{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:M3ZEA2HSCAJ563OTEJRSMAEDAU","short_pith_number":"pith:M3ZEA2HS","canonical_record":{"source":{"id":"2601.09243","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-01-14T07:26:55Z","cross_cats_sorted":[],"title_canon_sha256":"298c66da8aa1a77053ca539e2e080fdc1e8ef3b055c0c244965e38246add9fbc","abstract_canon_sha256":"ccefea3d8c2f67b9034c8138bb0b891b6dcfe77181e1b56029943126626ec550"},"schema_version":"1.0"},"canonical_sha256":"66f24068f21013df6dd322632600830508b9c08a74e10e3175d643e9a9a88ed5","source":{"kind":"arxiv","id":"2601.09243","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.09243","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"arxiv_version","alias_value":"2601.09243v2","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.09243","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"pith_short_12","alias_value":"M3ZEA2HSCAJ5","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"pith_short_16","alias_value":"M3ZEA2HSCAJ563OT","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"pith_short_8","alias_value":"M3ZEA2HS","created_at":"2026-07-17T01:21:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:M3ZEA2HSCAJ563OTEJRSMAEDAU","target":"record","payload":{"canonical_record":{"source":{"id":"2601.09243","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-01-14T07:26:55Z","cross_cats_sorted":[],"title_canon_sha256":"298c66da8aa1a77053ca539e2e080fdc1e8ef3b055c0c244965e38246add9fbc","abstract_canon_sha256":"ccefea3d8c2f67b9034c8138bb0b891b6dcfe77181e1b56029943126626ec550"},"schema_version":"1.0"},"canonical_sha256":"66f24068f21013df6dd322632600830508b9c08a74e10e3175d643e9a9a88ed5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-17T01:21:45.650036Z","signature_b64":"K+jXE+FN0yseVli79P/r89hxxRE7dop2Rx09rz7QYoLEVuMLc4hdVBbRPwYlBh+jObX0VznV6rXPpAFOvLyAAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"66f24068f21013df6dd322632600830508b9c08a74e10e3175d643e9a9a88ed5","last_reissued_at":"2026-07-17T01:21:45.649139Z","signature_status":"signed_v1","first_computed_at":"2026-07-17T01:21:45.649139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2601.09243","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-17T01:21:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/qLBbSN1fCviV1BU8OKPTPL349Rxfw4u7DBFFTMTdivzf+6Ff4PnOHOdTfJx91tX9taDjTQ3tQ/pchZXOQmQBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T11:15:29.086469Z"},"content_sha256":"ff65608e21396736a43153ae2454bc13971427e468690de4c049ca53c3678bba","schema_version":"1.0","event_id":"sha256:ff65608e21396736a43153ae2454bc13971427e468690de4c049ca53c3678bba"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:M3ZEA2HSCAJ563OTEJRSMAEDAU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A$^2$TG: Adaptive Anisotropic Textured Gaussians for Efficient 3D Scene Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hung-Kuo Chu, Sheng-Chi Hsu, Shih-Hsuan Hung, Ting-Yu Yen","submitted_at":"2026-01-14T07:26:55Z","abstract_excerpt":"Gaussian Splatting has emerged as a powerful representation for high-quality, real-time 3D scene rendering. While recent works extend Gaussians with learnable textures to enrich visual appearance, existing approaches allocate a fixed square texture per primitive, leading to inefficient memory usage and limited adaptability to scene variability. In this paper, we introduce adaptive anisotropic textured Gaussians (A$^2$TG), a novel representation that generalizes textured Gaussians by equipping each primitive with an anisotropic texture. Our method employs a gradient-guided adaptive rule to join"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.09243","kind":"arxiv","version":2},"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/2601.09243/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-17T01:21:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lsNB8fyOy4r0NmeqMu2nrP9ys+9Suutv6LBXf2T7+hGD2KW2JiKv0tX43PuiIzEPwaUuPLspYUZNS44FpRIzDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T11:15:29.086874Z"},"content_sha256":"c4685d8363ccc5a060dba2e8309e0b733c7da3570f225e3db135ad966b6dcec7","schema_version":"1.0","event_id":"sha256:c4685d8363ccc5a060dba2e8309e0b733c7da3570f225e3db135ad966b6dcec7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M3ZEA2HSCAJ563OTEJRSMAEDAU/bundle.json","state_url":"https://pith.science/pith/M3ZEA2HSCAJ563OTEJRSMAEDAU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M3ZEA2HSCAJ563OTEJRSMAEDAU/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T11:15:29Z","links":{"resolver":"https://pith.science/pith/M3ZEA2HSCAJ563OTEJRSMAEDAU","bundle":"https://pith.science/pith/M3ZEA2HSCAJ563OTEJRSMAEDAU/bundle.json","state":"https://pith.science/pith/M3ZEA2HSCAJ563OTEJRSMAEDAU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M3ZEA2HSCAJ563OTEJRSMAEDAU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:M3ZEA2HSCAJ563OTEJRSMAEDAU","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":"ccefea3d8c2f67b9034c8138bb0b891b6dcfe77181e1b56029943126626ec550","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-01-14T07:26:55Z","title_canon_sha256":"298c66da8aa1a77053ca539e2e080fdc1e8ef3b055c0c244965e38246add9fbc"},"schema_version":"1.0","source":{"id":"2601.09243","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.09243","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"arxiv_version","alias_value":"2601.09243v2","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.09243","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"pith_short_12","alias_value":"M3ZEA2HSCAJ5","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"pith_short_16","alias_value":"M3ZEA2HSCAJ563OT","created_at":"2026-07-17T01:21:45Z"},{"alias_kind":"pith_short_8","alias_value":"M3ZEA2HS","created_at":"2026-07-17T01:21:45Z"}],"graph_snapshots":[{"event_id":"sha256:c4685d8363ccc5a060dba2e8309e0b733c7da3570f225e3db135ad966b6dcec7","target":"graph","created_at":"2026-07-17T01:21:45Z","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/2601.09243/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Gaussian Splatting has emerged as a powerful representation for high-quality, real-time 3D scene rendering. While recent works extend Gaussians with learnable textures to enrich visual appearance, existing approaches allocate a fixed square texture per primitive, leading to inefficient memory usage and limited adaptability to scene variability. In this paper, we introduce adaptive anisotropic textured Gaussians (A$^2$TG), a novel representation that generalizes textured Gaussians by equipping each primitive with an anisotropic texture. Our method employs a gradient-guided adaptive rule to join","authors_text":"Hung-Kuo Chu, Sheng-Chi Hsu, Shih-Hsuan Hung, Ting-Yu Yen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-01-14T07:26:55Z","title":"A$^2$TG: Adaptive Anisotropic Textured Gaussians for Efficient 3D Scene Representation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.09243","kind":"arxiv","version":2},"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:ff65608e21396736a43153ae2454bc13971427e468690de4c049ca53c3678bba","target":"record","created_at":"2026-07-17T01:21:45Z","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":"ccefea3d8c2f67b9034c8138bb0b891b6dcfe77181e1b56029943126626ec550","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-01-14T07:26:55Z","title_canon_sha256":"298c66da8aa1a77053ca539e2e080fdc1e8ef3b055c0c244965e38246add9fbc"},"schema_version":"1.0","source":{"id":"2601.09243","kind":"arxiv","version":2}},"canonical_sha256":"66f24068f21013df6dd322632600830508b9c08a74e10e3175d643e9a9a88ed5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"66f24068f21013df6dd322632600830508b9c08a74e10e3175d643e9a9a88ed5","first_computed_at":"2026-07-17T01:21:45.649139Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-17T01:21:45.649139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"K+jXE+FN0yseVli79P/r89hxxRE7dop2Rx09rz7QYoLEVuMLc4hdVBbRPwYlBh+jObX0VznV6rXPpAFOvLyAAw==","signature_status":"signed_v1","signed_at":"2026-07-17T01:21:45.650036Z","signed_message":"canonical_sha256_bytes"},"source_id":"2601.09243","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ff65608e21396736a43153ae2454bc13971427e468690de4c049ca53c3678bba","sha256:c4685d8363ccc5a060dba2e8309e0b733c7da3570f225e3db135ad966b6dcec7"],"state_sha256":"3adb4b07b046b9df5931b76aeb02f30f9505f66bc04bd594942e1516a1787c87"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"khlyDmWgih5ebajY/9cXvr74YhAVZ/huRNTzW9360B4nxnywGyZw5qQSZFPDalbTeRm0U/lbXRTgif3hYDLpCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T11:15:29.108122Z","bundle_sha256":"c403d17b574f602b35f320647d7686240ad58778dbd62b341707b7febc018ac5"}}