{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:7Y2LLMYRPKCSJWHX63IVR2BTY5","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"11cbd9f447c30da2f9a4fad491f19665f2264529b5992530d4c4d8d658209a75","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-04T09:18:33Z","title_canon_sha256":"f5d50a30f8fbdf3614a86875ae33d420d99e2439e3a441536a590e9d21d2ed2f"},"schema_version":"1.0","source":{"id":"2606.05912","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.05912","created_at":"2026-06-05T01:15:27Z"},{"alias_kind":"arxiv_version","alias_value":"2606.05912v1","created_at":"2026-06-05T01:15:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05912","created_at":"2026-06-05T01:15:27Z"},{"alias_kind":"pith_short_12","alias_value":"7Y2LLMYRPKCS","created_at":"2026-06-05T01:15:27Z"},{"alias_kind":"pith_short_16","alias_value":"7Y2LLMYRPKCSJWHX","created_at":"2026-06-05T01:15:27Z"},{"alias_kind":"pith_short_8","alias_value":"7Y2LLMYR","created_at":"2026-06-05T01:15:27Z"}],"graph_snapshots":[{"event_id":"sha256:5d28d5cbf14353470e8afbde66feb4f4f0d3c7f664f4e792c82d558315e938b6","target":"graph","created_at":"2026-06-05T01:15:27Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.05912/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Modeling dynamic facial expressions using 3D Gaussian representations remains challenging due to their unstructured nature. Conventional Gaussian avatar pipelines require extensive multiview and sequential expression data, limiting scalability and accessibility. In this work, we introduce Self-Adaptive Gaussian Expression (SAGE), a framework for self-learning expression-induced Gaussian deformations that enables high-fidelity, animatable avatars from minimal input data. Our method jointly optimizes 2D Gaussian surfels and a Signed Distance Field (SDF) to enforce compact, surface-aligned Gaussi","authors_text":"Gregory Slabaugh, Jiahao Yang, Qing Wang, Shanxin Yuan, Xiaohang Yang, Yilan Dong","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-04T09:18:33Z","title":"Self-Learning Expression Deformations for Data-Efficient Gaussian Avatars"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05912","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:5bd3c96ecffee37bcf908bff4e087c1d67c8d0688d82925771d8119f8ad9c176","target":"record","created_at":"2026-06-05T01:15:27Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"11cbd9f447c30da2f9a4fad491f19665f2264529b5992530d4c4d8d658209a75","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-04T09:18:33Z","title_canon_sha256":"f5d50a30f8fbdf3614a86875ae33d420d99e2439e3a441536a590e9d21d2ed2f"},"schema_version":"1.0","source":{"id":"2606.05912","kind":"arxiv","version":1}},"canonical_sha256":"fe34b5b3117a8524d8f7f6d158e833c75d35ec0638701f233a8c12d862c0cb50","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fe34b5b3117a8524d8f7f6d158e833c75d35ec0638701f233a8c12d862c0cb50","first_computed_at":"2026-06-05T01:15:27.202063Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T01:15:27.202063Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vPvP489LPSaKWb9IQD2JNjYT9koomj5i5oJaZGRFuJxKBwJSZiWGeXud3ki/llnmZHUVhJDbYnZ42aMHofvUBA==","signature_status":"signed_v1","signed_at":"2026-06-05T01:15:27.202479Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.05912","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5bd3c96ecffee37bcf908bff4e087c1d67c8d0688d82925771d8119f8ad9c176","sha256:5d28d5cbf14353470e8afbde66feb4f4f0d3c7f664f4e792c82d558315e938b6"],"state_sha256":"b2bc8fe09b38dbc2a37fd9369d847f1c9b1f225ee3944c5e58f835d4346156d9"}