{"as_of":"2026-08-11T15:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a5dc1b7990dc6b5d19384ec6fe2445c9b351e763b4c7053a0c6eca9a62837bfe","coverage":[{"denominator":75,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":75,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:47:01.116935Z","state":"measured"},{"denominator":75,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":75,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2501.01136/citation-record","integrity":"/paper/2501.01136/integrity","json":"/paper/2501.01136/citation-record.json","paper":"/paper/2501.01136"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:00.758790Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.758790Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:e35611bf7cbbc3c8a0737b4b1924f824f529c521d600dfc044e1655d5bbac22b","observation_id":"a6fe053d-554d-4a05-8432-bd464644fa02","resolution":{"observed_at":"2026-08-10T22:47:00.758790Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:03.052931Z","title":"On learning symmetric locomotion","venue":null,"work_id":"7e396f6c-1c56-4cb0-8af4-b00463b71ff9","year":2019},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.766088Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:4ba73d4aa21825a03f8bb194dc7c6379a9daf51c578262bfea6bf8ad6e14bf9b","observation_id":"3f500042-28c4-42fa-a231-f67a78eb376c","resolution":{"observed_at":"2026-08-10T22:47:03.057566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.comcom.2022.09.029","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:01.170109Z","title":"Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case","venue":null,"work_id":"702da179-d92d-4fe4-8748-078b21d0c152","year":2022},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.770926Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:bf6805480486e3c5642477c2afe853c8e564583549a7bd54d899203253bffc94","observation_id":"d2af41f2-d3b6-4784-83fb-8b54e5bb1b10","resolution":{"observed_at":"2026-08-10T22:47:01.175250Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.07735","last_updated":"2021-11-20T06:25:22Z","snapshot_observed_at":"2026-08-11T11:56:07.587240Z","submitted_at":"2021-09-16T05:59:01Z","title":"Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2109.07735","doi":null,"metadata_source":"pith","pith_arxiv_id":"2109.07735","snapshot_observed_at":"2026-08-10T22:47:02.418487Z","title":"Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning","venue":"cs.RO","work_id":"b7d23ce1-e5da-4848-9993-178029b2ac06","year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.775981Z"},"links":{"cited_paper":"/paper/2109.07735","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:f60ef580c25fda57468bd2b37b9eaf28e6538171c16412c234147d17d9563fff","observation_id":"fb5fa430-529b-43a1-b20c-d48a8fea2a55","resolution":{"observed_at":"2026-08-10T22:47:02.423371Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:00.781304Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.781304Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:ca2733d58481af083ef70b9548f0ae5cd27c4d810f6ea288afa34982e5af76ca","observation_id":"c1cd5ee8-1831-4150-b3c8-69ff23845afc","resolution":{"observed_at":"2026-08-10T22:47:00.781304Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:03.027415Z","title":"Deep coordination graphs","venue":null,"work_id":"c069f357-11a9-4b42-b3cb-c08775a2bf00","year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.786223Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:7af3ecd4557aa7fb6b5a58776205448b2d898826542e9042e190ec3838a43f98","observation_id":"3e2e5a21-50fb-4f5b-857c-c593174c5863","resolution":{"observed_at":"2026-08-10T22:47:03.032158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11842","last_updated":"2024-05-25T20:31:15Z","snapshot_observed_at":"2026-08-07T08:30:56.087588Z","submitted_at":"2023-08-23T00:18:17Z","title":"${\\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11842","snapshot_observed_at":"2026-08-10T22:47:00.791312Z","title":"E(3)-equivariant actor-critic methods for cooperative multi-agent reinforcement learning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.791312Z"},"links":{"cited_paper":"/paper/2308.11842","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:2bd5cc049a3ba8148f2f42c640b496bb1785d5becd8e047496c26eafded0b0dd","observation_id":"a7e9fa89-3ea4-48d8-9857-f4495ad2a21f","resolution":{"observed_at":"2026-08-10T22:47:00.791312Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:03.012268Z","title":"Communication-efficient actor-critic methods for homogeneous markov games","venue":null,"work_id":"3ffd1388-f596-4e52-a9c3-60e7e40ea703","year":2022},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.796333Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:4b88ee1dd3631851f8f7f4beac7e7bbd17d1ba59a38333b7356dcb7a6de7475c","observation_id":"1deec965-7da3-4d7f-a213-2b31dffc5a0a","resolution":{"observed_at":"2026-08-10T22:47:03.016954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.996240Z","title":"Subequivariant graph reinforcement learning in 3 D environments","venue":null,"work_id":"58253e68-cd72-43f5-9c41-a5f130a404f1","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.800989Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:67f82fc64568102b3e8785a0cef53ac5ba3232a76f61091514b2c719c77b72e5","observation_id":"b950f9b9-6553-498b-9abd-73fd34a9a015","resolution":{"observed_at":"2026-08-10T22:47:03.001740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.980958Z","title":"Training deep convolutional neural networks to play go","venue":null,"work_id":"7e6b013d-b5da-4d73-b17a-48e248606461","year":2015},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.805516Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:77009f219a8691f25b0711e3293c17f5fd988977870a7c12caf385470b8604c8","observation_id":"90ddf8b9-d9f7-475c-b8ad-c08143bd9216","resolution":{"observed_at":"2026-08-10T22:47:02.985835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.05425","last_updated":"2021-11-19T12:00:16Z","snapshot_observed_at":"2026-08-08T11:53:57.880860Z","submitted_at":"2020-03-11T17:21:15Z","title":"Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.05425","snapshot_observed_at":"2026-08-10T22:47:00.809854Z","title":"Gauge equivariant mesh cnns: Anisotropic convolutions on geometric graphs, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.809854Z"},"links":{"cited_paper":"/paper/2003.05425","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:7110e133ba31f155697b7f091021dd1225a0a67244c856debb4d238bf2210c11","observation_id":"1bb88f0f-0b42-42a4-8c2b-7a83ec940350","resolution":{"observed_at":"2026-08-10T22:47:00.809854Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.966725Z","title":"Automatic symmetry discovery with lie algebra convolutional network","venue":null,"work_id":"d50daf96-a811-491a-a96f-a5d141cf7e41","year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.814831Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:2c0d087bc5f2f020a653b113cf13bc37479569fb6d22d789da56d24563ff9504","observation_id":"cda90d06-4d4f-42ab-a833-22a4b6873445","resolution":{"observed_at":"2026-08-10T22:47:02.971281Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.950036Z","title":null,"venue":null,"work_id":"1cfbf707-853b-4ad8-9ff6-57c708983c56","year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.818958Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:77343e82c42477e5223fa4ca2e971f59b0053141925893a6f1fbf11a51f3d1e8","observation_id":"6731e956-6916-4e51-8ce6-40370fe5b823","resolution":{"observed_at":"2026-08-10T22:47:02.955552Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:00.822873Z","title":"Generalizing convolutional neural networks for equivariance to lie groups on arbitrary continuous data","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.822873Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:7a44bc9b396d739b05957490e865cde271cdf61d0fd174d18ed2b01f1c75c42d","observation_id":"36804cf1-b72e-46b1-be94-517981475227","resolution":{"observed_at":"2026-08-10T22:47:00.822873Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.925653Z","title":"System identification of the crazyflie 2.0 nano quadrocopter","venue":null,"work_id":"adfe9ec7-be6a-4862-ad1c-70013bc3ac1c","year":2015},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.826947Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:614f0225257d6795627f6bddc60013826b09e47eb74c9361330ab4686a6c0523","observation_id":"c6c784bb-1fac-46ef-b898-5808c3a9a6cc","resolution":{"observed_at":"2026-08-10T22:47:02.930192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:00.830908Z","title":"Fuchs, Daniel E","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.830908Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:2822be95567e540d4559b3716ff9585934a4569b160a50adb9f371002fd879e8","observation_id":"681e92b8-67aa-4443-9398-0e5d830b99e2","resolution":{"observed_at":"2026-08-10T22:47:00.830908Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.900960Z","title":"Notes on group actions manifolds, lie groups and lie algebras","venue":null,"work_id":"81d3a02c-c819-43d9-b072-652c6e5c5d18","year":2005},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.834988Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:76e5c83ff0e0f425a36a51cb6052ba0be2e2d9c8cdca8be713f3e725c8d894b8","observation_id":"f0690e37-131b-49e6-86fa-1d2de5ddd7b1","resolution":{"observed_at":"2026-08-10T22:47:02.905360Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"1984.11034","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.364226Z","title":"Grizzle and S","venue":null,"work_id":"0afb6a11-e22e-4811-9e24-f2031508c054","year":1984},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.839427Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:d9db0851054346785b9220eda84a37d326ea486f41a01a1a3081b0285b921a8e","observation_id":"d8035478-6118-4916-b576-f8d28bc41713","resolution":{"observed_at":"2026-08-10T22:47:02.371594Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.ifacol.2023.02.023","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:01.151137Z","title":"Exploiting different symmetries for trajectory tracking control with application to quadrotors*","venue":null,"work_id":"8b59021d-b973-4246-86ea-a47532596155","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.844109Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:ebc08318cb471143336af3d4f40a31377dfd6d36fb7ea1ef7cc5be7a70e33a96","observation_id":"8180b495-e8a2-490b-ad3c-fd918dbcdeb5","resolution":{"observed_at":"2026-08-10T22:47:01.158514Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.886696Z","title":"Boosting multiagent reinforcement learning via permutation invariant and permutation equivariant networks","venue":null,"work_id":"c9801b57-1faa-4fd1-abd4-9c76783b8ba9","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.848455Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:e6d26ed4cd76d9d555317d9267f86c730a9ad6b8507488b997c50b1d68cdeaec","observation_id":"dcdf4986-7eb5-45b9-8919-10a4bda06c00","resolution":{"observed_at":"2026-08-10T22:47:02.891462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.872021Z","title":"Gauge equivariant transformer","venue":null,"work_id":"2d9432f3-d1a8-4cf9-8230-8242950edac5","year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.852602Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:c7b9d9145dbd618aa3c9933edee7d65095e589c000c034f83bd94a001be09f43","observation_id":"e0029e6c-ea18-4fb0-aa52-870436eb0674","resolution":{"observed_at":"2026-08-10T22:47:02.876056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.858666Z","title":"O ther-play","venue":null,"work_id":"cd46b682-10ff-40c9-9aad-b3f3eb8b8c73","year":null},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.857090Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:c4d14d18329e44030b0c8ed30e3330826da4c648eda9dbf319784a9e2341b5fb","observation_id":"f809b943-f323-445c-b6da-071e233d7097","resolution":{"observed_at":"2026-08-10T22:47:02.862899Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:00.861591Z","title":"Edge grasp network: A graph-based se(3)-invariant approach to grasp detection","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.861591Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:5b68be9ca9bbb57e7d96a3f3b84bf516f9e74358a859db6cd682637b0bfc0b2e","observation_id":"c25730f7-b3ac-40de-a4c8-ccb8f21b44a6","resolution":{"observed_at":"2026-08-10T22:47:00.861591Z","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":"2023.32496","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.196040Z","title":"Noack, Gang Hu, Shugao Liu, Yuchen Xu, and Huanhui Cao","venue":null,"work_id":"9fa1adab-0e16-4db8-b677-e4ce44266c61","year":2024},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.865731Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:308a6de0e1eae92d5233c6e1fef64c41ab5bf220d872c0d32ecc2be569116a6a","observation_id":"9d1126e6-1e1f-43c3-9171-6d647d314d7e","resolution":{"observed_at":"2026-08-10T22:47:02.203021Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.09537","last_updated":"2023-06-15T22:46:20Z","snapshot_observed_at":"2026-08-03T18:57:31.948257Z","submitted_at":"2023-06-15T22:46:20Z","title":"QuadSwarm: A Modular Multi-Quadrotor Simulator for Deep Reinforcement Learning with Direct Thrust Control","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.09537","snapshot_observed_at":"2026-08-10T22:47:00.870096Z","title":"Quadswarm: A modular multi-quadrotor simulator for deep reinforcement learning with direct thrust control","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.870096Z"},"links":{"cited_paper":"/paper/2306.09537","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:06558e98c2d06e660125f5fa7bbbf2791389a7753508cb5ef8ddf4eff4dbbd03","observation_id":"e4c89630-73e5-49c7-ba32-44947b34e997","resolution":{"observed_at":"2026-08-10T22:47:00.870096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.09202","last_updated":"2020-02-11T13:46:23Z","snapshot_observed_at":"2026-08-10T12:10:47.921121Z","submitted_at":"2018-10-22T12:17:40Z","title":"Graph Convolutional Reinforcement Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.09202","snapshot_observed_at":"2026-08-10T22:47:00.875907Z","title":"Graph convolutional reinforcement learning, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.875907Z"},"links":{"cited_paper":"/paper/1810.09202","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:bf7ee572712e9b50638d3a18eeb0b73b93bdd24165ae136aef35b6bac8130235","observation_id":"14f454fc-d024-4e1a-b4bd-08a4ee81b6ea","resolution":{"observed_at":"2026-08-10T22:47:00.875907Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.13649","last_updated":"2021-03-07T16:37:37Z","snapshot_observed_at":"2026-08-09T00:13:45.533552Z","submitted_at":"2020-04-28T16:48:16Z","title":"Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.13649","snapshot_observed_at":"2026-08-10T22:47:00.881006Z","title":"Image augmentation is all you need: Regularizing deep reinforcement learning from pixels, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.881006Z"},"links":{"cited_paper":"/paper/2004.13649","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:834e18497a8e44ef1d8d9a98dead5026ee0c9a2b9a74a8aab926f83cbc8b95b1","observation_id":"ba3c98f6-9c58-403c-98b5-1cc391ec477e","resolution":{"observed_at":"2026-08-10T22:47:00.881006Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.843889Z","title":"Reinforcement learning with augmented data","venue":null,"work_id":"5a3a47f7-6aa4-4208-9cc8-5c8b4f0edbd5","year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.886142Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:7b1abe3d6e89bc6f6ecccfc36868ec2762b84b0187700a04cf72a66cdc117726","observation_id":"aaa1f63d-7b67-4762-a838-8c6c93849ba6","resolution":{"observed_at":"2026-08-10T22:47:02.848588Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.828030Z","title":"HGAP : Boosting permutation invariant and permutation equivariant in multi-agent reinforcement learning via graph attention network","venue":null,"work_id":"8c317b87-66d8-4f17-a8b0-6fbae99f8be1","year":null},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.890755Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:bb859acc9ee0b326c79eb882b62adf86798c311d3bf14ff960277e314324017e","observation_id":"720fbd4f-632a-4681-ad80-d02ddb9bc20e","resolution":{"observed_at":"2026-08-10T22:47:02.833089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:00.895707Z","title":"Invariant transform experience replay: Data augmentation for deep reinforcement learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.895707Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:a70ea2db816efd8274ef2e5e99146c078dc756cb392a13407300688c6a17a1c9","observation_id":"381f3c56-86fd-409a-b024-23dffad83766","resolution":{"observed_at":"2026-08-10T22:47:00.895707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.00025","last_updated":"2019-10-31T18:04:42Z","snapshot_observed_at":"2026-07-06T08:33:53.451500Z","submitted_at":"2019-10-31T18:04:42Z","title":"PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning","version":1},"cited_work":{"arxiv_id":"1911.00025","doi":null,"metadata_source":"pith","pith_arxiv_id":"1911.00025","snapshot_observed_at":"2026-08-10T22:47:01.978408Z","title":"PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning","venue":"cs.LG","work_id":"f100c8ab-a26b-4bfc-991a-1fc76bf118f0","year":2019},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.900320Z"},"links":{"cited_paper":"/paper/1911.00025","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:4964a61b81c7c350b0a9af271a1e837aadd6d05b159a99143973382bea9506cb","observation_id":"8e5ed8a9-15dc-4dcf-8901-fabadd3bc2e6","resolution":{"observed_at":"2026-08-10T22:47:01.983691Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.08251","last_updated":"2022-03-30T09:25:40Z","snapshot_observed_at":"2026-07-06T12:08:53.711797Z","submitted_at":"2021-11-16T06:23:44Z","title":"Enabling equivariance for arbitrary Lie groups","version":2},"cited_work":{"arxiv_id":"2111.08251","doi":null,"metadata_source":"pith","pith_arxiv_id":"2111.08251","snapshot_observed_at":"2026-08-10T22:47:01.956830Z","title":"Enabling equivariance for arbitrary Lie groups","venue":"cs.CV","work_id":"4fe97042-6a7c-4553-bbdf-2ae54ab1292a","year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.905385Z"},"links":{"cited_paper":"/paper/2111.08251","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:646ef55193521d99fe0b784f98768bfa7fead6fe216058874cba3f1e9748411b","observation_id":"9d169899-ff26-4300-a04b-92aa4dff065f","resolution":{"observed_at":"2026-08-10T22:47:01.962191Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.00828","last_updated":"2020-08-30T00:08:41Z","snapshot_observed_at":"2026-07-06T09:09:18.723029Z","submitted_at":"2020-04-02T05:39:17Z","title":"Equivariant Filter Design for Kinematic Systems on Lie Groups","version":2},"cited_work":{"arxiv_id":"2004.00828","doi":null,"metadata_source":"pith","pith_arxiv_id":"2004.00828","snapshot_observed_at":"2026-08-10T22:47:01.935146Z","title":"Equivariant Filter Design for Kinematic Systems on Lie Groups","venue":"eess.SY","work_id":"622693e8-b787-40c5-9134-224a9d5ae718","year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.910123Z"},"links":{"cited_paper":"/paper/2004.00828","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:f3e04db0fb6a0b5b385b84b150d34b3909c024f40815ed2dd13c51b9ad4ae60d","observation_id":"e76b6e35-4077-4c43-9ec2-8786af2e6200","resolution":{"observed_at":"2026-08-10T22:47:01.940231Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2041.00212","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:01.910235Z","title":"Observers for kinematic systems with symmetry","venue":null,"work_id":"2a7c3015-53ba-4910-a104-99bdc459e523","year":2013},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.915290Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:e9aa7ec95be9f88a8220e0c9e9ffc298f80c757c143b01422758be6eeedc888f","observation_id":"78dd37ba-776f-4add-868b-a320a59e6338","resolution":{"observed_at":"2026-08-10T22:47:01.918565Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.08276","last_updated":"2020-08-30T00:41:41Z","snapshot_observed_at":"2026-08-09T19:53:02.267773Z","submitted_at":"2020-06-15T10:45:04Z","title":"Equivariant Systems Theory and Observer Design","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.08276","snapshot_observed_at":"2026-08-10T22:47:00.925185Z","title":"Mahony, T","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.925185Z"},"links":{"cited_paper":"/paper/2006.08276","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:1ac5f4f58c80605c06c96201d385d31c444a27e64f2f37ddc409ba60d577ae65","observation_id":"43cadcc2-80c3-4bba-8da2-bdc053a6213f","resolution":{"observed_at":"2026-08-10T22:47:00.925185Z","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":"2026-08-10T22:47:00.929960Z","title":"Exploiting symmetry for discrete-time reachability computations","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.929960Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:48d804fefb7bbafe614affff733b917d1103ea8744a9af01b22c472d638eb9d8","observation_id":"dbdb8a70-e613-45ed-bd03-78aa365072b2","resolution":{"observed_at":"2026-08-10T22:47:00.929960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1801.03237","last_updated":"2018-08-29T14:46:16Z","snapshot_observed_at":"2026-07-06T06:17:58.278569Z","submitted_at":"2018-01-10T04:45:17Z","title":"Symmetry reduction for dynamic programming","version":2},"cited_work":{"arxiv_id":"1801.03237","doi":null,"metadata_source":"pith","pith_arxiv_id":"1801.03237","snapshot_observed_at":"2026-08-10T22:47:01.716221Z","title":"Symmetry reduction for dynamic programming","venue":"cs.SY","work_id":"421541cc-2c1e-43fd-b0a8-a584aed0e595","year":2018},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.934699Z"},"links":{"cited_paper":"/paper/1801.03237","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:d927170f6a3b357470a63f8e48e3f7f6eda9dde6b3f0c759624d5412081ecc9f","observation_id":"389edd83-a4e4-4ed8-9940-d09ec7cd26a8","resolution":{"observed_at":"2026-08-10T22:47:01.720902Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.08356","last_updated":"2020-04-17T17:25:52Z","snapshot_observed_at":"2026-08-07T20:25:32.241139Z","submitted_at":"2020-04-17T17:25:52Z","title":"Goal-conditioned Batch Reinforcement Learning for Rotation Invariant Locomotion","version":1},"cited_work":{"arxiv_id":"2004.08356","doi":null,"metadata_source":"pith","pith_arxiv_id":"2004.08356","snapshot_observed_at":"2026-08-10T22:47:01.696114Z","title":"Goal-conditioned Batch Reinforcement Learning for Rotation Invariant Locomotion","venue":"cs.LG","work_id":"80dd890e-9a01-4629-abf0-6f16fd5a4902","year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.939661Z"},"links":{"cited_paper":"/paper/2004.08356","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:c9f427ba698f7e17c8a56921461739a3bc58034d8e843b109e90a63e6dc6aec7","observation_id":"cbdd8b6e-8e88-458b-baa5-8bc5c0ba0abc","resolution":{"observed_at":"2026-08-10T22:47:01.700841Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02581","last_updated":"2024-10-22T16:26:40Z","snapshot_observed_at":"2026-07-06T19:27:03.209340Z","submitted_at":"2024-10-03T15:25:37Z","title":"Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02581","snapshot_observed_at":"2026-08-10T22:47:00.944360Z","title":"Boosting sample efficiency and generalization in multi-agent reinforcement learning via equivariance, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.944360Z"},"links":{"cited_paper":"/paper/2410.02581","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:2ef9fd1df80c2fd2513d935971171ee65da353c46bc59536fb76a30fd64b8f84","observation_id":"a43bbc73-10b0-4d48-afaf-00791437763e","resolution":{"observed_at":"2026-08-10T22:47:00.944360Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.813665Z","title":"Lie group decompositions for equivariant neural networks","venue":null,"work_id":"b4eb6dae-ac75-4ef3-8e26-704d2872fb7d","year":2024},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.948827Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:e9a02b8a60a2a864152d93d692f9e43162ef1f619f220160275db67fb20b3b47","observation_id":"0813b301-ce0e-4da6-bbd5-36d0f5bbafc6","resolution":{"observed_at":"2026-08-10T22:47:02.818464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.03437","last_updated":"2020-07-01T02:38:48Z","snapshot_observed_at":"2026-07-06T09:36:06.200239Z","submitted_at":"2020-07-01T02:38:48Z","title":"Group Equivariant Deep Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.03437","snapshot_observed_at":"2026-08-10T22:47:00.953164Z","title":"Group equivariant deep reinforcement learning, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.953164Z"},"links":{"cited_paper":"/paper/2007.03437","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:457c0c415aa24fa76433ac603d21d4871273d6fdb726af565f475794f86dbfaa","observation_id":"11cd4f33-5dda-4dc8-b7f3-8389c49399cb","resolution":{"observed_at":"2026-08-10T22:47:00.953164Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.799189Z","title":"Attending to graph transformers, 2023","venue":null,"work_id":"1764b6bf-1b82-425d-8291-4dac97b22a4c","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.957478Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:9c2841ba92f66bebb9133d99c2d728873a3667c78c8d58c2914ae284217b9cf1","observation_id":"a71f0164-f2b0-44f1-b28d-102df220f238","resolution":{"observed_at":"2026-08-10T22:47:02.803640Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.785193Z","title":"Scalable multi-agent reinforcement learning through intelligent information aggregation","venue":null,"work_id":"11ab17aa-deb0-4ed8-bf6c-33ade0f70f56","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.961841Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:785a00ec4fbf6df42002f020d80a10b5d200e77de05ef7d0d3d623fd548466cb","observation_id":"e1598ffa-dc63-44f1-908a-6ff9eb014120","resolution":{"observed_at":"2026-08-10T22:47:02.789581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.771262Z","title":"Policy gradient with value function approximation for collective multiagent planning","venue":null,"work_id":"17cfbcaa-08b6-4343-8bf1-9dc6e28907a0","year":2017},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.966137Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:e81fed8082563f25db87dcb79e3b71c6a3eb69e4bcfecca7d9bf2cc78b1dbef6","observation_id":"ebc44355-13a9-4b4d-81e1-bd67ad285d39","resolution":{"observed_at":"2026-08-10T22:47:02.775985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.756388Z","title":"Equivariant reinforcement learning under partial observability","venue":null,"work_id":"e40e7c64-a389-4956-a9f6-42aca2b00b05","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.970355Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:891fc8d6984f5e3fb099661ebe84efac10c7e4c55f008beb791b840e6ac82899","observation_id":"a58fadcb-f0fe-4017-92a1-27616ba41a9a","resolution":{"observed_at":"2026-08-10T22:47:02.761213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.10433","last_updated":"2023-07-07T13:32:30Z","snapshot_observed_at":"2026-08-10T02:13:44.449650Z","submitted_at":"2023-02-21T04:10:16Z","title":"On discrete symmetries of robotics systems: A group-theoretic and data-driven analysis","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.10433","snapshot_observed_at":"2026-08-10T22:47:00.974732Z","title":"On discrete symmetries of robotics systems: A group-theoretic and data-driven analysis","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.974732Z"},"links":{"cited_paper":"/paper/2302.10433","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:9fa4acc28531d210d8b39ba1cd04d8c4f0ed1674b072e6676f2e8cd988becef1","observation_id":"1e896dc4-acf1-48b7-a141-63c9131bd88d","resolution":{"observed_at":"2026-08-10T22:47:00.974732Z","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":"2026-08-10T22:47:00.978871Z","title":"Schoellig","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.978871Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:3f5e092d418519cf3023cf9e88a829ed3afb2fe577590f5b839715faddcbb096","observation_id":"2dc82a33-5bb7-473a-a653-da8a6dffc119","resolution":{"observed_at":"2026-08-10T22:47:00.978871Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.741421Z","title":"Improving equivariant model training via constraint relaxation","venue":null,"work_id":"3277cf3e-711c-4660-b1c0-95fad436c089","year":2024},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.984089Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:9ee4c72acb92c5e949001191b54ab8b47076c6efda579c8a11e80415e210277d","observation_id":"4e1ca54e-6275-45af-a990-aa17e93018cd","resolution":{"observed_at":"2026-08-10T22:47:02.746173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.726761Z","title":"Sukhatme, and Vladlen Koltun","venue":null,"work_id":"7281f7ac-5f47-4f45-bc81-0b462ea1fd71","year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.989876Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:fe4df3862da2b2449b65d20f02fb07d890341aeb325c307698ea016a1f0cbfad","observation_id":"a57f7547-9dfa-4bc4-babc-c17a996258dc","resolution":{"observed_at":"2026-08-10T22:47:02.731187Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.08839","last_updated":"2020-08-27T13:45:29Z","snapshot_observed_at":"2026-07-06T09:05:55.638031Z","submitted_at":"2020-03-19T16:51:51Z","title":"Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2003.08839","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.08839","snapshot_observed_at":"2026-08-10T22:47:01.549939Z","title":"Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning","venue":"cs.LG","work_id":"1816a641-cd52-4583-bf2f-065d44946fa8","year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.994594Z"},"links":{"cited_paper":"/paper/2003.08839","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:6a998125dedb0fc25de4f82fc4ffae8a47ab3afcfc64af594044840ebc3dfe06","observation_id":"e2797219-443a-4d32-a01b-4b91987f93ea","resolution":{"observed_at":"2026-08-10T22:47:01.555451Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.712939Z","title":null,"venue":null,"work_id":"90587742-c3b3-4aa5-a7fd-a254d47b232a","year":2001},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:00.999459Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:acfeaa6c0f750cdcb250646e02d218b9aff1606f9d2dc23a344dd305de7c7340","observation_id":"02d4141c-1552-4b07-841c-4d478be03109","resolution":{"observed_at":"2026-08-10T22:47:02.717530Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.699175Z","title":"E(n) equivariant graph neural networks","venue":null,"work_id":"cd7b3d49-8a21-4b73-87b6-4fd2e525c48d","year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.004008Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:1e5b1ccbe76036dceb6812188a4dfb7a9c12385da68439ea976de7b983211f95","observation_id":"fab8329b-4ddd-4de4-a232-c049a09e8c5e","resolution":{"observed_at":"2026-08-10T22:47:02.703772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.684517Z","title":"Equivariant message passing for the prediction of tensorial properties and molecular spectra","venue":null,"work_id":"5c35c7db-905f-480d-881e-165d77492b5d","year":2021},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.008778Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:d6aa4142175711ab72301e76f489d385ca086ee19304e2fd7529991c2d9fabae","observation_id":"2dd23877-dadb-465a-87f4-6cfacf2bedc5","resolution":{"observed_at":"2026-08-10T22:47:02.689487Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.12747","last_updated":"2020-11-25T14:04:33Z","snapshot_observed_at":"2026-07-06T10:17:45.950338Z","submitted_at":"2020-11-25T14:04:33Z","title":"Symmetry-Aware Actor-Critic for 3D Molecular Design","version":1},"cited_work":{"arxiv_id":"2011.12747","doi":null,"metadata_source":"pith","pith_arxiv_id":"2011.12747","snapshot_observed_at":"2026-08-10T22:47:01.494179Z","title":"Symmetry-Aware Actor-Critic for 3D Molecular Design","venue":"stat.ML","work_id":"baaad3bc-1c8f-414f-b991-3e98a92d1862","year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.013389Z"},"links":{"cited_paper":"/paper/2011.12747","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:d2626eea819d5a5b10445b753f6c05e522edfb74ba6fbada871ea31f62105176","observation_id":"294efe6e-2fee-42b8-b025-346d7c817b77","resolution":{"observed_at":"2026-08-10T22:47:01.513209Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:01.018150Z","title":"So(2)-equivariant downwash models for close proximity flight","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.018150Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:26887e860c089e146512ca01d20dc0923937455efd7da51d421bf66a0fd6cf5d","observation_id":"4751ab17-3333-4718-a536-e057d53820a7","resolution":{"observed_at":"2026-08-10T22:47:01.018150Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.19024","last_updated":"2024-08-16T18:00:05Z","snapshot_observed_at":"2026-08-11T07:58:44.644526Z","submitted_at":"2024-03-27T21:31:46Z","title":"Exploiting Symmetry in Dynamics for Model-Based Reinforcement Learning with Asymmetric Rewards","version":3},"cited_work":{"arxiv_id":"2403.19024","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.19024","snapshot_observed_at":"2026-08-10T22:47:01.400233Z","title":"Exploiting Symmetry in Dynamics for Model-Based Reinforcement Learning with Asymmetric Rewards","venue":"cs.LG","work_id":"dbe57cf7-9472-4f2c-aefc-ac493a0d0a1c","year":2024},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.022806Z"},"links":{"cited_paper":"/paper/2403.19024","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:975460bfe3df2d0b7bafe6404e37da119083d321af8ab2fa8b71436d0900c896","observation_id":"60d34a64-2e1e-4381-bdbb-98744ed66cad","resolution":{"observed_at":"2026-08-10T22:47:01.405735Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.17320","last_updated":"2025-03-11T12:43:09Z","snapshot_observed_at":"2026-07-06T17:50:39.208397Z","submitted_at":"2024-03-26T02:02:35Z","title":"Leveraging Symmetry in RL-based Legged Locomotion Control","version":3},"cited_work":{"arxiv_id":"2403.17320","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.17320","snapshot_observed_at":"2026-08-10T22:47:01.377927Z","title":"Leveraging Symmetry in RL-based Legged Locomotion Control","venue":"cs.RO","work_id":"300b91c7-fd5b-4aed-8f34-e80b3d8ebfde","year":2024},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.028072Z"},"links":{"cited_paper":"/paper/2403.17320","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:a91227f52b591ed0fe35be6be41fd5135da8154bc5313dc54dbe6730a134c507","observation_id":"1a6bd442-0692-44fd-b84e-9fd46dbab04f","resolution":{"observed_at":"2026-08-10T22:47:01.382893Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1802.08219","last_updated":"2018-05-18T20:09:34Z","snapshot_observed_at":"2026-07-06T06:24:51.822169Z","submitted_at":"2018-02-22T18:17:31Z","title":"Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.08219","snapshot_observed_at":"2026-08-10T22:47:01.033185Z","title":"Tensor field networks: Rotation-and translation-equivariant neural networks for 3d point clouds","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.033185Z"},"links":{"cited_paper":"/paper/1802.08219","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:7cbc0375aaf19cef5bedc975c3016d0a7efae18f6835e15e4535de3a7caf75e1","observation_id":"840d98a1-a8be-4155-b8cd-96c7b3d75cd3","resolution":{"observed_at":"2026-08-10T22:47:01.033185Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.669509Z","title":"Graph neural networks for multi-robot active information acquisition","venue":null,"work_id":"318d4184-a79f-405c-a42e-8676541b4105","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.038148Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:402b48ffe268073956d6ada969482575dfa860cc01b0f9e98d0ddfe93102d36a","observation_id":"7a695fa7-575d-412f-9bf0-413b282fe47a","resolution":{"observed_at":"2026-08-10T22:47:02.674401Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.653539Z","title":"Coordinated deep reinforcement learners for traffic light control","venue":null,"work_id":"ef9abdf8-a0c8-4a0d-8e16-39de54974300","year":2016},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.042533Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:ae5e17c9412d36c51da88e1eb033b6cf495d19e1125b71ccdc5b88df95a507ee","observation_id":"72839b2a-0ada-4228-8d02-44a3dc35c6d6","resolution":{"observed_at":"2026-08-10T22:47:02.658604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.11963","last_updated":"2020-02-27T08:29:10Z","snapshot_observed_at":"2026-08-08T06:19:38.136041Z","submitted_at":"2020-02-27T08:29:10Z","title":"Plannable Approximations to MDP Homomorphisms: Equivariance under Actions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.11963","snapshot_observed_at":"2026-08-10T22:47:01.046793Z","title":"Oliehoek, and Max Welling","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.046793Z"},"links":{"cited_paper":"/paper/2002.11963","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:65a772cb7fd65034c86e268bddfb709985d7d165979a9f9b4db3e1ec1f7dca77","observation_id":"c8385171-4d59-4bcb-887c-ae69557a2cb0","resolution":{"observed_at":"2026-08-10T22:47:01.046793Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.639081Z","title":"Mdp homomorphic networks: Group symmetries in reinforcement learning","venue":null,"work_id":"2e6d32c9-d419-429c-82b9-fa618e575356","year":null},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.051339Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:cd826a3a140487dfd77860755bcd887facf45262fbaaef268b3f7802a1cf77ad","observation_id":"9b132096-df71-4149-9a9e-4e01a0a709ad","resolution":{"observed_at":"2026-08-10T22:47:02.643668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.04495","last_updated":"2022-04-29T11:56:14Z","snapshot_observed_at":"2026-07-06T11:56:03.791657Z","submitted_at":"2021-10-09T07:46:25Z","title":"Multi-Agent MDP Homomorphic Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.04495","snapshot_observed_at":"2026-08-10T22:47:01.055688Z","title":"Oliehoek, and Max Welling","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.055688Z"},"links":{"cited_paper":"/paper/2110.04495","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:d216a28497a7fee92f0f8c11f317372488aee930b4cf6e116fba1a6456fd2d08","observation_id":"a785f71c-2e34-4d5e-90e5-ca2b1d84c0dc","resolution":{"observed_at":"2026-08-10T22:47:01.055688Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02798","last_updated":"2020-11-05T02:00:46Z","snapshot_observed_at":"2026-08-11T02:45:11.977900Z","submitted_at":"2020-10-06T15:12:01Z","title":"Policy learning in SE(3) action spaces","version":2},"cited_work":{"arxiv_id":"2010.02798","doi":null,"metadata_source":"pith","pith_arxiv_id":"2010.02798","snapshot_observed_at":"2026-08-10T22:47:01.308978Z","title":"Policy learning in SE(3) action spaces","venue":"cs.RO","work_id":"813f9f0c-2fae-404a-8fd6-d8e195a001d2","year":2020},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.060217Z"},"links":{"cited_paper":"/paper/2010.02798","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:7b4173fa5494b07449c7758d423fea89c6fbde9795cd11ccb2c5d3605a8a97cd","observation_id":"11adef32-6afb-43bf-ac60-7a0f9eb2254e","resolution":{"observed_at":"2026-08-10T22:47:01.314436Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.624520Z","title":"Equivariant q learning in spatial action spaces","venue":null,"work_id":"f587dfe9-acf7-4d81-88c9-cfc631b9af68","year":2022},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.065663Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:510fde06d008c9289f56b88640285a4196212c24b9b9ba56716c8d22bff9cceb","observation_id":"7cb23789-487a-4d31-ac6e-4985164f37f8","resolution":{"observed_at":"2026-08-10T22:47:02.629243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.609290Z","title":"Wong, Robin Walters, and Robert Platt","venue":null,"work_id":"789d6e35-1563-4bd3-afc7-3730389fa0a1","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.070060Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:b10a1e9f9eb0e7ce8e87b4a49df188d534bbece2cee27afbfd15ce5e8386df78","observation_id":"959171c6-b748-480c-bedd-625569602936","resolution":{"observed_at":"2026-08-10T22:47:02.614211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.594754Z","title":"Koopman q-learning: Offline reinforcement learning via symmetries of dynamics","venue":null,"work_id":"01e03733-76bd-49a7-b154-0e828afd8322","year":2022},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.074343Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:c7901dfc32721d6b9974ddbdd0cdf43f7a49bef3f8c93ef8abbf6dd86c4d6503","observation_id":"d4893557-fd1d-4bc9-a81d-c924285b2cb8","resolution":{"observed_at":"2026-08-10T22:47:02.599326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.579947Z","title":"Mean field multi-agent reinforcement learning","venue":null,"work_id":"d0966402-7d34-47bb-81ec-0c3753e2a74f","year":2018},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.078623Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:ecdd4c9c61b0c0a9dc74180a1e1d4c86cfd143026697cf2e8be593ec0f0f7826","observation_id":"7185de4f-aa8d-45c7-adb3-dee2bd7e76c8","resolution":{"observed_at":"2026-08-10T22:47:02.584952Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.564796Z","title":"Equivariant reinforcement learning for quadrotor uav","venue":null,"work_id":"fbb70097-516a-451b-8c54-e2155eed7e7c","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.083053Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:fca4152f4847684997c4276110e188c67de9bb8b902ca29997a2cf5d5a5e05b9","observation_id":"2a50f385-d7be-4ece-a899-a496f9853c94","resolution":{"observed_at":"2026-08-10T22:47:02.569089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:01.088037Z","title":"Equivariant reinforcement learning for quadrotor uav","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.088037Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:6ecfdb8c29e0678b5f787acf1269fdf79201ee3039194050adf7d97b0fafd06e","observation_id":"bf0f64b6-a921-48bd-86c4-4e3ffdff583c","resolution":{"observed_at":"2026-08-10T22:47:01.088037Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.550015Z","title":"Equivariant reinforcement learning for quadrotor uav","venue":null,"work_id":"5021a63c-3526-49e4-93ab-c2c4a8aefc08","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.092794Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:c62ec0ee613d08c1cc073f55e6c1c22c6a1186a35fc78399a341eed13c0f77d3","observation_id":"013b7b8c-8d46-4d88-9f92-d770cc42dafe","resolution":{"observed_at":"2026-08-10T22:47:02.555390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.534035Z","title":"The surprising effectiveness of PPO in cooperative multi-agent games","venue":null,"work_id":"090ac683-ac2b-4e94-ad9e-e8b8d2c0ad4a","year":2022},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.097339Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:3d23bf61029b88eb690c9ee949fbf7928341ccd27484ce9fe58f4f554969dc97","observation_id":"9062f354-fb0a-47ef-8e1f-fb70263d627c","resolution":{"observed_at":"2026-08-10T22:47:02.539865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:47:02.518873Z","title":null,"venue":null,"work_id":"e2a39612-e384-458c-9989-fb0c5532db31","year":2023},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.102348Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:53defeaf15c1563daa5e327f2e855d866529f31b0a6dac106f1ef5b66dbe3c60","observation_id":"eb59130a-8b75-4c2d-91cd-06a1f6c1857b","resolution":{"observed_at":"2026-08-10T22:47:02.523553Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.09468","last_updated":"2022-02-18T23:04:57Z","snapshot_observed_at":"2026-07-06T12:39:25.252398Z","submitted_at":"2022-02-18T23:04:57Z","title":"Sample Efficient Grasp Learning Using Equivariant Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.09468","snapshot_observed_at":"2026-08-10T22:47:01.112363Z","title":"Sample efficient grasp learning using equivariant models, 2022 b","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.112363Z"},"links":{"cited_paper":"/paper/2202.09468","citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:7e4a7f67319d38c4cdf48d3a18f7b4df28c96d9c650a887fb825fa1c5fef5856","observation_id":"239cd46a-5fca-4ca0-abc9-1ed83c4f8f75","resolution":{"observed_at":"2026-08-10T22:47:01.112363Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:47:02.504295Z","title":"Zinkevich and Tucker R","venue":null,"work_id":"603e58ad-5d1f-4fda-88cd-76543aba3090","year":2001},"citing_paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning","version":2},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-10T22:47:01.116935Z"},"links":{"citing_paper":"/paper/2501.01136"},"observation_digest":"sha256:0ca4a9f2e26a8f4dfb37a35f2cd6722e9361d2c0a015992897338730a71dae50","observation_id":"70b6f87e-fdea-4826-9407-dd8e6111636c","resolution":{"observed_at":"2026-08-10T22:47:02.508730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.01136","last_updated":"2025-04-25T09:39:19Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-11T13:08:32.634962Z","submitted_at":"2025-01-02T08:41:31Z","title":"Symmetries-enhanced Multi-Agent Reinforcement Learning"},"reference_resolution":{"displayed":75,"state_counts":{"malformed_identifier":0,"metadata_mismatch":3,"parse_uncertain":0,"unresolved":26,"verified_exact":13,"verified_fuzzy":33},"total_outbound_references":75},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 0 inbound Pith citation observations for arXiv:2501.01136."}