{"as_of":"2026-08-08T17:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d17b1a3628e8fe58b579c725574d7c5c7f4bf1f7c07cec98c71dbaf77a624fd9","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T18:34:52.078107Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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":"2026-05-13T04:32:36.110870Z","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":"2026-05-13T04:37:15.846715Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"cited_work":{"arxiv_id":"2603.08541","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2603.08541","snapshot_observed_at":"2026-07-22T01:22:21.451305Z","title":"Equibim: Learning symmetry-equivariant policy for bimanual ma- nipulation","venue":null,"work_id":"13188bcd-7329-46ca-81bf-d1ca248ce3e3","year":2026},"citing_paper":{"arxiv_id":"2605.12228","last_updated":"2026-05-12T15:04:38Z","snapshot_observed_at":"2026-07-31T19:24:18.248951Z","submitted_at":"2026-05-12T15:04:38Z","title":"Morphologically Equivariant Flow Matching for Bimanual Mobile Manipulation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-13T04:32:36.110870Z"},"links":{"cited_paper":"/paper/2603.08541","citing_paper":"/paper/2605.12228"},"observation_digest":"sha256:75fde569bc9d0197c7fc9c20c78e4ea1c0b3478a65fe2a84603161caeb7554d5","observation_id":"527af1a4-4125-4e7e-8540-6aa1da79aeaf","resolution":{"observed_at":"2026-07-22T01:22:21.451305Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2603.08541/citation-record","integrity":"/paper/2603.08541/integrity","json":"/paper/2603.08541/citation-record.json","paper":"/paper/2603.08541"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:47.873397Z","title":"An algorithmic perspective on imitation learning.F oundations and Trends® in Robotics, 7(1-2):1–179, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:47.873397Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:99ae1f94f9112b334fdb636023f7942b04634ebdf17175ba011a7c6bc47aae3f","observation_id":"4b91cc10-4143-4afc-a586-e44b7117c91b","resolution":{"observed_at":"2026-08-02T18:34:47.873397Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:48.031543Z","title":"Diffusion policy: Visuomotor policy learning via action diffusion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:48.031543Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:57744c3bf7f29282329eace01dc20d70ffdf15e08d1819e7351d4c4ab10b406e","observation_id":"f23a3df7-f0d3-46f1-948c-df469bb27708","resolution":{"observed_at":"2026-08-02T18:34:48.031543Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:48.179375Z","title":"Learning fine-grained bimanual manipulation with low-cost hardware","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:48.179375Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:681a940426caea022eb062c2997eeccce0b48a03fd0706004b65f6243c474b4b","observation_id":"7841476d-6b52-4d4c-b200-36540940be7a","resolution":{"observed_at":"2026-08-02T18:34:48.179375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13126","last_updated":"2024-10-17T01:29:49Z","snapshot_observed_at":"2026-08-05T13:44:48.719708Z","submitted_at":"2024-10-17T01:29:49Z","title":"ALOHA Unleashed: A Simple Recipe for Robot Dexterity","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13126","snapshot_observed_at":"2026-08-02T18:34:48.292604Z","title":"Aloha unleashed: A simple recipe for robot dexterity.arXiv preprint arXiv:2410.13126, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:48.292604Z"},"links":{"cited_paper":"/paper/2410.13126","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:4ee2785ad5f07256bd866bdd17c762b7ba1e90ca14a88b1303c71696874a14cd","observation_id":"47bc1e13-77e5-4979-a8dc-bf19b2ed0161","resolution":{"observed_at":"2026-08-02T18:34:48.292604Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:48.408594Z","title":"Dexterous manipulation through imitation learning: A survey","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:48.408594Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:df41007ba200d356c1e4063e51f10b85f44b3a7b302d33512bb34b4681462d6f","observation_id":"1ef030be-b40c-4d4d-82e1-c7807def1928","resolution":{"observed_at":"2026-08-02T18:34:48.408594Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:48.552874Z","title":"Tacdiffusion: Force-domain diffusion policy for precise tactile ma- nipulation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:48.552874Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:974a2e08989a3bdc9bbaa6b1cfd064554db1cd9faf8be74b711da7526380cd37","observation_id":"c8142dc8-0b54-47d4-9a11-fe20b8e8141d","resolution":{"observed_at":"2026-08-02T18:34:48.552874Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09577","last_updated":"2025-05-14T17:29:35Z","snapshot_observed_at":"2026-08-07T15:45:21.303112Z","submitted_at":"2025-05-14T17:29:35Z","title":"VTLA: Vision-Tactile-Language-Action Model with Preference Learning for Insertion Manipulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09577","snapshot_observed_at":"2026-08-02T18:34:48.702793Z","title":"Vtla: Vision-tactile-language-action model with preference learning for insertion manipulation.arXiv preprint arXiv:2505.09577, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:48.702793Z"},"links":{"cited_paper":"/paper/2505.09577","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:1a8a76f0e2de7ccb477a30d08930eb43007c56fdd18b300af1341cf315633354","observation_id":"87599493-c667-41ca-a8d9-1eb946e8a5af","resolution":{"observed_at":"2026-08-02T18:34:48.702793Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:48.824351Z","title":"Manifeel: Benchmarking and under- standing visuotactile manipulation policy learning.arXiv preprint arXiv:2505.18472, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:48.824351Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:610e9391f57371faf93d7602e58a7ae42c10d29d9462956bed5456632a818fca","observation_id":"267f46e5-c9ff-43b2-a847-9c7ac33d94d3","resolution":{"observed_at":"2026-08-02T18:34:48.824351Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.15953","last_updated":"2026-05-13T00:42:26Z","snapshot_observed_at":"2026-07-06T21:44:32.853406Z","submitted_at":"2025-06-19T01:38:13Z","title":"ViTacFormer: Learning Cross-Modal Representation for Visuo-Tactile Dexterous Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.15953","snapshot_observed_at":"2026-08-02T18:34:48.952790Z","title":"Vitacformer: Learning cross-modal representation for visuo- tactile dexterous manipulation.arXiv preprint arXiv:2506.15953, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:48.952790Z"},"links":{"cited_paper":"/paper/2506.15953","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:9fd16be7f65ffb6cf17df62c8615045c78e8590e5027c5e665cf141f770d4e33","observation_id":"897036b5-5a46-4455-a6b4-4fc46080d6a9","resolution":{"observed_at":"2026-08-02T18:34:48.952790Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:49.090689Z","title":"Dexmimicgen: Automated data generation for bimanual dexterous manipulation via imitation learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:49.090689Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:e9a917ebb95f4aa3d4fbfbb735c5f27abdcefeee2918b8daf8652402be9f0559","observation_id":"2f5d113e-45b6-4320-aba5-8b2e51e533a8","resolution":{"observed_at":"2026-08-02T18:34:49.090689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:49.211247Z","title":"Canonical policy: Learning canonical 3d representation for equivariant policy.arXiv preprint arXiv:2505.18474, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:49.211247Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:426635ffd857ce800cb3c9364003dcc9aa95b240e1492fbdbe4492663e738256","observation_id":"072ac9cc-5879-4bd0-b041-9964a441e03f","resolution":{"observed_at":"2026-08-02T18:34:49.211247Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:49.328784Z","title":"A comparison of imitation learning algorithms for bimanual manipulation.IEEE Robotics and Automation Letters (RA-L), 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:49.328784Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:3a07c9e9d8d923f77ee04f5a5fea1be020730355f474e1da69e8d38040a5f3dd","observation_id":"9b132e2f-5151-4355-b634-6fd2389190eb","resolution":{"observed_at":"2026-08-02T18:34:49.328784Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.05287","last_updated":"2025-09-01T18:49:59Z","snapshot_observed_at":"2026-08-07T15:48:48.483917Z","submitted_at":"2025-05-08T14:29:00Z","title":"Morphologically Symmetric Reinforcement Learning for Ambidextrous Bimanual Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.05287","snapshot_observed_at":"2026-08-02T18:34:49.498981Z","title":"Morphologically symmetric reinforce- ment learning for ambidextrous bimanual manipulation.arXiv preprint arXiv:2505.05287, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:49.498981Z"},"links":{"cited_paper":"/paper/2505.05287","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:c6bbb65641e3d67f8b97f4190e603578ce9f9521fecf1c7ee3f3f7ab1721f387","observation_id":"988bf897-626d-4fda-9a25-d0a9b092ab1a","resolution":{"observed_at":"2026-08-02T18:34:49.498981Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:49.617812Z","title":"Morphological symmetries in robotics.The International Journal of Robotics Research, page 02783649241282422, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:49.617812Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:b26898b56f423261b7d8fb5dc6af871eadc93b05e9cca914bf35d5add2a70afb","observation_id":"75c52854-73c9-4f0c-bf93-bccf672af3b0","resolution":{"observed_at":"2026-08-02T18:34:49.617812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:49.760331Z","title":"Equivariant diffusion policy","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:49.760331Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:2adfb4724ca1aca3ebcec8a7f5f4ac5a07827346b2f9ef92a8626d56c7fa9352","observation_id":"7d3fa654-025d-44f9-874e-df3c447497de","resolution":{"observed_at":"2026-08-02T18:34:49.760331Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:49.930213Z","title":"Equiform: Noise-robust se (3)- equivariant policy learning from 3d point clouds.arXiv preprint arXiv:2601.17486, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:49.930213Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:dcf5b545f0e7dcaa0a91bc3d7c606d9ba21f880045d9e76ca7c2771bedbbe92e","observation_id":"4e00119e-0ccf-435f-950d-9f50687003c0","resolution":{"observed_at":"2026-08-02T18:34:49.930213Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.01918","last_updated":"2023-09-05T03:14:39Z","snapshot_observed_at":"2026-07-06T16:14:17.621050Z","submitted_at":"2023-09-05T03:14:39Z","title":"RoboAgent: Generalization and Efficiency in Robot Manipulation via Semantic Augmentations and Action Chunking","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.01918","snapshot_observed_at":"2026-08-02T18:34:50.115507Z","title":"Roboagent: Generalization and efficiency in robot manipulation via semantic augmentations and action chunking.arXiv preprint arXiv:2309.01918, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:50.115507Z"},"links":{"cited_paper":"/paper/2309.01918","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:8c07133252f5209a5acd8a4b30803e9e3db322e2410508cb00e90bfef40d9130","observation_id":"6cc23460-3ada-405f-8e11-c9770f3895ed","resolution":{"observed_at":"2026-08-02T18:34:50.115507Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.03403","last_updated":"2024-09-09T03:11:19Z","snapshot_observed_at":"2026-08-03T19:18:41.696136Z","submitted_at":"2024-09-05T10:39:15Z","title":"RoVi-Aug: Robot and Viewpoint Augmentation for Cross-Embodiment Robot Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.03403","snapshot_observed_at":"2026-08-02T18:34:50.250967Z","title":"Rovi-aug: Robot and viewpoint augmentation for cross-embodiment robot learning.arXiv preprint arXiv:2409.03403, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:50.250967Z"},"links":{"cited_paper":"/paper/2409.03403","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:f7c0dba000bc0ad314c3e4f7140fe571e7d7541860bad42a6a2aa339b7a53d88","observation_id":"b9f061f8-e9b0-48af-829e-0234fd68d633","resolution":{"observed_at":"2026-08-02T18:34:50.250967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.18088","last_updated":"2025-08-27T17:52:42Z","snapshot_observed_at":"2026-08-01T01:17:47.017808Z","submitted_at":"2025-06-22T16:26:53Z","title":"RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.18088","snapshot_observed_at":"2026-08-02T18:34:50.371299Z","title":"Robotwin 2.0: A scalable data generator and benchmark with strong domain randomization for robust bimanual robotic manipulation.arXiv preprint arXiv:2506.18088, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:50.371299Z"},"links":{"cited_paper":"/paper/2506.18088","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:7de6ca95fa59985c3ba1f96c6e6fab5adb3016ea9997525ce20b7544bc174c3e","observation_id":"4256cdfa-dffe-48fb-877f-9fa216c35b4a","resolution":{"observed_at":"2026-08-02T18:34:50.371299Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:50.520735Z","title":"Dual arm manipulation—a survey.Robotics and Autonomous systems, 60(10):1340–1353, 2012","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:50.520735Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:635b8de2a77327189e13fd288377a91886a7a9ca8e060059f8419f4217c2a6fd","observation_id":"9c628799-9b3c-4d01-8a9f-2b8e70f11f9b","resolution":{"observed_at":"2026-08-02T18:34:50.520735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.13677","last_updated":"2024-11-20T19:53:35Z","snapshot_observed_at":"2026-07-06T19:53:25.777341Z","submitted_at":"2024-11-20T19:53:35Z","title":"Bimanual Dexterity for Complex Tasks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.13677","snapshot_observed_at":"2026-08-02T18:34:50.697096Z","title":"Bimanual dexterity for complex tasks.arXiv preprint arXiv:2411.13677, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:50.697096Z"},"links":{"cited_paper":"/paper/2411.13677","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:270a890927151acfe653f75534a3cbf434268d7720a679e2a77b2eed955bbb88","observation_id":"f7abf403-2879-46a0-9d75-402ce8f5d9c4","resolution":{"observed_at":"2026-08-02T18:34:50.697096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:50.854971Z","title":"Deep imitation learning for bimanual robotic manipulation.Advances in neural information processing systems, 33:2327–2337, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:50.854971Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:81c61f8976a82ffe72769aaf7d89ba7152ab6b64d2dc44b2ac488cc8d6a17c6c","observation_id":"2d84d04f-138b-4b8a-815c-9a726ad44c11","resolution":{"observed_at":"2026-08-02T18:34:50.854971Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.12768","last_updated":"2026-05-06T08:19:11Z","snapshot_observed_at":"2026-08-08T14:05:53.379524Z","submitted_at":"2025-07-17T03:48:57Z","title":"AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.12768","snapshot_observed_at":"2026-08-02T18:34:50.972052Z","title":"Anypos: Automated task-agnostic actions for bimanual manipulation.arXiv preprint arXiv:2507.12768, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:50.972052Z"},"links":{"cited_paper":"/paper/2507.12768","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:c84d2b200ef9277d05c01303f9ba098df67bc28d5253b956d91fee47148529d3","observation_id":"7d32184f-0d9c-4009-be31-861ce0c53886","resolution":{"observed_at":"2026-08-02T18:34:50.972052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:51.091400Z","title":"A collaborative control method of dual-arm robots based on deep reinforcement learning.Applied Sciences, 11(4):1816, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:51.091400Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:2831d6728e7d09f6add559f9120633b5cf7f2cc67efc4be99edc6a17ff13bc50","observation_id":"3bcec4fd-ebbc-44f9-b11f-214092197c52","resolution":{"observed_at":"2026-08-02T18:34:51.091400Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:51.206658Z","title":"Equibot: SIM(3)-equivariant diffusion policy for generalizable and data efficient learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:51.206658Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:87218b694376a5d27dbe32a8b11ce29d0e9840180f42765de2ff7d5d9f97874b","observation_id":"285e5fec-6b1c-42b1-a730-8a7792e7a189","resolution":{"observed_at":"2026-08-02T18:34:51.206658Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.04576","last_updated":"2024-09-06T19:30:36Z","snapshot_observed_at":"2026-08-08T12:41:18.822749Z","submitted_at":"2024-09-06T19:30:36Z","title":"ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.04576","snapshot_observed_at":"2026-08-02T18:34:51.348050Z","title":"Actionflow: Equivariant, accurate, and efficient policies with spatially symmetric flow matching.arXiv preprint arXiv:2409.04576, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:51.348050Z"},"links":{"cited_paper":"/paper/2409.04576","citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:4ff8ce116f41c27d9ab9e16ac7f8b1285e74c0e59bdacb17bd60be3328c56281","observation_id":"c7c0e851-7e6f-4180-bc7e-1d6e07dc3c17","resolution":{"observed_at":"2026-08-02T18:34:51.348050Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:51.519474Z","title":"Highly accurate protein structure prediction with alphafold.nature, 596(7873):583–589, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:51.519474Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:c73d02d533db4395dd948a4da602bd4c3f3ce4639f2a3608af9dc010ee03718a","observation_id":"5335a93e-cde7-4cd0-8d8f-3127a5dac8ca","resolution":{"observed_at":"2026-08-02T18:34:51.519474Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:51.660896Z","title":"Residual rotation correction using tactile equivariance","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:51.660896Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:0b81ea814fbc302831d68aa77e5887333b49d025b31b82011d8c71812aa7f5a6","observation_id":"2a0ceca6-0ca4-43c2-a074-3a1017acdba4","resolution":{"observed_at":"2026-08-02T18:34:51.660896Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:51.789002Z","title":"E(2)-equivariant graph planning for navigation.IEEE Robotics and Automation Letters, 9(4):3371–3378, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:51.789002Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:74128a271bd7f33ce4140470f06e241835cbdc2842292dabb8932e42359ed79a","observation_id":"9a0b2615-4801-4754-b3df-482059aa9234","resolution":{"observed_at":"2026-08-02T18:34:51.789002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:51.918703Z","title":"3D Diffusion Policy: Generalizable visuomotor policy learning via simple 3d representations","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:51.918703Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:b423ad6331f52fab83226e88cca4f1544b094e974dc56059bb1c65f5245af9f1","observation_id":"75d9d248-96a5-4cc0-8d49-472d39118122","resolution":{"observed_at":"2026-08-02T18:34:51.918703Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T18:34:52.078107Z","title":"Lerobot: An open-source library for end-to-end robot learning.arXiv preprint arXiv:2602.22818, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-02T18:34:52.078107Z"},"links":{"citing_paper":"/paper/2603.08541"},"observation_digest":"sha256:709bdfae3a96b8865f42f320efe68027834f7bbc5576ab818ca4d7b44ed9242e","observation_id":"d937c4f5-97e8-4b3a-a9a0-34ada89b9284","resolution":{"observed_at":"2026-08-02T18:34:52.078107Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2603.08541","last_updated":"2026-07-21T01:28:23Z","latest_version":3,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-02T18:34:47.412259Z","submitted_at":"2026-03-09T16:09:18Z","title":"EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":31,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":31},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2603.08541."}