{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:OWPBEDW62FSUBJ6I7IYCLT7IZC","short_pith_number":"pith:OWPBEDW6","schema_version":"1.0","canonical_sha256":"759e120eded16540a7c8fa3025cfe8c89e74dab2fea4f84ba74e2572ee31f00b","source":{"kind":"arxiv","id":"2509.05394","version":1},"attestation_state":"computed","paper":{"title":"Reverse Browser: Vector-Image-to-Code Generator","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.SE","authors_text":"Zoltan Toth-Czifra","submitted_at":"2025-09-05T11:13:40Z","abstract_excerpt":"Automating the conversion of user interface design into code (image-to-code or image-to-UI) is an active area of software engineering research. However, the state-of-the-art solutions do not achieve high fidelity to the original design, as evidenced by benchmarks. In this work, I approach the problem differently: I use vector images instead of bitmaps as model input. I create several large datasets for training machine learning models. I evaluate the available array of Image Quality Assessment (IQA) algorithms and introduce a new, multi-scale metric. I then train a large open-weights model and"},"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":"2509.05394","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.SE","submitted_at":"2025-09-05T11:13:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"90277e58f811b233de1739130c4f0ba4cf9803ce44f91fe03d001d04aa9c7940","abstract_canon_sha256":"9efe4e9fadbe925bd1ea4d09b92203409aeac58a5abf97e3fca468a65e1baa70"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:05:46.462839Z","signature_b64":"xUxOnUmS3Rb/GR/RDGuzQplNX9M/hluDwbfggly5+gKFRCzNjonj+GSdUdWmxgX2pcaTQkbGf2MapEicgfkeCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"759e120eded16540a7c8fa3025cfe8c89e74dab2fea4f84ba74e2572ee31f00b","last_reissued_at":"2026-07-05T12:05:46.462337Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:05:46.462337Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Reverse Browser: Vector-Image-to-Code Generator","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.SE","authors_text":"Zoltan Toth-Czifra","submitted_at":"2025-09-05T11:13:40Z","abstract_excerpt":"Automating the conversion of user interface design into code (image-to-code or image-to-UI) is an active area of software engineering research. However, the state-of-the-art solutions do not achieve high fidelity to the original design, as evidenced by benchmarks. In this work, I approach the problem differently: I use vector images instead of bitmaps as model input. I create several large datasets for training machine learning models. I evaluate the available array of Image Quality Assessment (IQA) algorithms and introduce a new, multi-scale metric. I then train a large open-weights model and"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.05394","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/2509.05394/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":"2509.05394","created_at":"2026-07-05T12:05:46.462399+00:00"},{"alias_kind":"arxiv_version","alias_value":"2509.05394v1","created_at":"2026-07-05T12:05:46.462399+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.05394","created_at":"2026-07-05T12:05:46.462399+00:00"},{"alias_kind":"pith_short_12","alias_value":"OWPBEDW62FSU","created_at":"2026-07-05T12:05:46.462399+00:00"},{"alias_kind":"pith_short_16","alias_value":"OWPBEDW62FSUBJ6I","created_at":"2026-07-05T12:05:46.462399+00:00"},{"alias_kind":"pith_short_8","alias_value":"OWPBEDW6","created_at":"2026-07-05T12:05:46.462399+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/OWPBEDW62FSUBJ6I7IYCLT7IZC","json":"https://pith.science/pith/OWPBEDW62FSUBJ6I7IYCLT7IZC.json","graph_json":"https://pith.science/api/pith-number/OWPBEDW62FSUBJ6I7IYCLT7IZC/graph.json","events_json":"https://pith.science/api/pith-number/OWPBEDW62FSUBJ6I7IYCLT7IZC/events.json","paper":"https://pith.science/paper/OWPBEDW6"},"agent_actions":{"view_html":"https://pith.science/pith/OWPBEDW62FSUBJ6I7IYCLT7IZC","download_json":"https://pith.science/pith/OWPBEDW62FSUBJ6I7IYCLT7IZC.json","view_paper":"https://pith.science/paper/OWPBEDW6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2509.05394&json=true","fetch_graph":"https://pith.science/api/pith-number/OWPBEDW62FSUBJ6I7IYCLT7IZC/graph.json","fetch_events":"https://pith.science/api/pith-number/OWPBEDW62FSUBJ6I7IYCLT7IZC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OWPBEDW62FSUBJ6I7IYCLT7IZC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OWPBEDW62FSUBJ6I7IYCLT7IZC/action/storage_attestation","attest_author":"https://pith.science/pith/OWPBEDW62FSUBJ6I7IYCLT7IZC/action/author_attestation","sign_citation":"https://pith.science/pith/OWPBEDW62FSUBJ6I7IYCLT7IZC/action/citation_signature","submit_replication":"https://pith.science/pith/OWPBEDW62FSUBJ6I7IYCLT7IZC/action/replication_record"}},"created_at":"2026-07-05T12:05:46.462399+00:00","updated_at":"2026-07-05T12:05:46.462399+00:00"}