{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:P2ACHJDU5OIG76TXCZL5NCWI2F","short_pith_number":"pith:P2ACHJDU","schema_version":"1.0","canonical_sha256":"7e8023a474eb906ffa771657d68ac8d17d4d594ff7dc0dd531bc589e1370b7e6","source":{"kind":"arxiv","id":"2602.00813","version":5},"attestation_state":"computed","paper":{"title":"Generating a Paracosm for Training-Free Zero-Shot Composed Image Retrieval","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Shu Kong, Tong Wang, Yunhan Zhao","submitted_at":"2026-01-31T16:42:55Z","abstract_excerpt":"Composed Image Retrieval (CIR) is the task of retrieving a target image from a database using a multimodal query, which consists of a reference image and a modification text. The text specifies how to alter the reference image to form a ''mental image'', based on which CIR should find the target image in the database. The fundamental challenge of CIR is that this ''mental image'' is not physically available and is only implicitly defined by the query. The contemporary literature pursues zero-shot methods and uses a Large Multimodal Model (LMM) to generate a textual description for a given mult"},"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":"2602.00813","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-01-31T16:42:55Z","cross_cats_sorted":[],"title_canon_sha256":"209f9f4ad113c2f8e0084237d9bd52e71b1da59761886c9a03ace49a7fbc5d51","abstract_canon_sha256":"a9fe7b65b95fb26d82daaf6674461206b94229e1d0ad25cb13d073fa65c25c67"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-26T01:15:48.933823Z","signature_b64":"/97/n/XLiFyrKMvF6dszRNBteN6Piir4xxfR3WMSUFbr5wfG6c6dmcV/qv+e9GreHQI7ZCjaIh3I0zRXFtOHBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7e8023a474eb906ffa771657d68ac8d17d4d594ff7dc0dd531bc589e1370b7e6","last_reissued_at":"2026-06-26T01:15:48.933344Z","signature_status":"signed_v1","first_computed_at":"2026-06-26T01:15:48.933344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Generating a Paracosm for Training-Free Zero-Shot Composed Image Retrieval","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Shu Kong, Tong Wang, Yunhan Zhao","submitted_at":"2026-01-31T16:42:55Z","abstract_excerpt":"Composed Image Retrieval (CIR) is the task of retrieving a target image from a database using a multimodal query, which consists of a reference image and a modification text. The text specifies how to alter the reference image to form a ''mental image'', based on which CIR should find the target image in the database. The fundamental challenge of CIR is that this ''mental image'' is not physically available and is only implicitly defined by the query. The contemporary literature pursues zero-shot methods and uses a Large Multimodal Model (LMM) to generate a textual description for a given mult"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.00813","kind":"arxiv","version":5},"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/2602.00813/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":"2602.00813","created_at":"2026-06-26T01:15:48.933406+00:00"},{"alias_kind":"arxiv_version","alias_value":"2602.00813v5","created_at":"2026-06-26T01:15:48.933406+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.00813","created_at":"2026-06-26T01:15:48.933406+00:00"},{"alias_kind":"pith_short_12","alias_value":"P2ACHJDU5OIG","created_at":"2026-06-26T01:15:48.933406+00:00"},{"alias_kind":"pith_short_16","alias_value":"P2ACHJDU5OIG76TX","created_at":"2026-06-26T01:15:48.933406+00:00"},{"alias_kind":"pith_short_8","alias_value":"P2ACHJDU","created_at":"2026-06-26T01:15:48.933406+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/P2ACHJDU5OIG76TXCZL5NCWI2F","json":"https://pith.science/pith/P2ACHJDU5OIG76TXCZL5NCWI2F.json","graph_json":"https://pith.science/api/pith-number/P2ACHJDU5OIG76TXCZL5NCWI2F/graph.json","events_json":"https://pith.science/api/pith-number/P2ACHJDU5OIG76TXCZL5NCWI2F/events.json","paper":"https://pith.science/paper/P2ACHJDU"},"agent_actions":{"view_html":"https://pith.science/pith/P2ACHJDU5OIG76TXCZL5NCWI2F","download_json":"https://pith.science/pith/P2ACHJDU5OIG76TXCZL5NCWI2F.json","view_paper":"https://pith.science/paper/P2ACHJDU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2602.00813&json=true","fetch_graph":"https://pith.science/api/pith-number/P2ACHJDU5OIG76TXCZL5NCWI2F/graph.json","fetch_events":"https://pith.science/api/pith-number/P2ACHJDU5OIG76TXCZL5NCWI2F/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/P2ACHJDU5OIG76TXCZL5NCWI2F/action/timestamp_anchor","attest_storage":"https://pith.science/pith/P2ACHJDU5OIG76TXCZL5NCWI2F/action/storage_attestation","attest_author":"https://pith.science/pith/P2ACHJDU5OIG76TXCZL5NCWI2F/action/author_attestation","sign_citation":"https://pith.science/pith/P2ACHJDU5OIG76TXCZL5NCWI2F/action/citation_signature","submit_replication":"https://pith.science/pith/P2ACHJDU5OIG76TXCZL5NCWI2F/action/replication_record"}},"created_at":"2026-06-26T01:15:48.933406+00:00","updated_at":"2026-06-26T01:15:48.933406+00:00"}