{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:W42OT3XWREMDMBBWJKPKEAFSJA","short_pith_number":"pith:W42OT3XW","schema_version":"1.0","canonical_sha256":"b734e9eef689183604364a9ea200b24827c135a8cd674693a64c66a019c46996","source":{"kind":"arxiv","id":"2303.12647","version":1},"attestation_state":"computed","paper":{"title":"A Word is Worth a Thousand Pictures: Prompts as AI Design Material","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Alex Fiannaca, Carrie Cai, Chinmay Kulkarni, Michael Terry, Minsuk Chang, Stefania Druga","submitted_at":"2023-03-22T15:28:37Z","abstract_excerpt":"Recent advances in Machine-Learning have led to the development of models that generate images based on a text description.Such large prompt-based text to image models (TTIs), trained on a considerable amount of data, allow the creation of high-quality images by users with no graphics or design training. This paper examines the role such TTI models can playin collaborative, goal-oriented design. Through a within-subjects study with 14 non-professional designers, we find that such models can help participants explore a design space rapidly and allow for fluid collaboration. We also find that te"},"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":"2303.12647","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2023-03-22T15:28:37Z","cross_cats_sorted":[],"title_canon_sha256":"fc03604103a05d04e7c432d6b46ab6944699694c675fc76b2d3df8149ec47f22","abstract_canon_sha256":"8405042f3095092798c31d74630b0f2d9e3175e45e6dfa9f354efa56f437b310"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:53:43.691058Z","signature_b64":"lq7y35PaR0hJmcyrmb1fEvvN0mjpHoPjjGSfLM7PjyZOPBrYdp3I7uohzWm6wIqYswSOPZXo4tMTiPgv6ZB1AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b734e9eef689183604364a9ea200b24827c135a8cd674693a64c66a019c46996","last_reissued_at":"2026-07-05T05:53:43.690673Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:53:43.690673Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Word is Worth a Thousand Pictures: Prompts as AI Design Material","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Alex Fiannaca, Carrie Cai, Chinmay Kulkarni, Michael Terry, Minsuk Chang, Stefania Druga","submitted_at":"2023-03-22T15:28:37Z","abstract_excerpt":"Recent advances in Machine-Learning have led to the development of models that generate images based on a text description.Such large prompt-based text to image models (TTIs), trained on a considerable amount of data, allow the creation of high-quality images by users with no graphics or design training. This paper examines the role such TTI models can playin collaborative, goal-oriented design. Through a within-subjects study with 14 non-professional designers, we find that such models can help participants explore a design space rapidly and allow for fluid collaboration. We also find that te"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.12647","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/2303.12647/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":"2303.12647","created_at":"2026-07-05T05:53:43.690732+00:00"},{"alias_kind":"arxiv_version","alias_value":"2303.12647v1","created_at":"2026-07-05T05:53:43.690732+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.12647","created_at":"2026-07-05T05:53:43.690732+00:00"},{"alias_kind":"pith_short_12","alias_value":"W42OT3XWREMD","created_at":"2026-07-05T05:53:43.690732+00:00"},{"alias_kind":"pith_short_16","alias_value":"W42OT3XWREMDMBBW","created_at":"2026-07-05T05:53:43.690732+00:00"},{"alias_kind":"pith_short_8","alias_value":"W42OT3XW","created_at":"2026-07-05T05:53:43.690732+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.29675","citing_title":"From Prompts to Context: An Ontology-Driven Framework for Human-Generative AI Collaboration","ref_index":18,"is_internal_anchor":false},{"citing_arxiv_id":"2605.19832","citing_title":"Material for Thought: Generative AI as an Active Creative Medium","ref_index":8,"is_internal_anchor":false},{"citing_arxiv_id":"2509.10652","citing_title":"Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration","ref_index":57,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/W42OT3XWREMDMBBWJKPKEAFSJA","json":"https://pith.science/pith/W42OT3XWREMDMBBWJKPKEAFSJA.json","graph_json":"https://pith.science/api/pith-number/W42OT3XWREMDMBBWJKPKEAFSJA/graph.json","events_json":"https://pith.science/api/pith-number/W42OT3XWREMDMBBWJKPKEAFSJA/events.json","paper":"https://pith.science/paper/W42OT3XW"},"agent_actions":{"view_html":"https://pith.science/pith/W42OT3XWREMDMBBWJKPKEAFSJA","download_json":"https://pith.science/pith/W42OT3XWREMDMBBWJKPKEAFSJA.json","view_paper":"https://pith.science/paper/W42OT3XW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2303.12647&json=true","fetch_graph":"https://pith.science/api/pith-number/W42OT3XWREMDMBBWJKPKEAFSJA/graph.json","fetch_events":"https://pith.science/api/pith-number/W42OT3XWREMDMBBWJKPKEAFSJA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W42OT3XWREMDMBBWJKPKEAFSJA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W42OT3XWREMDMBBWJKPKEAFSJA/action/storage_attestation","attest_author":"https://pith.science/pith/W42OT3XWREMDMBBWJKPKEAFSJA/action/author_attestation","sign_citation":"https://pith.science/pith/W42OT3XWREMDMBBWJKPKEAFSJA/action/citation_signature","submit_replication":"https://pith.science/pith/W42OT3XWREMDMBBWJKPKEAFSJA/action/replication_record"}},"created_at":"2026-07-05T05:53:43.690732+00:00","updated_at":"2026-07-05T05:53:43.690732+00:00"}