{"as_of":"2026-08-18T16:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e0d5e2478374e6b8095fbe54c9fbc3675d4e2a78a6e4da4562bb66f7f68e6ded","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":18,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:18:25.935849Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T09:19:42.969889Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-08-12T14:01:46.766565Z","title":"Learn- ing to manipulate anywhere: A visual generalizable framework for reinforcement learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.16755","last_updated":"2024-11-24T07:30:54Z","snapshot_observed_at":"2026-08-16T06:06:49.584232Z","submitted_at":"2024-11-24T07:30:54Z","title":"FunGrasp: Functional Grasping for Diverse Dexterous Hands","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T14:01:46.766565Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2411.16755"},"observation_digest":"sha256:1dadacbc53b2acc09e68cff1a9d33fd3adb1668423c812e9a52c5229f7f2005e","observation_id":"e26ed806-c873-40f5-b2ec-e33036ff3f3a","resolution":{"observed_at":"2026-08-12T14:01:46.766565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-08-11T22:38:33.305761Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03293","last_updated":"2025-06-04T08:30:06Z","snapshot_observed_at":"2026-08-16T21:12:40.974751Z","submitted_at":"2024-12-04T13:11:38Z","title":"Diffusion-VLA: Generalizable and Interpretable Robot Foundation Model via Self-Generated Reasoning","version":3},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-11T22:38:33.305761Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2412.03293"},"observation_digest":"sha256:c8dfbf243f2a56da1b7eb67786c4972bdb65468068ab49891f6f737e3d552235","observation_id":"e425115c-9b20-484f-b73e-69965c97da97","resolution":{"observed_at":"2026-08-11T22:38:33.305761Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-08-11T20:57:12.521885Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.05268","last_updated":"2024-12-06T18:55:09Z","snapshot_observed_at":"2026-08-13T09:52:42.403876Z","submitted_at":"2024-12-06T18:55:09Z","title":"DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-11T20:57:12.521885Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2412.05268"},"observation_digest":"sha256:8d10f10bc5e6f48ad405a3b17be032808383f903f331751088805e920f5eb107","observation_id":"807a81e8-a895-4c32-ae7b-74a84e5ab0a8","resolution":{"observed_at":"2026-08-11T20:57:12.521885Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-08-08T13:00:39.187433Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.07380","last_updated":"2025-08-30T21:44:04Z","snapshot_observed_at":"2026-08-16T02:58:44.580749Z","submitted_at":"2025-02-11T08:57:41Z","title":"Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-08T13:00:39.187433Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2502.07380"},"observation_digest":"sha256:b9713026a5aed5510488f4223e8c5fe5138fc74cc6483311841b5ad37521b176","observation_id":"a4f59524-45c5-47fa-aaba-0f5a101f07b1","resolution":{"observed_at":"2026-08-08T13:00:39.187433Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-08-16T12:18:25.935849Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.13175","last_updated":"2025-04-17T17:59:43Z","snapshot_observed_at":"2026-08-17T15:25:04.438378Z","submitted_at":"2025-04-17T17:59:43Z","title":"Novel Demonstration Generation with Gaussian Splatting Enables Robust One-Shot Manipulation","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-16T12:18:25.935849Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2504.13175"},"observation_digest":"sha256:f07b82aac99d0a0a162154e5327d78791903cff9391c3447cb6f046db24fe310","observation_id":"ac7961d7-f576-4719-bf5f-4b87edb85ed2","resolution":{"observed_at":"2026-08-16T12:18:25.935849Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-08-15T23:29:32.078898Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04619","last_updated":"2025-08-29T14:54:30Z","snapshot_observed_at":"2026-08-17T21:33:27.152159Z","submitted_at":"2025-05-07T17:59:28Z","title":"Merging and Disentangling Views in Visual Reinforcement Learning for Robotic Manipulation","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:32.078898Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2505.04619"},"observation_digest":"sha256:971ff25058636218716cf9327b1db4f7749f1407b62668d3536c132025b3b423","observation_id":"65bf7690-6596-44bd-8681-3bd7e2cb2384","resolution":{"observed_at":"2026-08-15T23:29:32.078898Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-08-15T22:12:22.886471Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.07819","last_updated":"2025-06-17T08:36:51Z","snapshot_observed_at":"2026-08-18T13:00:26.664278Z","submitted_at":"2025-05-12T17:59:43Z","title":"H$^3$DP: Triply-Hierarchical Diffusion Policy for Visuomotor Learning","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T22:12:22.886471Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2505.07819"},"observation_digest":"sha256:23bd07933282f701af9e660f6469098d799a380138daf2380822f3b6ee20d31a","observation_id":"2f254162-3a68-4e61-9d13-f02813d20fe3","resolution":{"observed_at":"2026-08-15T22:12:22.886471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-08-06T22:04:34.686270Z","title":"Learning to manipulate any- where: A visual generalizable framework for reinforcement learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.22756","last_updated":"2025-06-28T05:03:31Z","snapshot_observed_at":"2026-08-14T17:47:41.760864Z","submitted_at":"2025-06-28T05:03:31Z","title":"RoboPearls: Editable Video Simulation for Robot Manipulation","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-06T22:04:34.686270Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2506.22756"},"observation_digest":"sha256:36bdf5a13a8ab5377f6ee2b505d28f48202c9922456903d9192f5083579d9476","observation_id":"5fb88f38-08dc-41bf-a731-8ecdce4377e2","resolution":{"observed_at":"2026-08-06T22:04:34.686270Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-08-05T05:47:31.510415Z","title":"Learn- ing to manipulate anywhere: A visual generalizable framework for reinforcement learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.04970","last_updated":"2025-09-05T09:52:08Z","snapshot_observed_at":"2026-08-16T14:26:10.968986Z","submitted_at":"2025-09-05T09:52:08Z","title":"DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T05:47:31.510415Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2509.04970"},"observation_digest":"sha256:c43fe52ca917b28763ab2d5b0f4407485c971996793625c9e6cbf57c6e0148b1","observation_id":"7e08bd72-de2f-48df-b64a-94b96a15a174","resolution":{"observed_at":"2026-08-05T05:47:31.510415Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2407.15815","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-07-04T09:19:42.969889Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":"7212d1c7-d50b-4e95-bc06-c6dfbf7b53a7","year":2024},"citing_paper":{"arxiv_id":"2509.09674","last_updated":"2025-09-11T17:59:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-11T17:59:17Z","title":"SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-15T08:02:11.189795Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2509.09674"},"observation_digest":"sha256:02279b0f5903d65fbe595c730d524fe0d7a4e33b97b58a8f062755f4505f0b7b","observation_id":"af4cad6e-cb31-41c1-bd65-1c506c350e7c","resolution":{"observed_at":"2026-05-15T08:02:11.434219Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2407.15815","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-07-04T09:19:42.969889Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":"7212d1c7-d50b-4e95-bc06-c6dfbf7b53a7","year":2024},"citing_paper":{"arxiv_id":"2602.16712","last_updated":"2026-05-15T19:05:22Z","snapshot_observed_at":"2026-08-16T06:46:37.924671Z","submitted_at":"2026-02-18T18:59:57Z","title":"One Hand to Rule Them All: Canonical Representations for Unified Dexterous Manipulation","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-21T12:29:09.497661Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2602.16712"},"observation_digest":"sha256:0fb529e6f82abf4a0e98c6be919dc5ad7a3cbe258a685c78c031252f53886693","observation_id":"9b9c7080-d926-47d3-913e-f52d6051a52f","resolution":{"observed_at":"2026-05-21T12:30:07.553096Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2407.15815","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-07-04T09:19:42.969889Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":"7212d1c7-d50b-4e95-bc06-c6dfbf7b53a7","year":2024},"citing_paper":{"arxiv_id":"2604.15023","last_updated":"2026-04-16T13:53:01Z","snapshot_observed_at":"2026-08-15T03:43:33.132771Z","submitted_at":"2026-04-16T13:53:01Z","title":"DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-10T10:17:26.903231Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2604.15023"},"observation_digest":"sha256:6f7e12e7f2cb7ff753b7d6750adc710dd856d67362642149c35796fca3f94c98","observation_id":"4f1c7726-e860-4e3f-b64e-f548c7943598","resolution":{"observed_at":"2026-05-10T10:19:20.200096Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2407.15815","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-07-04T09:19:42.969889Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":"7212d1c7-d50b-4e95-bc06-c6dfbf7b53a7","year":2024},"citing_paper":{"arxiv_id":"2604.26509","last_updated":"2026-05-08T13:30:17Z","snapshot_observed_at":"2026-08-11T16:14:56.361924Z","submitted_at":"2026-04-29T10:17:55Z","title":"3D Generation for Embodied AI and Robotic Simulation: A Survey","version":1},"reference_index":172,"source":"pdf_text","source_observed_at":"2026-05-07T13:16:44.508344Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2604.26509"},"observation_digest":"sha256:3da611d1281a2820e8dffd70564c35bf12db9882b6ea34c8de53bf9027b027ad","observation_id":"b1be1fe7-1c3f-40b0-9138-748b8fb43046","resolution":{"observed_at":"2026-05-12T09:01:25.431015Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2407.15815","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-07-04T09:19:42.969889Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":"7212d1c7-d50b-4e95-bc06-c6dfbf7b53a7","year":2024},"citing_paper":{"arxiv_id":"2604.26509","last_updated":"2026-05-08T13:30:17Z","snapshot_observed_at":"2026-08-11T16:14:56.361924Z","submitted_at":"2026-04-29T10:17:55Z","title":"3D Generation for Embodied AI and Robotic Simulation: A Survey","version":2},"reference_index":172,"source":"pdf_text","source_observed_at":"2026-05-08T03:31:05.311070Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2604.26509"},"observation_digest":"sha256:770deded5f00a0e5f6be2c069f4f8c9bf3e4d53bd92b8bcce6afc79547912800","observation_id":"6f77de62-09fd-4640-9af4-f709e67b63b0","resolution":{"observed_at":"2026-05-11T22:06:13.023187Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2407.15815","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-07-04T09:19:42.969889Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":"7212d1c7-d50b-4e95-bc06-c6dfbf7b53a7","year":2024},"citing_paper":{"arxiv_id":"2604.26509","last_updated":"2026-05-08T13:30:17Z","snapshot_observed_at":"2026-08-11T16:14:56.361924Z","submitted_at":"2026-04-29T10:17:55Z","title":"3D Generation for Embodied AI and Robotic Simulation: A Survey","version":3},"reference_index":172,"source":"pdf_text","source_observed_at":"2026-05-11T01:56:24.510913Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2604.26509"},"observation_digest":"sha256:13bf2648dd4bcbdaf9f9064ab1dc0f5b5c6397f3c5f159c20f7d9e0bfbed9987","observation_id":"f53ec3fe-5641-462d-a7a3-51fe08ad38f1","resolution":{"observed_at":"2026-05-11T04:05:59.046809Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2407.15815","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-07-04T09:19:42.969889Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":"7212d1c7-d50b-4e95-bc06-c6dfbf7b53a7","year":2024},"citing_paper":{"arxiv_id":"2606.22471","last_updated":"2026-06-29T14:49:32Z","snapshot_observed_at":"2026-08-12T12:21:36.342489Z","submitted_at":"2026-06-21T12:31:59Z","title":"Scalable Multi-Task Data Generation via Reinforcement Learning for Language-Conditioned Bimanual Dexterous Manipulation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-26T10:18:01.230648Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2606.22471"},"observation_digest":"sha256:a3b5385c97e70a4eb6d3aaac721037a60b172911c4ee4b304c1f609c8d954a94","observation_id":"8cab7d7d-a445-40da-8c25-710cd62bd6c2","resolution":{"observed_at":"2026-07-04T09:19:42.971686Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2407.15815","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-07-04T09:19:42.969889Z","title":"Learning to manipulate anywhere: A visual generalizable framework for reinforcement learning","venue":null,"work_id":"7212d1c7-d50b-4e95-bc06-c6dfbf7b53a7","year":2024},"citing_paper":{"arxiv_id":"2606.22471","last_updated":"2026-06-29T14:49:32Z","snapshot_observed_at":"2026-08-12T12:21:36.342489Z","submitted_at":"2026-06-21T12:31:59Z","title":"Scalable Multi-Task Data Generation via Reinforcement Learning for Language-Conditioned Bimanual Dexterous Manipulation","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-30T10:46:26.385071Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2606.22471"},"observation_digest":"sha256:eb9fe41ecfafbf3d6f3ae211c87d5013f1784a787242c1d581ec9e1a909fdea3","observation_id":"37a7f439-aa69-4a6a-be3e-2587b4f14265","resolution":{"observed_at":"2026-06-30T10:54:36.914892Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15815","snapshot_observed_at":"2026-07-11T20:32:22.412216Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04265","last_updated":"2026-07-05T12:24:14Z","snapshot_observed_at":"2026-08-13T00:19:28.599201Z","submitted_at":"2026-07-05T12:24:14Z","title":"HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-11T20:32:22.412216Z"},"links":{"cited_paper":"/paper/2407.15815","citing_paper":"/paper/2607.04265"},"observation_digest":"sha256:be97c336905c16dc1d36193bdb28f171695200727b71ee840c375332e214cf15","observation_id":"ce9bad05-4d09-4e77-8520-05ba9bc6ce06","resolution":{"observed_at":"2026-07-11T20:32:22.412216Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2407.15815/citation-record","integrity":"/paper/2407.15815/integrity","json":"/paper/2407.15815/citation-record.json","paper":"/paper/2407.15815"},"outbound":[],"paper":{"arxiv_id":"2407.15815","last_updated":"2024-10-23T05:32:34Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-16T13:32:03.635999Z","submitted_at":"2024-07-22T17:29:02Z","title":"Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2407.15815."}