{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:3R6OZNI5FU5XY4QXLWRYH24QRO","short_pith_number":"pith:3R6OZNI5","schema_version":"1.0","canonical_sha256":"dc7cecb51d2d3b7c72175da383eb908bb59ff4aa7d101aab72ab128ecd6a93ec","source":{"kind":"arxiv","id":"2606.05261","version":1},"attestation_state":"computed","paper":{"title":"NIV: Neural Axis Variations for Variable Font Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Ariel Shamir, Nadav Benedek, Ohad Fried","submitted_at":"2026-06-03T16:17:43Z","abstract_excerpt":"Variable fonts enable continuous variation of glyph geometry along semantic design axes such as weight, width, slant, and optical size. However, constructing a variable font from a static font remains a labor-intensive process requiring expert typographic design and manual specification of glyph variation data. We introduce NIV (Neural Axis Variations), a method that automatically converts a static font into a fully functional variable font. Given glyph outlines and a set of desired design axes, NIV predicts per-point displacements. The model operates directly on vector glyph geometry and empl"},"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":"2606.05261","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-03T16:17:43Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"0a2fc1175b43654b7083a81218a22043a1019d82a27a44e215f925253e4b2bbc","abstract_canon_sha256":"5e978058d15d4b8513f74aa21a63f7bbf89ec76ba96d65868d0201ca1b30a593"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T00:13:50.814559Z","signature_b64":"UbKkBmYDwfT1X9rAOmHsowJPegwcYSW2o3AzH8/lOVKE1pPWs3foFOsXhvgdWoQKZqgusqMR32OwfG43zNqwAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dc7cecb51d2d3b7c72175da383eb908bb59ff4aa7d101aab72ab128ecd6a93ec","last_reissued_at":"2026-06-05T00:13:50.814098Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T00:13:50.814098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"NIV: Neural Axis Variations for Variable Font Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Ariel Shamir, Nadav Benedek, Ohad Fried","submitted_at":"2026-06-03T16:17:43Z","abstract_excerpt":"Variable fonts enable continuous variation of glyph geometry along semantic design axes such as weight, width, slant, and optical size. However, constructing a variable font from a static font remains a labor-intensive process requiring expert typographic design and manual specification of glyph variation data. We introduce NIV (Neural Axis Variations), a method that automatically converts a static font into a fully functional variable font. Given glyph outlines and a set of desired design axes, NIV predicts per-point displacements. The model operates directly on vector glyph geometry and empl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05261","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/2606.05261/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":"2606.05261","created_at":"2026-06-05T00:13:50.814165+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.05261v1","created_at":"2026-06-05T00:13:50.814165+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05261","created_at":"2026-06-05T00:13:50.814165+00:00"},{"alias_kind":"pith_short_12","alias_value":"3R6OZNI5FU5X","created_at":"2026-06-05T00:13:50.814165+00:00"},{"alias_kind":"pith_short_16","alias_value":"3R6OZNI5FU5XY4QX","created_at":"2026-06-05T00:13:50.814165+00:00"},{"alias_kind":"pith_short_8","alias_value":"3R6OZNI5","created_at":"2026-06-05T00:13:50.814165+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/3R6OZNI5FU5XY4QXLWRYH24QRO","json":"https://pith.science/pith/3R6OZNI5FU5XY4QXLWRYH24QRO.json","graph_json":"https://pith.science/api/pith-number/3R6OZNI5FU5XY4QXLWRYH24QRO/graph.json","events_json":"https://pith.science/api/pith-number/3R6OZNI5FU5XY4QXLWRYH24QRO/events.json","paper":"https://pith.science/paper/3R6OZNI5"},"agent_actions":{"view_html":"https://pith.science/pith/3R6OZNI5FU5XY4QXLWRYH24QRO","download_json":"https://pith.science/pith/3R6OZNI5FU5XY4QXLWRYH24QRO.json","view_paper":"https://pith.science/paper/3R6OZNI5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.05261&json=true","fetch_graph":"https://pith.science/api/pith-number/3R6OZNI5FU5XY4QXLWRYH24QRO/graph.json","fetch_events":"https://pith.science/api/pith-number/3R6OZNI5FU5XY4QXLWRYH24QRO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3R6OZNI5FU5XY4QXLWRYH24QRO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3R6OZNI5FU5XY4QXLWRYH24QRO/action/storage_attestation","attest_author":"https://pith.science/pith/3R6OZNI5FU5XY4QXLWRYH24QRO/action/author_attestation","sign_citation":"https://pith.science/pith/3R6OZNI5FU5XY4QXLWRYH24QRO/action/citation_signature","submit_replication":"https://pith.science/pith/3R6OZNI5FU5XY4QXLWRYH24QRO/action/replication_record"}},"created_at":"2026-06-05T00:13:50.814165+00:00","updated_at":"2026-06-05T00:13:50.814165+00:00"}