2017-06-19T09:37:29Z","abstract_excerpt":"A great deal of work aims to discover large general purpose models of image interest or memorability for visual search and information retrieval. This paper argues that image interest is often domain and user specific, and that efficient mechanisms for learning about this domain-specific image interest as quickly as possible, while limiting the amount of data-labelling required, are often more useful to end-users. This work uses pairwise image comparisons to reduce the labelling burden on these users, and introduces an image interest estimation approach that performs similarly to recent data h"},"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":"1706.05850","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-06-19T09:37:29Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"b04ec415f446ae30a42420ca33dba0eacf04b0f9edf431d10d70a7630f1d2247","abstract_canon_sha256":"d369ea3a155addd0c8b037915914134956443b533306ac5587871fedfd285852"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:04:58.237846Z","signature_b64":"wr2UvjMGs4j1yyjbHwvTSz7vgjC0LdcvfM7BwQjAFs90Na07dZeLHBC29ez2D8Kkcw++b8kuAhAPX7lSTnWKDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40318c16f86ba38457c420c9dca55c7c5e3317da0ac7dd35e8d2cc8ccb667c30","last_reissued_at":"2026-07-05T01:04:58.237379Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:04:58.237379Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Rapid Probabilistic Interest Learning from Domain-Specific Pairwise Image Comparisons","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Michael Burke, Purity Molala, Raesetje Sefala, Siyabonga Mbonambi","submitted_at":"2017-06-19T09:37:29Z","abstract_excerpt":"A great deal of work aims to discover large general purpose models of image interest or memorability for visual search and information retrieval. This paper argues that image interest is often domain and user specific, and that efficient mechanisms for learning about this domain-specific image interest as quickly as possible, while limiting the amount of data-labelling required, are often more useful to end-users. This work uses pairwise image comparisons to reduce the labelling burden on these users, and introduces an image interest estimation approach that performs similarly to recent data h"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.05850","kind":"arxiv","version":3},"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/1706.05850/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":"1706.05850","created_at":"2026-07-05T01:04:58.237435+00:00"},{"alias_kind":"arxiv_version","alias_value":"1706.05850v3","created_at":"2026-07-05T01:04:58.237435+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.05850","created_at":"2026-07-05T01:04:58.237435+00:00"},{"alias_kind":"pith_short_12","alias_value":"IAYYYFXYNORY","created_at":"2026-07-05T01:04:58.237435+00:00"},{"alias_kind":"pith_short_16","alias_value":"IAYYYFXYNORYIV6E","created_at":"2026-07-05T01:04:58.237435+00:00"},{"alias_kind":"pith_short_8","alias_value":"IAYYYFXY","created_at":"2026-07-05T01:04:58.237435+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/IAYYYFXYNORYIV6EEDE5ZJK4PR","json":"https://pith.science/pith/IAYYYFXYNORYIV6EEDE5ZJK4PR.json","graph_json":"https://pith.science/api/pith-number/IAYYYFXYNORYIV6EEDE5ZJK4PR/graph.json","events_json":"https://pith.science/api/pith-number/IAYYYFXYNORYIV6EEDE5ZJK4PR/events.json","paper":"https://pith.science/paper/IAYYYFXY"},"agent_actions":{"view_html":"https://pith.science/pith/IAYYYFXYNORYIV6EEDE5ZJK4PR","download_json":"https://pith.science/pith/IAYYYFXYNORYIV6EEDE5ZJK4PR.json","view_paper":"https://pith.science/paper/IAYYYFXY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1706.05850&json=true","fetch_graph":"https://pith.science/api/pith-number/IAYYYFXYNORYIV6EEDE5ZJK4PR/graph.json","fetch_events":"https://pith.science/api/pith-number/IAYYYFXYNORYIV6EEDE5ZJK4PR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IAYYYFXYNORYIV6EEDE5ZJK4PR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IAYYYFXYNORYIV6EEDE5ZJK4PR/action/storage_attestation","attest_author":"https://pith.science/pith/IAYYYFXYNORYIV6EEDE5ZJK4PR/action/author_attestation","sign_citation":"https://pith.science/pith/IAYYYFXYNORYIV6EEDE5ZJK4PR/action/citation_signature","submit_replication":"https://pith.science/pith/IAYYYFXYNORYIV6EEDE5ZJK4PR/action/replication_record"}},"created_at":"2026-07-05T01:04:58.237435+00:00","updated_at":"2026-07-05T01:04:58.237435+00:00"}