{"as_of":"2026-08-07T10:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:240f574ceb4083b55e9b0162f6cc97b0c87cb6e68375e2230105d6325f6df8c7","coverage":[{"denominator":66,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":66,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-16T20:34:16.666956Z","state":"measured"},{"denominator":67,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":67,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-01T06:28:47.232989Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-01T09:35:39.837421Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"cited_work":{"arxiv_id":"2512.17817","doi":null,"metadata_source":"pith","pith_arxiv_id":"2512.17817","snapshot_observed_at":"2026-07-01T09:35:39.837421Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","venue":"cs.CV","work_id":"df087f62-0bb0-4be8-a68f-fc93e77c59ab","year":2025},"citing_paper":{"arxiv_id":"2606.30754","last_updated":"2026-06-29T18:00:42Z","snapshot_observed_at":"2026-08-02T04:01:57.680474Z","submitted_at":"2026-06-29T18:00:42Z","title":"Streaming Gaussian Encoding for 4D Panoptic Occupancy Tracking","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-01T06:28:47.232989Z"},"links":{"cited_paper":"/paper/2512.17817","citing_paper":"/paper/2606.30754"},"observation_digest":"sha256:9ce7e6158551bd482c4825b997c9dc29dbac21780fb81b932ad4f982f12a1d51","observation_id":"729fc77a-aa1e-45a1-8440-0501a54db219","resolution":{"observed_at":"2026-07-01T09:35:39.839787Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2512.17817/citation-record","integrity":"/paper/2512.17817/integrity","json":"/paper/2512.17817/citation-record.json","paper":"/paper/2512.17817"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Referit3d: Neural listeners for fine-grained 3d object identification in real-world scenes","venue":null,"work_id":"fa5c786f-b3dc-4994-9852-1791c3d58edb","year":2020},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:d76ce2bce36f1f015e2ac874f5ed6ea1577b3741a5731ce36f055c62474cccb5","observation_id":"c67964b3-1728-43e3-b05b-083e678ae194","resolution":{"observed_at":"2026-05-17T01:13:48.948459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Crosspoint: Self-supervised cross-modal contrastive learning for 3d point cloud understanding","venue":null,"work_id":"728120d5-4023-4006-994d-0224caa90d08","year":2022},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:7cafedb55d174915151714f293b03147cd6f4e79d4a1fac3e382eb88896076ae","observation_id":"eb0cb245-befd-4ce8-938e-5d973810425f","resolution":{"observed_at":"2026-05-17T01:13:48.961096Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scanqa: 3d question answering for spatial scene understanding","venue":null,"work_id":"0a9f20dc-0a1b-4f6d-b821-c3f2c20462ad","year":2022},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:c8d110b2feb7bd0ea5289ada2ecf37f865e9a574b62f624a2fb556d72e45139f","observation_id":"78a72f3b-bc07-4cf2-a304-72d124a18c1e","resolution":{"observed_at":"2026-05-17T01:13:48.956023Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.08897","last_updated":"2022-01-12T08:19:29Z","snapshot_observed_at":"2026-07-06T12:09:19.763667Z","submitted_at":"2021-11-17T04:27:01Z","title":"ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data","version":3},"cited_work":{"arxiv_id":"2111.08897","doi":null,"metadata_source":"pith","pith_arxiv_id":"2111.08897","snapshot_observed_at":"2026-07-04T06:19:37.435697Z","title":"ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data","venue":"cs.CV","work_id":"0ce910be-ca1c-44c7-b7b1-c5353759d85e","year":2021},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2111.08897","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:f6b52ced125f92b77365e09f05b3073daec162e98dc34771dffced97fd45b1c7","observation_id":"67a541c4-872c-480d-81d1-3f9b4038a40c","resolution":{"observed_at":"2026-05-16T20:38:24.872378Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.13181","last_updated":"2025-04-28T18:01:39Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-17T17:59:57Z","title":"Perception Encoder: The best visual embeddings are not at the output of the network","version":2},"cited_work":{"arxiv_id":"2504.13181","doi":"10.48550/arxiv.2504.13181","metadata_source":"pith","pith_arxiv_id":"2504.13181","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Perception Encoder: The best visual embeddings are not at the output of the network","venue":"cs.CV","work_id":"409be941-4d4a-4ceb-a28a-eaa2d7709a1c","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2504.13181","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:0806e34bd914595b00420a8febf3272c877c2432b89c8d878de8d7dd9e6483c9","observation_id":"c8c9d038-827d-4b39-ac2a-7c12e3e875d8","resolution":{"observed_at":"2026-05-16T20:38:24.838182Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"From thousands to billions: 3d visual language grounding via render-supervised distillation from 2d vlms","venue":null,"work_id":"60efe9fe-63f8-4240-936a-ad7cb4fcfba9","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:9377107665b236dbc031895cc721b1c2a58b314fde59a0905bcb89ad6254b060","observation_id":"2355813e-e660-44ed-bbc7-e469b91094c0","resolution":{"observed_at":"2026-05-17T01:13:48.880538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Emerg- ing properties in self-supervised vision transformers","venue":null,"work_id":"77f558e6-a734-4bd7-b454-3c5bfe6a86a2","year":2021},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:a1b51cb4243b06290f607ae17d79db37ec1380cf50bdf536ffb05b342f72c15f","observation_id":"4ede3b8e-438d-4e97-bec4-23fb914ad538","resolution":{"observed_at":"2026-05-17T01:13:48.869078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.06158","last_updated":"2017-09-18T20:34:48Z","snapshot_observed_at":"2026-08-02T16:47:23.623541Z","submitted_at":"2017-09-18T20:34:48Z","title":"Matterport3D: Learning from RGB-D Data in Indoor Environments","version":1},"cited_work":{"arxiv_id":"1709.06158","doi":"10.48550/arxiv.1709.06158","metadata_source":"pith","pith_arxiv_id":"1709.06158","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Matterport3D: Learning from RGB-D Data in Indoor Environments","venue":"cs.CV","work_id":"a6675134-1bd7-4d3f-9344-d7072e7449e9","year":2017},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/1709.06158","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:838934ac2288f412e271a6c36c522ccd34ab41b2a8c6fda3bb555bf379bf0905","observation_id":"641eac48-1fe9-44da-ab9c-c7e8ed7528ab","resolution":{"observed_at":"2026-05-16T20:38:24.841202Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ll3da: Visual interactive instruction tuning for omni-3d understanding reasoning and planning","venue":null,"work_id":"754b2e02-8785-4567-a110-4d59cc7670a2","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:cdc586b76f3a6b77a673daea6357ad4a4bded1b3df7edbadb73e63a781db1f8a","observation_id":"28b4f8a3-4f12-455b-896c-27198a7655bf","resolution":{"observed_at":"2026-05-17T01:13:48.854653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scannet: Richly-annotated 3d reconstructions of indoor scenes","venue":null,"work_id":"4e00a9af-1ce5-400c-9dbc-6dca25b13a30","year":2017},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:6817e4708d2890a5889a724abef89fa8cde0d1da9bb783c598c643d6b5053f27","observation_id":"77516e75-4ecb-4e98-acc1-be59c7d3f5aa","resolution":{"observed_at":"2026-05-17T01:13:48.898343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pla: Language-driven open- vocabulary 3d scene understanding","venue":null,"work_id":"74d6b25f-179a-4ff0-bafe-cf363fbfd579","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:9876fc9ec4fb08dd2bef8a427602d62d900fa6f7cf77bbf1c1da93c635ceadbe","observation_id":"504d931b-5127-4267-9861-009240f7c804","resolution":{"observed_at":"2026-05-17T01:13:48.930066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scene-llm: Extending language model for 3d visual reasoning","venue":null,"work_id":"bf61220f-204f-4d9a-bbe9-70428e65e8e1","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:8389564aa4e743b50433714f0ac1edd79b500197cc7f5fda0769fc13bf6eedc6","observation_id":"18677c75-80ca-4b96-94cf-72143490baa6","resolution":{"observed_at":"2026-05-17T01:13:48.903673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Can3tok: Canonical 3d tokenization and latent modeling of scene-level 3d gaussians","venue":null,"work_id":"f6fa0b75-56b3-4c35-a84e-17332d27f702","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:ef860d8dc97da07eed737c2bad916c77640c311c2b387f881aa6c8ce5ba5eea3","observation_id":"6b98b2c7-8632-4cd3-94f4-a3868675c1e1","resolution":{"observed_at":"2026-05-17T01:13:48.893511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.00886","last_updated":"2025-07-01T15:52:59Z","snapshot_observed_at":"2026-08-06T21:02:39.083439Z","submitted_at":"2025-07-01T15:52:59Z","title":"GaussianVLM: Scene-centric 3D Vision-Language Models using Language-aligned Gaussian Splats for Embodied Reasoning and Beyond","version":1},"cited_work":{"arxiv_id":"2507.00886","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.00886","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Gaussianvlm: Scene-centric 3d vision-language models using language- aligned gaussian splats for embodied reasoning and beyond","venue":null,"work_id":"4bd5b345-8b04-4090-b596-414a2afcc851","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2507.00886","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:523fb0573b6777c68412b4f03fdc72e20d26349745a47bd1444746943c124017","observation_id":"f079f03d-4b14-4c66-bf24-7bbb12e19578","resolution":{"observed_at":"2026-05-16T20:38:24.856606Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Momentum contrast for unsupervised visual rep- resentation learning","venue":null,"work_id":"25139962-17f5-4023-b1f9-a77896a0bf62","year":2020},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:04ef56fe92457c934e92b12b1f4f45bcab98fe39f276ea7a7e4d901b2b2ee958","observation_id":"f62d39ba-aa17-45af-875a-632755a8d486","resolution":{"observed_at":"2026-05-17T01:13:48.791429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Masked autoencoders are scalable vision learners","venue":null,"work_id":"71535847-d8cd-4392-b733-372f417a01c4","year":2022},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:f15ebf06e780e98755c7533c32c970d8a435befd231a1918c679429c4231731e","observation_id":"b743ca39-caa1-4442-9d45-c36653151b41","resolution":{"observed_at":"2026-05-17T01:13:48.795062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"9a4bb1c7-3ca3-4895-ad57-d3c5b2ab42e9","year":null},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:ab48ed19dcd478285173cca8d4e60c37faaea9b577685f369853035d8f4a15c3","observation_id":"5ee9100e-2c76-4f14-a5dd-f4e2dae57a95","resolution":{"observed_at":"2026-05-17T01:13:48.801591Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":"1503.02531","doi":"10.1109/cvpr52733.2024.01515","metadata_source":"pith","pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Distilling the Knowledge in a Neural Network","venue":"stat.ML","work_id":"d927ab1f-17b8-4002-9d09-c3d55764fbad","year":2015},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:4153599f1f318921f3ac2db43a5ce03ef4a836309a024355cab0f781adf242f9","observation_id":"5d9cb9ae-7f10-4564-840e-eb724b70a999","resolution":{"observed_at":"2026-05-16T20:38:24.875254Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Gausstr: Foundation model-aligned gaussian transformer for self-supervised 3d spatial understanding","venue":null,"work_id":"28f024df-a1b9-472d-9cb7-e842f6a570f6","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:71c761d4ef2da8c320d1186af7ecad7a4698f7ccedd32b9f64bdd1b199acb222","observation_id":"1f02d051-09f1-40bf-a995-7fd652f7dcea","resolution":{"observed_at":"2026-05-17T01:13:48.821689Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Open-vocabulary 3d semantic segmentation with foundation models","venue":null,"work_id":"4b15b172-657f-4fbf-8420-f2fd9232363f","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:7a63988966b97356b4bbe4f063bcc44a5eb4e310fee3965fd31091d6166fb483","observation_id":"3e6228c7-a0a9-443c-b933-00eba4777e0c","resolution":{"observed_at":"2026-05-17T01:13:48.863158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Relaxing accurate initialization constraint for 3d gaussian splatting","venue":null,"work_id":"2ef39ee4-c8ae-44d0-9e32-61a5f07cce98","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:4de434e9ad959e206c58bde9686715cc727a835043ed938806a457574086ca7f","observation_id":"0afdc15b-7023-4038-a6bb-9ed3d8835233","resolution":{"observed_at":"2026-05-17T01:13:48.865875Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T07:46:04.037239Z","title":"3d gaussian splatting for real-time radiance field rendering.ACM Trans","venue":null,"work_id":"f02b3a8e-cb41-4f1f-ae1c-75b487ba20f9","year":null},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:5c508d1141c4d93e6c77baab46611f7e8d295658126e8236627d8dc29c2624fc","observation_id":"9e1b03ac-c89f-4a35-afcf-07d955968949","resolution":{"observed_at":"2026-05-17T01:13:48.872633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-06T01:01:40.223738Z","title":"Lerf: Language embedded radiance fields","venue":null,"work_id":"a228929c-ea73-405b-9da2-4a72782d81a9","year":null},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:544f6e1252c7e22c07be5d7141340b0f4fad0746fd395eb036c05ffb2f00878c","observation_id":"20331918-4403-4d46-9075-7241435c5184","resolution":{"observed_at":"2026-05-17T01:13:48.857709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"3d gaussian splat- ting as markov chain monte carlo.Advances in Neural Infor- mation Processing Systems, 37:80965–80986","venue":null,"work_id":"d04ac66b-a039-4091-80ca-1a3f7a4b6038","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:80e11213cfd6a100f7e54ab9c267f106c0580f69375c0a38ce92c52862a52942","observation_id":"7e070b50-3c26-4c52-8c6a-f980bc872535","resolution":{"observed_at":"2026-05-17T01:13:48.875497Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Segment any- thing","venue":null,"work_id":"18431f4b-522a-47d1-9fcd-e8d466a9b42d","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:be35714d059e3ff1b42c5750aaa385fc93146a9b8a3991b52f5db5486a7dfe5c","observation_id":"6b345b5d-59a7-45c5-b1d5-1fc2f0ef0c41","resolution":{"observed_at":"2026-05-17T01:13:48.940947Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mosaic3d: Foundation dataset and model for open-vocabulary 3d segmentation","venue":null,"work_id":"54c9546d-ceb9-4374-ab44-1e89faa2f9c5","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:d47e18c488b10bbea7667f7bc2de2d25abb0f0952b10782eafc8b786ea234b87","observation_id":"ca5c8233-86ce-48f0-9e0a-31eefe7e5873","resolution":{"observed_at":"2026-05-17T01:13:48.921197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.18052","last_updated":"2025-06-03T16:42:52Z","snapshot_observed_at":"2026-07-06T20:57:21.459904Z","submitted_at":"2025-03-23T12:50:25Z","title":"SceneSplat: Gaussian Splatting-based Scene Understanding with Vision-Language Pretraining","version":2},"cited_work":{"arxiv_id":"2503.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.18052","snapshot_observed_at":"2026-06-30T07:14:21.340168Z","title":"Scenesplat: Gaussian splatting-based scene un- derstanding with vision-language pretraining","venue":null,"work_id":"a1a529ef-0d88-4cd6-8082-7f758f07d865","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2503.18052","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:b24da43e242f733bd8471d48df7f9f15c38f52566dd2a2a1e17228950186f063","observation_id":"0ef09104-6d1c-4f86-8942-fa03950d7b82","resolution":{"observed_at":"2026-05-16T20:38:24.844419Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scenesplat++: A large dataset and com- prehensive benchmark for language gaussian splatting","venue":null,"work_id":"aac76753-93e1-477b-a25d-697c030ef0a3","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:243cc4cf94831d34fd1c05a7c910e44e7e405727877e9e22bd8c2d5ce98c8cbc","observation_id":"880451b1-0b6f-4766-a49f-8bd88cdaec8f","resolution":{"observed_at":"2026-05-17T01:13:48.886017Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A large-scale dataset of gaussian splats and their self-supervised pretrain- ing","venue":null,"work_id":"c3db43b0-38d8-4207-b43e-18692e7260d9","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:55963564789f00ae5b58739b54e551ca0d961a55bdb9238c4c7805800e832534","observation_id":"3aa4130e-36b1-4462-8b97-a93e190c375d","resolution":{"observed_at":"2026-05-17T01:13:48.798302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ludvig: Learning-free uplift- ing of 2d visual features to gaussian splatting scenes","venue":null,"work_id":"c0b5fa17-5121-4bf6-a5cd-b753b43de56b","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:df6d775b41273eafd4d3e6243517879350fab8c3adb499dba458b1252c29619a","observation_id":"591323bb-b25a-412c-bab9-f72f5431d9a8","resolution":{"observed_at":"2026-05-17T01:13:48.826363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:54:34.262354Z","title":"Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106","venue":null,"work_id":"cb45bd9c-4741-435d-ac44-8e1c90e27505","year":2021},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:243a7fd2c2ec4d505e5ff6ce9f31a68786bd59699b809fbbb3e25777442212bf","observation_id":"44749dc6-85bf-4f86-bcf7-a6aec81bbab6","resolution":{"observed_at":"2026-05-17T01:13:48.936785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-06T05:58:29.182448Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":"2304.07193","doi":"10.48550/arxiv.2304.07193","metadata_source":"pith","pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DINOv2: Learning Robust Visual Features without Supervision","venue":"cs.CV","work_id":"26b304e5-b54a-4f26-be7e-83299eca52e4","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:6fe37ccf7171e9d393a11b7672734e9cee78d0a5a2aa8791d425175648432d22","observation_id":"85d17996-51a1-4c69-836f-f9eef95124eb","resolution":{"observed_at":"2026-05-16T20:38:24.869229Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Masked autoencoders for 3d point cloud self- supervised learning.World Scientific Annual Review of Arti- ficial Intelligence, 1:2440001","venue":null,"work_id":"2e501615-afc6-4983-9f7d-9adc056284d8","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:0ee7bd1d3da931301f0b6873691b47a06031c0661c99643c21d42dbe82488932","observation_id":"78e50b7e-2531-41c0-82e9-187871786d62","resolution":{"observed_at":"2026-05-17T01:13:48.909609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"3d vision-language gaussian splatting","venue":null,"work_id":"95ad7603-77dc-4ddd-aa75-da4742ad25f2","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:813b3598acc9ce93f087842dfc21006a1016d7689622f2375dcc126681e98992","observation_id":"3c78f126-9547-4be4-a743-08ae5ddb3715","resolution":{"observed_at":"2026-05-17T01:13:48.895935Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Openscene: 3d scene understanding with open vocabularies","venue":null,"work_id":"4e1f9124-be57-4a97-a3b0-2f5ae1aadf43","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:5c021c898baaa369427bc3d861f2ea90dc6727cbe05b993c4dcbdca4c15f7b4c","observation_id":"f71dc532-0f77-45d2-87a6-238e684d5e37","resolution":{"observed_at":"2026-05-17T01:13:48.878066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T17:15:09.606701Z","title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","venue":null,"work_id":"45c3ecf6-4dcf-4a97-b4e6-9af89630c33a","year":null},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:5c5208c4b37d53d00d7eb0397a52453c3c5b68a8d394f79316a418288f063897","observation_id":"584f8741-f698-40ae-8d63-3c3c140ef7c6","resolution":{"observed_at":"2026-05-17T01:13:48.924231Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pointnet++: Deep hierarchical feature learning on point sets in a metric space.Advances in neural information processing systems, 30","venue":null,"work_id":"dd1c1870-f163-4460-ad1d-8ec80b02e3dd","year":2017},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:a1ab6b73c28f9445f968e685f56f632ee3e811e482e366f26fe626db2dd7f722","observation_id":"5e8936eb-9b97-4fbc-ac25-85cde2554cbf","resolution":{"observed_at":"2026-05-17T01:13:48.883240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Langsplat: 3d language gaussian splatting","venue":null,"work_id":"7a86b909-bcfa-4285-844d-0637d327ca86","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:cf286900c0c41726a22b08883d3c7d8df554638869b3847ee805ce1237c1f980","observation_id":"66018ff0-96c6-485c-9f8a-89c02bcd88e9","resolution":{"observed_at":"2026-05-17T01:13:48.851830Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T16:06:20.313807Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":"ee6b8956-3ac5-4cbe-9ab5-9c2078e5a407","year":2021},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:a123fae767dcb20debe96aa3043be8b94a6b0883110897e52716bbc5cfaf6a23","observation_id":"21d4068a-b39c-462a-ade9-37e32da45bc3","resolution":{"observed_at":"2026-05-17T01:13:48.849158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01680","last_updated":"2024-10-02T15:50:35Z","snapshot_observed_at":"2026-08-05T11:44:55.224063Z","submitted_at":"2024-10-02T15:50:35Z","title":"PHI-S: Distribution Balancing for Label-Free Multi-Teacher Distillation","version":1},"cited_work":{"arxiv_id":"2410.01680","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.01680","snapshot_observed_at":"2026-07-03T08:17:45.216951Z","title":"Phi-s: Dis- tribution balancing for label-free multi-teacher distillation","venue":null,"work_id":"7de364d7-bb65-4409-b1f8-cda92b99762b","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2410.01680","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:661098dfd7cba818873a145e7a5121bbe55fe19b3874a0f825d887b9f66fd047","observation_id":"d75c5cd3-22ca-4dcc-9f29-3104339fc51b","resolution":{"observed_at":"2026-05-16T20:38:24.866161Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Am-radio: Agglomerative vision foundation model reduce all domains into one","venue":null,"work_id":"19bf467d-caab-4edc-a439-14d1ecab1d05","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:589462e591d0d6099a692212d17fc8fb98a9ea889abcb0d9a43f03d5fd11fd29","observation_id":"3d7958e2-03b6-4315-87e6-3adf813115d8","resolution":{"observed_at":"2026-05-17T01:13:48.906657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Bringing masked autoencoders explicit con- trastive properties for point cloud self-supervised learning","venue":null,"work_id":"96a3b63a-4724-41df-9e27-790fc5fa9585","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:d0cb94f9f6d47ad8fc3de83e54178776f08e12686d57a01e144895d00acfb1ce","observation_id":"a384edb2-4eea-4584-904c-1d948ea89a1b","resolution":{"observed_at":"2026-05-17T01:13:48.932944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Language- grounded indoor 3d semantic segmentation in the wild","venue":null,"work_id":"7d6ae3e6-1f63-48e9-9f17-851ed2b665f7","year":2022},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:489354af7b5af30caa20f6dc15734786816926f871a101b114c322c62534769e","observation_id":"eee360c5-234c-4c20-8634-05f195b10a6d","resolution":{"observed_at":"2026-05-17T01:13:48.912433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dune: Distilling a universal encoder from heterogeneous 2d and 3d teachers","venue":null,"work_id":"5c6f5253-2b4d-4219-a09a-7727f0355a99","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:e820b26888fbacc7e2ba33563111287d67861bad828cb834665ee0ec0645f6b1","observation_id":"70a5c030-42af-46dd-907d-c68c6bfa6285","resolution":{"observed_at":"2026-05-17T01:13:48.915255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.03105","last_updated":"2023-04-12T09:22:53Z","snapshot_observed_at":"2026-07-06T14:01:25.012788Z","submitted_at":"2022-10-06T17:55:09Z","title":"Mask3D: Mask Transformer for 3D Semantic Instance Segmentation","version":2},"cited_work":{"arxiv_id":"2210.03105","doi":"10.48550/arxiv.2210.03105","metadata_source":"arxiv_reference","pith_arxiv_id":"2210.03105","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"org/10.48550/arXiv.2210.03105","venue":"arXiv (Cornell University)","work_id":"5609a96a-903c-4b47-9fb1-4a98ce757c3c","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2210.03105","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:12f328b30b48196e313de2edd5ff74c54f615443bc396304e25e5eb61840eb6b","observation_id":"22332c95-3692-4b7d-b631-efeed94f9385","resolution":{"observed_at":"2026-05-16T20:38:24.862923Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.10104","last_updated":"2025-08-13T18:00:55Z","snapshot_observed_at":"2026-07-06T22:12:35.584339Z","submitted_at":"2025-08-13T18:00:55Z","title":"DINOv3","version":1},"cited_work":{"arxiv_id":"2508.10104","doi":"10.1055/a-2487-1252","metadata_source":"pith","pith_arxiv_id":"2508.10104","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DINOv3","venue":"cs.CV","work_id":"c8b07deb-8fe7-4e18-9620-f3569d3529ce","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2508.10104","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:5cb0363b141037d3af67296861885fb83bbae94c2dd3ce98ba5b0e437cd8cde0","observation_id":"a8c005e7-5a87-47b4-808c-86c8990ac397","resolution":{"observed_at":"2026-05-16T20:38:24.853538Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"SpatialVerse Research Team","venue":null,"work_id":"384cd743-6e94-4490-a3a9-dd06d570af92","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:4132a04b3a03e3fb56dcffce97aca8eecaa79a820850a2017c8d8175d47e9f36","observation_id":"27a17d31-5672-4960-ae94-ab71611950d9","resolution":{"observed_at":"2026-05-17T01:13:48.830508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.14786","last_updated":"2025-02-20T18:08:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-20T18:08:29Z","title":"SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features","version":1},"cited_work":{"arxiv_id":"2502.14786","doi":"10.48550/arxiv.2502.14786","metadata_source":"pith","pith_arxiv_id":"2502.14786","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features","venue":"cs.CV","work_id":"50eec732-2d41-432f-9dcf-ac7fff235ea5","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2502.14786","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:4f2cafdc64d8b02e71bf6ec767dabdeab421c455b35dcfdaadc2eb82cb6aac2b","observation_id":"12246d20-8a6f-40f1-85fb-da146578092a","resolution":{"observed_at":"2026-05-16T20:38:24.847545Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-07-10T23:49:08.777694+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-10T23:49:08.777694+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Unipre3d: Unified pre-training of 3d point cloud models with cross-modal gaussian splatting","venue":null,"work_id":"22053513-1f4b-4222-91ff-ac60ee2d9d67","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:93983573e865f14de176a62b2e42b50509dc23c82b19779c1b8aa423fd03d10f","observation_id":"7f653455-3acb-47c5-bb18-1cfb061eec06","resolution":{"observed_at":"2026-05-17T01:13:48.834581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Point transformer v2: Grouped vector atten- tion and partition-based pooling","venue":null,"work_id":"1158bd79-aa73-4ebc-9b5d-df541cac598d","year":2022},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:8c5571ecbc52609457ba1f86c6213e780deffb97723695d432948bdee3685775","observation_id":"03485c16-0767-41c9-ae45-32c13970ea7f","resolution":{"observed_at":"2026-05-17T01:13:48.888734Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Masked scene contrast: A scalable framework for unsu- pervised 3d representation learning","venue":null,"work_id":"71d199f9-160b-41da-bcf6-f9d0be98f667","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:43c9499497052fce56e23f4024367159d561f9452a406c475ce0cef7bd426daa","observation_id":"93def5a3-7f75-407b-b12c-c3bf6d28fa10","resolution":{"observed_at":"2026-05-17T01:13:48.845972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Point transformer v3: Simpler faster stronger","venue":null,"work_id":"ca39b585-068b-4f93-a98f-902d9b059c83","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:b88e8d57c4b2a5e6203351767eefa62be0d56a1a627f4e4527910f0df31faf52","observation_id":"6d96a510-0234-4870-8393-fc7d42d9c8f6","resolution":{"observed_at":"2026-05-17T01:13:48.817110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Towards large- scale 3d representation learning with multi-dataset point prompt training","venue":null,"work_id":"ae27ef8d-93a7-41b2-aa4b-828cb179476d","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:d60487b958e4c6f76a89b1248532e3164f23e738279285d342076d8ca66a826f","observation_id":"e24b966e-a639-43b3-b255-ee921ba33303","resolution":{"observed_at":"2026-05-17T01:13:48.900889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sonata: Self- supervised learning of reliable point representations","venue":null,"work_id":"49294b20-a5ae-4f6a-8b0d-fec8932fda0d","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:e74729e9c9e792d64a8717bb2150c23f0b92ac6e00dc67eea86b1f75db242395","observation_id":"abd5b7a1-b91d-40ea-9566-e33f7006a577","resolution":{"observed_at":"2026-05-17T01:13:48.944201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pointcontrast: Unsupervised pre- training for 3d point cloud understanding","venue":null,"work_id":"aff57ba1-5c63-4fbf-967a-8e1f74e6ce7b","year":2020},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:e4faa9092467c96e7bbde0dff9059413895e8c934f8b096c8948063e8a65db90","observation_id":"8335650e-9d6b-41c4-b10d-30f98c97b976","resolution":{"observed_at":"2026-05-17T01:13:48.927175Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pointllm: Empowering large language models to understand point clouds","venue":null,"work_id":"56366a8a-51f6-42ee-83b1-052498230776","year":null},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:f147edb98e00f869a6b6ade1fe4b76bcb5fa01757caebc5ade36f81accc102aa","observation_id":"20ddfc54-d879-4dd5-878c-907f9366b727","resolution":{"observed_at":"2026-05-17T01:13:48.838940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding","venue":null,"work_id":"112e8dca-1c5c-4cd8-962d-dfb4f884b935","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:5084e4ce21f14b69a032b9ba874876b29f38e0f1ec84eb3a18740b55c34d4a0d","observation_id":"83126b87-8bc7-4217-84ec-ba1a92d69f0b","resolution":{"observed_at":"2026-05-17T01:13:48.842916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.06084","last_updated":"2024-07-08T16:26:52Z","snapshot_observed_at":"2026-07-06T18:43:09.852565Z","submitted_at":"2024-07-08T16:26:52Z","title":"3D Vision and Language Pretraining with Large-Scale Synthetic Data","version":1},"cited_work":{"arxiv_id":"2407.06084","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.06084","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"3d vision and language pre- training with large-scale synthetic data","venue":null,"work_id":"f6fbb437-6ef7-4f51-a5e9-643fb119f58a","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2407.06084","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:fe6ffab9e40323d0ebc79e56aaff25f67d09951c37ac7cb8ebb00dbc01744edb","observation_id":"0f75b524-9531-4b50-afc4-d6cb8250b81d","resolution":{"observed_at":"2026-05-16T20:38:24.850840Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Regionplc: Regional point-language contrastive learning for open-world 3d scene understanding","venue":null,"work_id":"20a0e3e2-1df8-4214-9680-8ccf4d586e2f","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:41eb3252c95ed4553b8bac81bc108f646b9f16a3925eca741ef3bd789c7c3036","observation_id":"f282a696-29e0-4ed7-9d00-59c6d11db7bd","resolution":{"observed_at":"2026-05-17T01:13:48.891068Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scannet++: A high-fidelity dataset of 3d in- door scenes","venue":null,"work_id":"3c703054-81a3-425f-8522-1f5f3090b90e","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:a58c5828a38a32c58625764e0b1a8030e53988d3aabf2b8093f171c0d517ece8","observation_id":"b8f3e168-8b05-492c-95a4-7cc1b5888b91","resolution":{"observed_at":"2026-05-17T01:13:48.860414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Point-bert: Pre-training 3d point cloud transformers with masked point modeling","venue":null,"work_id":"a7794e20-8216-476d-88a4-f9f8680dc39f","year":2022},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:d3ad9252646a43df913f139f90201f1cd848a94bc8e39eb2ebb510c8131dfc83","observation_id":"745fd570-eee4-4c80-bfbc-03eea206b2b5","resolution":{"observed_at":"2026-05-17T01:13:48.918294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sigmoid loss for language image pre-training","venue":null,"work_id":"1d9cb606-6e9a-4b37-891a-bdd0834c85e0","year":2023},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:bdfe4e0c2eb04e50ed1494f4d0ce3d85e45539b340d8f5aeac2ea6f65e1edbbd","observation_id":"fbcedb66-a499-4da0-a165-165a03cfbd86","resolution":{"observed_at":"2026-05-17T01:13:48.812657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.23607","doi":"10.48550/arxiv.2510.23607","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Zhang, X","venue":"arXiv (Cornell University)","work_id":"95fbd52d-e3f7-41b2-8b4f-cfd1201f62b6","year":2025},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:4d1e6259042d5c41003d5174a7152643180de4b9f5b3ffcb84e5bb2fb2b2c797","observation_id":"7ed42ef1-484e-4892-9a41-29471a19b70a","resolution":{"observed_at":"2026-05-16T20:38:24.859775Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Point transformer","venue":null,"work_id":"4f5e9e35-177a-4021-b92c-dea4d1f9d09d","year":2021},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:50f7588fd85f3cea2a9ba86b33fec72136c093283da88cded9b3ed3f70c68ab9","observation_id":"a1d13412-74dc-41c2-a763-60f1d821c866","resolution":{"observed_at":"2026-05-17T01:13:48.804418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Structured3d: A large photo-realistic dataset for structured 3d modeling","venue":null,"work_id":"6348c953-b545-4593-b057-9da6f029b044","year":2020},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:dd573fc8836a9d9ccf95546052c32d1efd0d134f481462ce9a73adb3db2b550a","observation_id":"3f757d37-9fe2-487e-b257-b8de3d05d1c3","resolution":{"observed_at":"2026-05-17T01:13:48.808356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.09637","last_updated":"2024-03-14T17:59:46Z","snapshot_observed_at":"2026-07-06T17:44:45.924645Z","submitted_at":"2024-03-14T17:59:46Z","title":"GaussianGrasper: 3D Language Gaussian Splatting for Open-vocabulary Robotic Grasping","version":1},"cited_work":{"arxiv_id":"2403.09637","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.09637","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2403.09637 (2024)","venue":null,"work_id":"af43db06-c223-451c-b4c9-565f47f54c9d","year":2024},"citing_paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding","version":3},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-16T20:34:16.666956Z"},"links":{"cited_paper":"/paper/2403.09637","citing_paper":"/paper/2512.17817"},"observation_digest":"sha256:70b3c9fe86e8970f9d98a4ce912e518464d6ba1997351bf94c744d2111eb70ed","observation_id":"2bd425b7-95d7-4cd3-8140-980d5d45f623","resolution":{"observed_at":"2026-05-16T20:38:24.835297Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2512.17817","last_updated":"2026-05-04T21:21:49Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-19T17:22:35Z","title":"Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding"},"reference_resolution":{"displayed":66,"state_counts":{"malformed_identifier":0,"metadata_mismatch":3,"parse_uncertain":0,"unresolved":1,"verified_exact":11,"verified_fuzzy":51},"total_outbound_references":66},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 1 inbound Pith citation observation for arXiv:2512.17817."}