{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5WOJ34G4GOZSSLKUXVVHUHFBY3","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":"fab2d1453fa204f09d0e994d40f5ee28c4f1aad94aa458214cf60c8e3328b36c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-07T17:57:03Z","title_canon_sha256":"c2359f27674e435131ddb8a6b0d80a6e05e5497bfb032287b46b1fea64a46eb8"},"schema_version":"1.0","source":{"id":"2402.05054","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.05054","created_at":"2026-07-05T07:42:35Z"},{"alias_kind":"arxiv_version","alias_value":"2402.05054v1","created_at":"2026-07-05T07:42:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.05054","created_at":"2026-07-05T07:42:35Z"},{"alias_kind":"pith_short_12","alias_value":"5WOJ34G4GOZS","created_at":"2026-07-05T07:42:35Z"},{"alias_kind":"pith_short_16","alias_value":"5WOJ34G4GOZSSLKU","created_at":"2026-07-05T07:42:35Z"},{"alias_kind":"pith_short_8","alias_value":"5WOJ34G4","created_at":"2026-07-05T07:42:35Z"}],"graph_snapshots":[{"event_id":"sha256:46c053ff192c09535bcc4362b1b87d02641cdab223054ae5050aaabd906fdeae","target":"graph","created_at":"2026-07-05T07:42:35Z","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/2402.05054/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"3D content creation has achieved significant progress in terms of both quality and speed. Although current feed-forward models can produce 3D objects in seconds, their resolution is constrained by the intensive computation required during training. In this paper, we introduce Large Multi-View Gaussian Model (LGM), a novel framework designed to generate high-resolution 3D models from text prompts or single-view images. Our key insights are two-fold: 1) 3D Representation: We propose multi-view Gaussian features as an efficient yet powerful representation, which can then be fused together for dif","authors_text":"Gang Zeng, Jiaxiang Tang, Tengfei Wang, Xiaokang Chen, Zhaoxi Chen, Ziwei Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-07T17:57:03Z","title":"LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.05054","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:f0b696b16de12a8e942e2fea63c37eb3de3c236d0dc683653ec415df765e940b","target":"record","created_at":"2026-07-05T07:42:35Z","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":"fab2d1453fa204f09d0e994d40f5ee28c4f1aad94aa458214cf60c8e3328b36c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-07T17:57:03Z","title_canon_sha256":"c2359f27674e435131ddb8a6b0d80a6e05e5497bfb032287b46b1fea64a46eb8"},"schema_version":"1.0","source":{"id":"2402.05054","kind":"arxiv","version":1}},"canonical_sha256":"ed9c9df0dc33b3292d54bd6a7a1ca1c6fa3ef089551d02c06372394d4d9e31ee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ed9c9df0dc33b3292d54bd6a7a1ca1c6fa3ef089551d02c06372394d4d9e31ee","first_computed_at":"2026-07-05T07:42:35.628806Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:42:35.628806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HkQT2CGeV1YpazBsNWbnOx5GXwWnSXB/k9xBl+jIGxKcn24Qx2/5eNRF2v9L2TJRG26ZIteN3BM3kprwsBbDDA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:42:35.629213Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.05054","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f0b696b16de12a8e942e2fea63c37eb3de3c236d0dc683653ec415df765e940b","sha256:46c053ff192c09535bcc4362b1b87d02641cdab223054ae5050aaabd906fdeae"],"state_sha256":"3742bfd74da4cf41e5f313ca8ae60eb0257696458f1641a40697057b9ace4311"}