{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QAPFYDGCTY7OMARQXCMAHTDYOQ","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":"54204887961760e96c8a9dc048995aed152a03073f9992c73ba5a41b5093fe3f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-20T19:10:37Z","title_canon_sha256":"51ac107001e5057db959d76ab71c010c2ab887a0ec918b07bf25841f8c92399b"},"schema_version":"1.0","source":{"id":"2503.16653","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.16653","created_at":"2026-07-05T10:37:48Z"},{"alias_kind":"arxiv_version","alias_value":"2503.16653v2","created_at":"2026-07-05T10:37:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.16653","created_at":"2026-07-05T10:37:48Z"},{"alias_kind":"pith_short_12","alias_value":"QAPFYDGCTY7O","created_at":"2026-07-05T10:37:48Z"},{"alias_kind":"pith_short_16","alias_value":"QAPFYDGCTY7OMARQ","created_at":"2026-07-05T10:37:48Z"},{"alias_kind":"pith_short_8","alias_value":"QAPFYDGC","created_at":"2026-07-05T10:37:48Z"}],"graph_snapshots":[{"event_id":"sha256:15ebac11b478ea97c501d6d996e1dd615a04431533861fea241627e4b0328cd1","target":"graph","created_at":"2026-07-05T10:37:48Z","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/2503.16653/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper propose iFlame, a novel transformer-based network architecture for mesh generation. While attention-based models have demonstrated remarkable performance in mesh generation, their quadratic computational complexity limits scalability, particularly for high-resolution 3D data. Conversely, linear attention mechanisms offer lower computational costs but often struggle to capture long-range dependencies, resulting in suboptimal outcomes. To address this trade-off, we propose an interleaving autoregressive mesh generation framework that combines the efficiency of linear attention with th","authors_text":"Biao Zhang, Dong-Ming Yan, Hanxiao Wang, Peter Wonka, Weize Quan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-20T19:10:37Z","title":"iFlame: Interleaving Full and Linear Attention for Efficient Mesh Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.16653","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":"sha256:27e7a11b05db1165ae259c407f643e43853bfedf46f0c8ae81eb06e4ac57efa3","target":"record","created_at":"2026-07-05T10:37:48Z","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":"54204887961760e96c8a9dc048995aed152a03073f9992c73ba5a41b5093fe3f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-20T19:10:37Z","title_canon_sha256":"51ac107001e5057db959d76ab71c010c2ab887a0ec918b07bf25841f8c92399b"},"schema_version":"1.0","source":{"id":"2503.16653","kind":"arxiv","version":2}},"canonical_sha256":"801e5c0cc29e3ee60230b89803cc787409ef30a7bbcf4ab6075142d081466ae6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"801e5c0cc29e3ee60230b89803cc787409ef30a7bbcf4ab6075142d081466ae6","first_computed_at":"2026-07-05T10:37:48.836903Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:37:48.836903Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"13amXf0JkfaqMzFO07f5Sdxh+a5CYbnZcDz657XgkqbpGhthQ/3/6SUyg7sakGHcH2F1243QrIgvoxK+RkOiCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:37:48.837494Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.16653","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:27e7a11b05db1165ae259c407f643e43853bfedf46f0c8ae81eb06e4ac57efa3","sha256:15ebac11b478ea97c501d6d996e1dd615a04431533861fea241627e4b0328cd1"],"state_sha256":"ebb166da4e86b54872c7488b6a6e9de36f75e75f38ce705b7346d33c587928a3"}