{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:4Y3LW4SQDDFBGWRZZLI6J23PAP","short_pith_number":"pith:4Y3LW4SQ","schema_version":"1.0","canonical_sha256":"e636bb725018ca135a39cad1e4eb6f03f7c3c5d0de0d1073b8cdef868b926d23","source":{"kind":"arxiv","id":"2605.30174","version":1},"attestation_state":"computed","paper":{"title":"LiveSVG: Zero-Shot SVG Animation via Video Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alex Rav Acha, Ariel Shamir, Bar Cavia, Dani Lischinski, Dvir Samuel, Matan Levy, Ran Margolin, Shmuel Peleg, Yael Pritch","submitted_at":"2026-05-28T16:23:34Z","abstract_excerpt":"We introduce LiveSVG, a zero-shot approach for generating Scalable Vector Graphics (SVG) animations using video diffusion models. Current SVG animation methods struggle with complex motions: LLM-based code synthesis fails to express fine, non-rigid B\\'ezier deformations, while Score Distillation Sampling (SDS) provides noisy gradients and often requires category-specific priors like skeletons. In contrast, LiveSVG fits vector geometry directly to an explicitly generated target video. Given an input SVG image and a motion prompt, we generate a previewable target video using a frozen image-to-vi"},"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":"2605.30174","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T16:23:34Z","cross_cats_sorted":[],"title_canon_sha256":"691a42818b119100de681f32b1a447edb1222a34ba918023c93bbfe836fe4cf5","abstract_canon_sha256":"58f72a6ae22eb35ae1851aef2451ae48316bf45938c34be01ca5cebeb386d75c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T02:06:11.828955Z","signature_b64":"sJPzUAqPYgtOl9xDLwK5GiX5XF6QUUCsGzmLtT2Yk6GRLzrZ2WI7Vgcf71hPU8bW5Xhdy6qBRyjzhKvNckZ7Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e636bb725018ca135a39cad1e4eb6f03f7c3c5d0de0d1073b8cdef868b926d23","last_reissued_at":"2026-05-29T02:06:11.828541Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T02:06:11.828541Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LiveSVG: Zero-Shot SVG Animation via Video Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alex Rav Acha, Ariel Shamir, Bar Cavia, Dani Lischinski, Dvir Samuel, Matan Levy, Ran Margolin, Shmuel Peleg, Yael Pritch","submitted_at":"2026-05-28T16:23:34Z","abstract_excerpt":"We introduce LiveSVG, a zero-shot approach for generating Scalable Vector Graphics (SVG) animations using video diffusion models. Current SVG animation methods struggle with complex motions: LLM-based code synthesis fails to express fine, non-rigid B\\'ezier deformations, while Score Distillation Sampling (SDS) provides noisy gradients and often requires category-specific priors like skeletons. In contrast, LiveSVG fits vector geometry directly to an explicitly generated target video. Given an input SVG image and a motion prompt, we generate a previewable target video using a frozen image-to-vi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30174","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/2605.30174/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":"2605.30174","created_at":"2026-05-29T02:06:11.828606+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.30174v1","created_at":"2026-05-29T02:06:11.828606+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30174","created_at":"2026-05-29T02:06:11.828606+00:00"},{"alias_kind":"pith_short_12","alias_value":"4Y3LW4SQDDFB","created_at":"2026-05-29T02:06:11.828606+00:00"},{"alias_kind":"pith_short_16","alias_value":"4Y3LW4SQDDFBGWRZ","created_at":"2026-05-29T02:06:11.828606+00:00"},{"alias_kind":"pith_short_8","alias_value":"4Y3LW4SQ","created_at":"2026-05-29T02:06:11.828606+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/4Y3LW4SQDDFBGWRZZLI6J23PAP","json":"https://pith.science/pith/4Y3LW4SQDDFBGWRZZLI6J23PAP.json","graph_json":"https://pith.science/api/pith-number/4Y3LW4SQDDFBGWRZZLI6J23PAP/graph.json","events_json":"https://pith.science/api/pith-number/4Y3LW4SQDDFBGWRZZLI6J23PAP/events.json","paper":"https://pith.science/paper/4Y3LW4SQ"},"agent_actions":{"view_html":"https://pith.science/pith/4Y3LW4SQDDFBGWRZZLI6J23PAP","download_json":"https://pith.science/pith/4Y3LW4SQDDFBGWRZZLI6J23PAP.json","view_paper":"https://pith.science/paper/4Y3LW4SQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.30174&json=true","fetch_graph":"https://pith.science/api/pith-number/4Y3LW4SQDDFBGWRZZLI6J23PAP/graph.json","fetch_events":"https://pith.science/api/pith-number/4Y3LW4SQDDFBGWRZZLI6J23PAP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4Y3LW4SQDDFBGWRZZLI6J23PAP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4Y3LW4SQDDFBGWRZZLI6J23PAP/action/storage_attestation","attest_author":"https://pith.science/pith/4Y3LW4SQDDFBGWRZZLI6J23PAP/action/author_attestation","sign_citation":"https://pith.science/pith/4Y3LW4SQDDFBGWRZZLI6J23PAP/action/citation_signature","submit_replication":"https://pith.science/pith/4Y3LW4SQDDFBGWRZZLI6J23PAP/action/replication_record"}},"created_at":"2026-05-29T02:06:11.828606+00:00","updated_at":"2026-05-29T02:06:11.828606+00:00"}