{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:26WCKIGWDDNZXOOGV54KU7DO54","short_pith_number":"pith:26WCKIGW","canonical_record":{"source":{"id":"2412.13654","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-18T09:33:20Z","cross_cats_sorted":[],"title_canon_sha256":"69f5a64804aa03b97dcfe78187f538293a1a553a8d97b28c809d592e4342976d","abstract_canon_sha256":"f4aaab69269c8bd9fafd31637a941c1d8c55d40b285d5c2095513bed82e11e80"},"schema_version":"1.0"},"canonical_sha256":"d7ac2520d618db9bb9c6af78aa7c6eef1bc960b0ee770aedd176cc20e1a61862","source":{"kind":"arxiv","id":"2412.13654","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.13654","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"arxiv_version","alias_value":"2412.13654v2","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.13654","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"pith_short_12","alias_value":"26WCKIGWDDNZ","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"pith_short_16","alias_value":"26WCKIGWDDNZXOOG","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"pith_short_8","alias_value":"26WCKIGW","created_at":"2026-07-05T10:27:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:26WCKIGWDDNZXOOGV54KU7DO54","target":"record","payload":{"canonical_record":{"source":{"id":"2412.13654","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-18T09:33:20Z","cross_cats_sorted":[],"title_canon_sha256":"69f5a64804aa03b97dcfe78187f538293a1a553a8d97b28c809d592e4342976d","abstract_canon_sha256":"f4aaab69269c8bd9fafd31637a941c1d8c55d40b285d5c2095513bed82e11e80"},"schema_version":"1.0"},"canonical_sha256":"d7ac2520d618db9bb9c6af78aa7c6eef1bc960b0ee770aedd176cc20e1a61862","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:27:22.213064Z","signature_b64":"JMq6GSTNOs6EMRtMIVsZIdJdSQedNAexBG3q2CS+HKSOzQwuZJJ5bzCyYHmctemTLrjXgzI5N4nrhbccyn3OBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d7ac2520d618db9bb9c6af78aa7c6eef1bc960b0ee770aedd176cc20e1a61862","last_reissued_at":"2026-07-05T10:27:22.212562Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:27:22.212562Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.13654","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":"2026-07-05T10:27:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iG7MHbV3loGAAuw/nd5kS4E5Ytg4bvoHxp89/UcpxThbUeo45A3JtZiTbJa0zp+MxuiGcEEwjnXrsqy/s1pPAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:11:09.983097Z"},"content_sha256":"7b980ec8f436f82c035d0064ac274d8d8f7ed1e62f13a8b946cba499e8c13657","schema_version":"1.0","event_id":"sha256:7b980ec8f436f82c035d0064ac274d8d8f7ed1e62f13a8b946cba499e8c13657"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:26WCKIGWDDNZXOOGV54KU7DO54","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GAGS: Granularity-Aware Feature Distillation for Language Gaussian Splatting","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bisheng Yang, Chenglu Wen, Haiping Wang, Yuan Liu, Yuning Peng, Zhen Dong","submitted_at":"2024-12-18T09:33:20Z","abstract_excerpt":"3D open-vocabulary scene understanding, which accurately perceives complex semantic properties of objects in space, has gained significant attention in recent years. In this paper, we propose GAGS, a framework that distills 2D CLIP features into 3D Gaussian splatting, enabling open-vocabulary queries for renderings on arbitrary viewpoints. The main challenge of distilling 2D features for 3D fields lies in the multiview inconsistency of extracted 2D features, which provides unstable supervision for the 3D feature field. GAGS addresses this challenge with two novel strategies. First, GAGS associ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.13654","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/2412.13654/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":"2026-07-05T10:27:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CtRGOm9zzorLWaemAyS4Cogru5D+CRL/o9Vab3wTfB1PqfFzbewps/jRy0ApwN333rVKleP15gCSyeRnnctDAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:11:09.983746Z"},"content_sha256":"75c44064d05f035b1e2b89e0e1817e7c7a3fa1786c853fe88ba7155f712bfc8e","schema_version":"1.0","event_id":"sha256:75c44064d05f035b1e2b89e0e1817e7c7a3fa1786c853fe88ba7155f712bfc8e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/26WCKIGWDDNZXOOGV54KU7DO54/bundle.json","state_url":"https://pith.science/pith/26WCKIGWDDNZXOOGV54KU7DO54/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/26WCKIGWDDNZXOOGV54KU7DO54/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":"2026-08-09T16:11:09Z","links":{"resolver":"https://pith.science/pith/26WCKIGWDDNZXOOGV54KU7DO54","bundle":"https://pith.science/pith/26WCKIGWDDNZXOOGV54KU7DO54/bundle.json","state":"https://pith.science/pith/26WCKIGWDDNZXOOGV54KU7DO54/state.json","well_known_bundle":"https://pith.science/.well-known/pith/26WCKIGWDDNZXOOGV54KU7DO54/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:26WCKIGWDDNZXOOGV54KU7DO54","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":"f4aaab69269c8bd9fafd31637a941c1d8c55d40b285d5c2095513bed82e11e80","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-18T09:33:20Z","title_canon_sha256":"69f5a64804aa03b97dcfe78187f538293a1a553a8d97b28c809d592e4342976d"},"schema_version":"1.0","source":{"id":"2412.13654","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.13654","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"arxiv_version","alias_value":"2412.13654v2","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.13654","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"pith_short_12","alias_value":"26WCKIGWDDNZ","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"pith_short_16","alias_value":"26WCKIGWDDNZXOOG","created_at":"2026-07-05T10:27:22Z"},{"alias_kind":"pith_short_8","alias_value":"26WCKIGW","created_at":"2026-07-05T10:27:22Z"}],"graph_snapshots":[{"event_id":"sha256:75c44064d05f035b1e2b89e0e1817e7c7a3fa1786c853fe88ba7155f712bfc8e","target":"graph","created_at":"2026-07-05T10:27:22Z","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/2412.13654/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"3D open-vocabulary scene understanding, which accurately perceives complex semantic properties of objects in space, has gained significant attention in recent years. In this paper, we propose GAGS, a framework that distills 2D CLIP features into 3D Gaussian splatting, enabling open-vocabulary queries for renderings on arbitrary viewpoints. The main challenge of distilling 2D features for 3D fields lies in the multiview inconsistency of extracted 2D features, which provides unstable supervision for the 3D feature field. GAGS addresses this challenge with two novel strategies. First, GAGS associ","authors_text":"Bisheng Yang, Chenglu Wen, Haiping Wang, Yuan Liu, Yuning Peng, Zhen Dong","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-18T09:33:20Z","title":"GAGS: Granularity-Aware Feature Distillation for Language Gaussian Splatting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.13654","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":"sha256:7b980ec8f436f82c035d0064ac274d8d8f7ed1e62f13a8b946cba499e8c13657","target":"record","created_at":"2026-07-05T10:27:22Z","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":"f4aaab69269c8bd9fafd31637a941c1d8c55d40b285d5c2095513bed82e11e80","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-18T09:33:20Z","title_canon_sha256":"69f5a64804aa03b97dcfe78187f538293a1a553a8d97b28c809d592e4342976d"},"schema_version":"1.0","source":{"id":"2412.13654","kind":"arxiv","version":2}},"canonical_sha256":"d7ac2520d618db9bb9c6af78aa7c6eef1bc960b0ee770aedd176cc20e1a61862","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7ac2520d618db9bb9c6af78aa7c6eef1bc960b0ee770aedd176cc20e1a61862","first_computed_at":"2026-07-05T10:27:22.212562Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:27:22.212562Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JMq6GSTNOs6EMRtMIVsZIdJdSQedNAexBG3q2CS+HKSOzQwuZJJ5bzCyYHmctemTLrjXgzI5N4nrhbccyn3OBA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:27:22.213064Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.13654","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7b980ec8f436f82c035d0064ac274d8d8f7ed1e62f13a8b946cba499e8c13657","sha256:75c44064d05f035b1e2b89e0e1817e7c7a3fa1786c853fe88ba7155f712bfc8e"],"state_sha256":"10a9d65af44f99efa72236f363516825b74f5fa7f3dc4defbdfc6772c590aee4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rmamC7h2/VhW1EEdcdVv3jzqYQvqKMyhqETkncF2M/BYDyovYFtIN9HWH+cAhXfqT2ArpVVDz4fRcihwEGKfBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T16:11:09.992729Z","bundle_sha256":"46f115fff6d6588b03e3cf1ccdb1bbf209ba95eb7d4441a4779f76323653beef"}}