{"as_of":"2026-08-13T03:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6109b505499234c0738d7ab98926ff651ebc73466c39bcfaf7ce58455ccbd850","coverage":[{"denominator":294,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T00:48:44.749058Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2608.07870/citation-record","integrity":"/paper/2608.07870/integrity","json":"/paper/2608.07870/citation-record.json","paper":"/paper/2608.07870"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T00:48:43.369255Z","title":"Reinforcement Learning Conference , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.369255Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:0bcd2b181d4a2af55ba69a1de7626158bd6943cd4b5b83bfda739b27375e7fcf","observation_id":"e57fe484-753a-4801-94ee-3ff9606f0877","resolution":{"observed_at":"2026-08-12T00:48:43.369255Z","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":"2026-08-12T00:48:43.374775Z","title":"Forty-first International Conference on Machine Learning , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.374775Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:1bbaaceff8374315839eba04ba9940911b300ab6e669a3cd2efc6dff9093a88c","observation_id":"0a1769ee-b33b-472d-bce1-c6040c873083","resolution":{"observed_at":"2026-08-12T00:48:43.374775Z","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":"2026-08-12T00:48:43.379946Z","title":"1995 , publisher=","venue":null,"work_id":null,"year":1995},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.379946Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:22911d1731c4271a770fe8830f9d226a785ab238e2302d35b5ae56350015e534","observation_id":"f566992d-9f2a-4076-a641-251a09bb0f24","resolution":{"observed_at":"2026-08-12T00:48:43.379946Z","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":"2026-08-12T00:48:43.385181Z","title":"Nature , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.385181Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:1a914373ee3628de2fbfe2b99a0f6af9fc7c7dc18bf53829ae6bf5cebd7b2587","observation_id":"6fe540d3-b1d3-44f6-8415-3847da813fe3","resolution":{"observed_at":"2026-08-12T00:48:43.385181Z","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":"2026-08-12T00:48:43.390233Z","title":"Computing in science & engineering , volume=","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.390233Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:a6544796e99bbdded88d2dfe356c14144bb559c81e40e373868b233e16ea068c","observation_id":"05dafc2f-1811-4649-9c9c-2d5770715ac2","resolution":{"observed_at":"2026-08-12T00:48:43.390233Z","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":"2026-08-12T00:48:43.396065Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.396065Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:b6920a7e26812e51f954957ab1c75e5176b63a3113609ffeacadce129db87d64","observation_id":"c76a30be-da7f-48e6-a214-3974facf7d31","resolution":{"observed_at":"2026-08-12T00:48:43.396065Z","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":"2026-08-12T00:48:43.400994Z","title":", journal=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.400994Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:48c4f48f268dd2a62cf80b9662b7dc8cb6e7e7dac38126ebe816fb9f80ede29d","observation_id":"6b68cf87-fb4b-4cf4-a1d3-0cb5b3867532","resolution":{"observed_at":"2026-08-12T00:48:43.400994Z","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":"2026-08-12T00:48:43.406424Z","title":"IOS Press , year = 2016, pages =","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.406424Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e4bc89c4d67bed3140b11cef0828f0d1d5c8f88c594caead6a9d51de6d352a6d","observation_id":"2ce24967-37c6-4a39-afae-8b685bd9e7fe","resolution":{"observed_at":"2026-08-12T00:48:43.406424Z","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":"2026-08-12T00:48:43.411348Z","title":"Python for Data Analysis: Data Wrangling with Pandas,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.411348Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:90771cc81ffd5f9d098da315450d58e811e440340769877a69903b6c13dcde4c","observation_id":"537cbd8a-edd5-4e73-b8dc-77b7344564ac","resolution":{"observed_at":"2026-08-12T00:48:43.411348Z","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":"2026-08-12T00:48:43.416067Z","title":"Forty-second International Conference on Machine Learning , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.416067Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:9ec2eecb670047720b130a51d3fa9d3c6779272fdc7bcc99ef265819af5d3bdc","observation_id":"88ca4713-8e5c-451e-bdb2-b82c241a8bd2","resolution":{"observed_at":"2026-08-12T00:48:43.416067Z","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":"2026-08-12T00:48:43.421960Z","title":"The Thirteenth International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.421960Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:891e782487b961d4b971e8ca00da8cff221f426d1a9f0db473133bb4bc8637e5","observation_id":"ba8fa836-86f2-4c74-8f27-38838dfbb0eb","resolution":{"observed_at":"2026-08-12T00:48:43.421960Z","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":"2026-08-12T00:48:43.427133Z","title":"Mixture of Experts in a Mixture of","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.427133Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:22daf48423328dc626b0d7fe1e760140034f752c323749aa7f5fc2e241ccd17f","observation_id":"5307efec-b126-4005-ba32-fc25dc5c5554","resolution":{"observed_at":"2026-08-12T00:48:43.427133Z","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":"2026-08-12T00:48:43.432382Z","title":"Forty-third International Conference on Machine Learning , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.432382Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:70530d43f5ae99919b6e5877cb347aa1775c783b8f5141e0e7d21839c4038829","observation_id":"bad3e48c-f9ca-41f6-b3e6-e3fecc873e94","resolution":{"observed_at":"2026-08-12T00:48:43.432382Z","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":"2026-08-12T00:48:43.436841Z","title":"The Thirty-ninth Annual Conference on Neural Information Processing Systems , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.436841Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:109335901e868a2cd5fd2307378cf22646b688368a204c095002e7d0d039532a","observation_id":"0a8446cb-4ed2-45e6-bb9b-e499db6719b4","resolution":{"observed_at":"2026-08-12T00:48:43.436841Z","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":"2026-08-12T00:48:43.481309Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.481309Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:999ae00b8a46e4406421f224f80bd764c6e71d15da4566ff5619314394b9f503","observation_id":"5150b72d-6b65-4fd6-98e3-f72911551c87","resolution":{"observed_at":"2026-08-12T00:48:43.481309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.17518","last_updated":"2025-06-20T23:47:04Z","snapshot_observed_at":"2026-08-10T10:35:48.301748Z","submitted_at":"2025-06-20T23:47:04Z","title":"A Survey of State Representation Learning for Deep Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.17518","snapshot_observed_at":"2026-08-12T00:48:43.522343Z","title":"arXiv preprint arXiv:2506.17518 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.522343Z"},"links":{"cited_paper":"/paper/2506.17518","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:04781fe35b43d1355a61e1015f6b85dd48462fe541a9b9961c48bb4453e4b909","observation_id":"88367737-f250-4c95-9ced-7c15ca0d2c37","resolution":{"observed_at":"2026-08-12T00:48:43.522343Z","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":"2026-08-12T00:48:43.548531Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.548531Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:f0215b89a4d36e7bb3f9fab8e4ce3a3eca2186942e20af736e23bc3de2a68f3d","observation_id":"e44d22c7-a2b9-4b68-bb0d-17eb3c6e61f3","resolution":{"observed_at":"2026-08-12T00:48:43.548531Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.04561","last_updated":"2024-10-21T14:11:42Z","snapshot_observed_at":"2026-08-10T09:08:51.877870Z","submitted_at":"2022-10-10T11:01:57Z","title":"A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.04561","snapshot_observed_at":"2026-08-12T00:48:43.611443Z","title":"arXiv preprint arXiv:2210.04561 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.611443Z"},"links":{"cited_paper":"/paper/2210.04561","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:ebf7c6b8850d8ce47c76cbe54d25163171cb01ff7edb5ec965753ffb9f050040","observation_id":"11ba5a13-27d9-4a8a-9098-e9b6fbb2c8b6","resolution":{"observed_at":"2026-08-12T00:48:43.611443Z","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":"2026-08-12T00:48:43.661040Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.661040Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:dcf3d888ec9af3ae4afabc08f616ff17e06b643198a01883f7a9d8195ca9bc1d","observation_id":"f100fbb2-efc4-4b6c-a740-d696d3c323c9","resolution":{"observed_at":"2026-08-12T00:48:43.661040Z","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":"2026-08-12T00:48:43.682920Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.682920Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:4ad891d27a23f821b0b74b237c9aaaedbda3052e17e442801665bee865cc9107","observation_id":"822fcae4-438d-4c94-ba91-80311edbadab","resolution":{"observed_at":"2026-08-12T00:48:43.682920Z","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":"2026-08-12T00:48:43.688473Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.688473Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:0a1568927cc35a34f7979a576db2a2da7de96e1b7f78a85d17f475231cbde7db","observation_id":"add1ad3c-3f92-43de-9a1f-3a94bc49de80","resolution":{"observed_at":"2026-08-12T00:48:43.688473Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.16142","last_updated":"2025-01-27T15:36:37Z","snapshot_observed_at":"2026-08-12T13:31:12.701489Z","submitted_at":"2025-01-27T15:36:37Z","title":"Towards General-Purpose Model-Free Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.16142","snapshot_observed_at":"2026-08-12T00:48:43.695144Z","title":"arXiv preprint arXiv:2501.16142 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.695144Z"},"links":{"cited_paper":"/paper/2501.16142","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:9c952801166e3e39564e1943e1f7d9171c2d5b59dfe56e8534bbebaf17b00fac","observation_id":"01506ef6-e2e9-4d3c-bb21-c04ad0be6a5d","resolution":{"observed_at":"2026-08-12T00:48:43.695144Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2007.05929","last_updated":"2021-05-20T09:15:57Z","snapshot_observed_at":"2026-08-10T04:32:16.941126Z","submitted_at":"2020-07-12T07:38:15Z","title":"Data-Efficient Reinforcement Learning with Self-Predictive Representations","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.05929","snapshot_observed_at":"2026-08-12T00:48:43.700829Z","title":"arXiv preprint arXiv:2007.05929 , year=","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.700829Z"},"links":{"cited_paper":"/paper/2007.05929","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:489788fab113992115d10a4ee31fb85974e3dce891ac7176ca93be5e16f3b7c4","observation_id":"e823bf09-6b87-401b-a16f-93f22e1f97e0","resolution":{"observed_at":"2026-08-12T00:48:43.700829Z","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":"2026-08-12T00:48:43.706395Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.706395Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:706810b5f839c9f261316e7c1225177c828c6c01578451efd751e2cf26340941","observation_id":"659b241e-5954-401b-b281-00999289429d","resolution":{"observed_at":"2026-08-12T00:48:43.706395Z","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":"2026-08-12T00:48:43.711324Z","title":"2016 IEEE/RSJ international conference on intelligent robots and systems (IROS) , pages=","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.711324Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e20d62bd947ef78f6d9fd8ce5f8fd828651b6636e8c3e3c57bb842f8f61b5995","observation_id":"588fb875-6a1a-40b6-b008-c2be8e4ddcc3","resolution":{"observed_at":"2026-08-12T00:48:43.711324Z","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":"2026-08-12T00:48:43.716805Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.716805Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:c49d15841d147fcb74e6c456fb2e6f7ac430a682b4d3b5a8ee558bfb90730607","observation_id":"f08bcd87-10c5-41df-8e2a-a31162099b81","resolution":{"observed_at":"2026-08-12T00:48:43.716805Z","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":"2026-08-12T00:48:43.722823Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.722823Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:5f7399d215a222f8724ca3ae0e0cd3ed74356aac71338c50213dd0ce4b694438","observation_id":"f6d33a24-ca73-4944-a4ef-b070bf066548","resolution":{"observed_at":"2026-08-12T00:48:43.722823Z","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":"2026-08-12T00:48:43.728230Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.728230Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:026fe0c64b6f97612e841576c71e0742fbfe8c6b5c6f20211714bd2730b2b635","observation_id":"aacf2e18-d1af-4451-8395-b794e5fe600f","resolution":{"observed_at":"2026-08-12T00:48:43.728230Z","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":"2026-08-12T00:48:43.735816Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.735816Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:add79c4ede6fd5143cbfb53cd663ffc7275dd25de283fd8d8bf95474a839854e","observation_id":"fcf7acd0-e71d-4f35-9770-c83b315843e7","resolution":{"observed_at":"2026-08-12T00:48:43.735816Z","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":"2026-08-12T00:48:43.746142Z","title":"International Conference on Machine Learning , pages=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.746142Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:dc3dceb443c2a8404d8343830965452d0fa3d22af5dc3b7e896e6e2b65971b82","observation_id":"fa20d1a6-60b3-4c7d-bb46-db45444c0afd","resolution":{"observed_at":"2026-08-12T00:48:43.746142Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.04935","last_updated":"2021-10-11T00:16:43Z","snapshot_observed_at":"2026-08-12T13:31:04.414064Z","submitted_at":"2021-10-11T00:16:43Z","title":"Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.04935","snapshot_observed_at":"2026-08-12T00:48:43.752787Z","title":"arXiv preprint arXiv:2110.04935 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.752787Z"},"links":{"cited_paper":"/paper/2110.04935","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:145bcab13a21012c441c96447ebb521c29fd61b86efc300482dad5937b579897","observation_id":"740f8dde-456b-467f-97e5-c227892f50db","resolution":{"observed_at":"2026-08-12T00:48:43.752787Z","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":"2026-08-12T00:48:43.758999Z","title":"International Conference on Machine Learning , pages=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.758999Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:4e577f616325d322bdff340ff8808c39a822cbd834d36af7e010899ebbf827cd","observation_id":"191fbf1a-a53a-4466-8534-fd926951d195","resolution":{"observed_at":"2026-08-12T00:48:43.758999Z","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":"2026-08-12T00:48:43.764378Z","title":", author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.764378Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e52ffe3a7c4873174f0825937a291e3c7758e4d600ba0b60ec34a49684f2cdec","observation_id":"a702cc7e-7664-411c-a733-6e62d9961d49","resolution":{"observed_at":"2026-08-12T00:48:43.764378Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.08898","last_updated":"2024-04-21T05:59:37Z","snapshot_observed_at":"2026-08-10T14:41:41.836601Z","submitted_at":"2024-01-17T00:47:43Z","title":"Bridging State and History Representations: Understanding Self-Predictive RL","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.08898","snapshot_observed_at":"2026-08-12T00:48:43.773234Z","title":"arXiv preprint arXiv:2401.08898 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.773234Z"},"links":{"cited_paper":"/paper/2401.08898","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:0e2f01ad764ea52b01aee807612498a07da21e25be62f3157c275cd67b9ac7a0","observation_id":"66e176ce-c77d-4edd-a955-5227dad8bba4","resolution":{"observed_at":"2026-08-12T00:48:43.773234Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.03550","last_updated":"2025-02-05T19:08:42Z","snapshot_observed_at":"2026-08-10T12:46:07.609834Z","submitted_at":"2025-02-05T19:08:42Z","title":"TD-M(PC)$^2$: Improving Temporal Difference MPC Through Policy Constraint","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.03550","snapshot_observed_at":"2026-08-12T00:48:43.783070Z","title":"arXiv preprint arXiv:2502.03550 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.783070Z"},"links":{"cited_paper":"/paper/2502.03550","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e7b3c9f48dd2da5e1cdd6c45d5d3c03728adfd2cb74a98d10977d6812a258517","observation_id":"5974cec4-da9d-49dd-b719-f69b3a4ea8c8","resolution":{"observed_at":"2026-08-12T00:48:43.783070Z","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":"2026-08-12T00:48:43.788493Z","title":"Conference on robot learning , pages=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.788493Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:b86c918d658dea613dd4c31e588547fa409bdc32aef7988b3e9f847be7490f62","observation_id":"a21eed42-d0d2-43af-906c-fadf49141fc7","resolution":{"observed_at":"2026-08-12T00:48:43.788493Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.10122","last_updated":"2018-05-09T09:06:27Z","snapshot_observed_at":"2026-07-31T21:36:45.596575Z","submitted_at":"2018-03-27T15:08:55Z","title":"World Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.10122","snapshot_observed_at":"2026-08-12T00:48:43.793741Z","title":"arXiv preprint arXiv:1803.10122 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.793741Z"},"links":{"cited_paper":"/paper/1803.10122","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:a4110a86a3472b56dd7bb8a97103deac8dd6fd6a7abbd4ab2d2c629ab05db7a0","observation_id":"e74c4449-ae73-48dc-9134-5bedfa202383","resolution":{"observed_at":"2026-08-12T00:48:43.793741Z","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":"2026-08-12T00:48:43.800026Z","title":"2016 IEEE International Conference on Robotics and Automation (ICRA) , pages=","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.800026Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:35e938247bb1450658cc6358d2d2d28f719eb216e728b1720acb0735e7ddd325","observation_id":"05453046-1d4f-4fed-baa2-6bf8004e17e1","resolution":{"observed_at":"2026-08-12T00:48:43.800026Z","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":"2026-08-12T00:48:43.805467Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.805467Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:5d2bcb9aea9ae7093b67285efd0cacaf0cfc5616bbb28b5617824d58033fc6c6","observation_id":"fdbb37c7-128f-4300-99a0-637a8505ac81","resolution":{"observed_at":"2026-08-12T00:48:43.805467Z","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":"2026-08-12T00:48:43.812219Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.812219Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:0e1f19140952ecd1a1dbbdd3a93567b7ca938fe8f566ae1ae29d353bcc272627","observation_id":"6346b7e8-e270-4e32-8b59-a358ed14bec9","resolution":{"observed_at":"2026-08-12T00:48:43.812219Z","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":"2026-08-12T00:48:43.887581Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.887581Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:95b5a966051f77a5a4d0d7bc69a35d393c1284a2df7bf5af5642aef776ae66e6","observation_id":"ba4fd107-1f6d-4719-9e68-1681dc3207e4","resolution":{"observed_at":"2026-08-12T00:48:43.887581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07220","last_updated":"2023-12-30T04:16:38Z","snapshot_observed_at":"2026-07-06T16:31:03.559653Z","submitted_at":"2023-10-11T06:10:07Z","title":"COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07220","snapshot_observed_at":"2026-08-12T00:48:43.931187Z","title":"arXiv preprint arXiv:2310.07220 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.931187Z"},"links":{"cited_paper":"/paper/2310.07220","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:955ca1515d490c58d05fb675b70ba01a6d0aa0f3f8b9497765c76b11b4040cb4","observation_id":"df9dfe30-75cb-421d-9aa3-6b57b8d080bc","resolution":{"observed_at":"2026-08-12T00:48:43.931187Z","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":"2026-08-12T00:48:43.961083Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:43.961083Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:1db13bc063f1e5deb4209c425ae4db59cefe77ca9e957361d064c8860183f3df","observation_id":"8a59a100-b319-49e4-a15c-c3632c901f6c","resolution":{"observed_at":"2026-08-12T00:48:43.961083Z","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":"2026-08-12T00:48:44.014325Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.014325Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:a203765740bcd995fa21f3dca4549f92a31398f3df5a14e3a3993095d0764045","observation_id":"866e7b91-cd58-4b2b-a212-1903425b48c6","resolution":{"observed_at":"2026-08-12T00:48:44.014325Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.06038","last_updated":"2020-02-14T13:57:22Z","snapshot_observed_at":"2026-07-06T08:57:20.804732Z","submitted_at":"2020-02-14T13:57:22Z","title":"Never Give Up: Learning Directed Exploration Strategies","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.06038","snapshot_observed_at":"2026-08-12T00:48:44.053445Z","title":"arXiv preprint arXiv:2002.06038 , year=","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.053445Z"},"links":{"cited_paper":"/paper/2002.06038","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:b6c879e78981d177f9d5ca9154d8fa51c18b6286c216fbbb0515aa6dce65c2c9","observation_id":"7de685ac-596f-42f6-8523-7251ead4d9af","resolution":{"observed_at":"2026-08-12T00:48:44.053445Z","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":"2026-08-12T00:48:44.059904Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.059904Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:00dab8a63d7e104a758cb1de890e5e64c6114cfb79455a4e718a7681fbcebedb","observation_id":"a5fc1bad-1600-422a-b509-cbab437ef210","resolution":{"observed_at":"2026-08-12T00:48:44.059904Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12098","last_updated":"2025-07-31T14:50:20Z","snapshot_observed_at":"2026-08-12T12:18:41.250359Z","submitted_at":"2024-12-16T18:59:53Z","title":"MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.12098","snapshot_observed_at":"2026-08-12T00:48:44.066449Z","title":"arXiv preprint arXiv:2412.12098 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.066449Z"},"links":{"cited_paper":"/paper/2412.12098","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:4b7d1eda7ebb8f2cb8228e28f120b56fc7f21809d4003211656d5dca75fbb6a5","observation_id":"c938ee00-49a0-4d3f-9224-54bdcfd536ce","resolution":{"observed_at":"2026-08-12T00:48:44.066449Z","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":"2026-08-12T00:48:44.072332Z","title":"nature , volume=","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.072332Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:bd19010fe3bd410a06821cad83d13a6854c3244de1f62694b7dbde3c61e00891","observation_id":"a89cd13f-7dd9-4fb9-908d-3ed70fd1b6f9","resolution":{"observed_at":"2026-08-12T00:48:44.072332Z","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":"2026-08-12T00:48:44.078290Z","title":"Proceedings of the aaai conference on artificial intelligence , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.078290Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:45885317b019d426a7c5e487edd8a0e7e009c97bec7caa1cdc019d1685a6dc24","observation_id":"1d7635b6-8253-4f0e-a4db-b7e2aaba4979","resolution":{"observed_at":"2026-08-12T00:48:44.078290Z","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":"2026-08-12T00:48:44.084451Z","title":"Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.084451Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e360e3819ee3add3a60905470025fd005d60063c5ebbc637399763d065cdc59d","observation_id":"a9715d7f-6d3d-4154-b07d-d133c6410890","resolution":{"observed_at":"2026-08-12T00:48:44.084451Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09754","last_updated":"2025-05-29T15:02:38Z","snapshot_observed_at":"2026-08-12T22:24:32.544479Z","submitted_at":"2024-10-13T07:20:53Z","title":"SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.09754","snapshot_observed_at":"2026-08-12T00:48:44.091692Z","title":"arXiv preprint arXiv:2410.09754 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.091692Z"},"links":{"cited_paper":"/paper/2410.09754","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e423801aea418c3c4cfe4d3ee3670fd9af6775fa8c0aea84b32b9b7dea198133","observation_id":"0787e997-171a-42a8-bbc5-fb5348ab050a","resolution":{"observed_at":"2026-08-12T00:48:44.091692Z","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":"2026-08-12T00:48:44.098974Z","title":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.098974Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:ff16d4e62ef198191fa0a81ba0da72d582a45b4b46b2045d7ede39cdda3e5b3f","observation_id":"5a1f2ae1-7053-4aa4-8249-1cf7dd2ab0c7","resolution":{"observed_at":"2026-08-12T00:48:44.098974Z","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":"2026-08-12T00:48:44.105270Z","title":"Proceedings of Thirty Third Conference on Learning Theory , pages =","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.105270Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e72e6696b2df0057c7b2cd83d6cd5ef82f492e076ebae4ac02f83a9e99c33dfe","observation_id":"a7848cbe-36cc-4fd7-b152-8a881c73140c","resolution":{"observed_at":"2026-08-12T00:48:44.105270Z","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":"2026-08-12T00:48:44.111469Z","title":"Proceedings of Thirty Third Conference on Learning Theory , pages =","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.111469Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:4aa9250dd9da63cbb94781e765b023759a19badc92dd3154d09efdcec6e2f35c","observation_id":"9ad6e267-1e30-4cd5-afe6-1f372f6bf4a4","resolution":{"observed_at":"2026-08-12T00:48:44.111469Z","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":"2026-08-12T00:48:44.117463Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.117463Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:7a8261e5453c4d8ebec719394d9189c2863f623ee4572cf4614dbd5f858a20a4","observation_id":"a1dac091-19f1-4d9f-935e-403de56169eb","resolution":{"observed_at":"2026-08-12T00:48:44.117463Z","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":"2026-08-12T00:48:44.123263Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.123263Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:79b0d2675751f41c4b55117c6d07ece959ffdca1cc0bfa5951294279a06718a0","observation_id":"481ad074-4492-4aec-af65-831112326ca8","resolution":{"observed_at":"2026-08-12T00:48:44.123263Z","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":"2026-08-12T00:48:44.133001Z","title":"2022 , url=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.133001Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e95a359d4c5f9d6a5e13c2e7774112f18cfd99e16a7be8e1cf9c8a638cfe5e95","observation_id":"f7b6e6e6-1e94-46b4-8bd9-b07cfae3ea6e","resolution":{"observed_at":"2026-08-12T00:48:44.133001Z","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":"2026-08-12T00:48:44.139018Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.139018Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:8e4fc73dc5ecefcca727a63a024cca0148b77956ed03f3611a0ace4cfbbdca2a","observation_id":"aa9f190a-1632-4f81-a78a-6eedaf61126d","resolution":{"observed_at":"2026-08-12T00:48:44.139018Z","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":"2026-08-12T00:48:44.146145Z","title":"Proceedings of the 36th International Conference on Machine Learning , pages =","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.146145Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:103bc511e90860a5e3bdef3cf346b3113d434e8d24e68caaecc8bd789405c40e","observation_id":"7159aae7-50a7-4cca-8517-d2148e9c84d2","resolution":{"observed_at":"2026-08-12T00:48:44.146145Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.15280","last_updated":"2025-05-29T14:58:32Z","snapshot_observed_at":"2026-08-12T22:33:21.478260Z","submitted_at":"2025-02-21T08:17:24Z","title":"Hyperspherical Normalization for Scalable Deep Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.15280","snapshot_observed_at":"2026-08-12T00:48:44.152418Z","title":"arXiv preprint arXiv:2502.15280 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.152418Z"},"links":{"cited_paper":"/paper/2502.15280","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:bf93433ca08fb80df181a6a90ef2c62217fe61ab7b66d79894c248edd735e7bf","observation_id":"88b5cb1d-64b3-4d44-ac5b-b5468ef11ab0","resolution":{"observed_at":"2026-08-12T00:48:44.152418Z","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":"2026-08-12T00:48:44.157720Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.157720Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:4312f4ecb1eed2ae37df5012d7e47f33102e51ab0b684b5c8d91295c5b4473e2","observation_id":"7db6e75c-242c-4144-bafb-a2ad44777109","resolution":{"observed_at":"2026-08-12T00:48:44.157720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.05826","last_updated":"2021-09-22T08:03:34Z","snapshot_observed_at":"2026-07-06T09:27:40.943546Z","submitted_at":"2020-06-10T13:26:31Z","title":"Transient Non-Stationarity and Generalisation in Deep Reinforcement Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.05826","snapshot_observed_at":"2026-08-12T00:48:44.162632Z","title":"arXiv preprint arXiv:2006.05826 , year=","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.162632Z"},"links":{"cited_paper":"/paper/2006.05826","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:5dae29c4b48ab713c5a69fb797edf56e4051c9b42649aba17bf899ec9f837eca","observation_id":"ae02036d-b966-4feb-a596-1ea638cd1e4e","resolution":{"observed_at":"2026-08-12T00:48:44.162632Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.01078","last_updated":"2022-11-10T15:04:36Z","snapshot_observed_at":"2026-08-13T02:08:45.453593Z","submitted_at":"2022-06-02T15:04:18Z","title":"Deep Transformer Q-Networks for Partially Observable Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.01078","snapshot_observed_at":"2026-08-12T00:48:44.168393Z","title":"arXiv preprint arXiv:2206.01078 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.168393Z"},"links":{"cited_paper":"/paper/2206.01078","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:dfcf212211c0993e10f6de8d2a3afdc430510f1a83c3e2c8cfc52bc8e9151427","observation_id":"a694a16d-40ef-4fa2-a5a3-3939c02c198e","resolution":{"observed_at":"2026-08-12T00:48:44.168393Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.01327","last_updated":"2023-05-08T16:06:13Z","snapshot_observed_at":"2026-08-11T03:20:58.190859Z","submitted_at":"2023-02-02T18:56:25Z","title":"Dual PatchNorm","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.01327","snapshot_observed_at":"2026-08-12T00:48:44.173965Z","title":"arXiv preprint arXiv:2302.01327 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.173965Z"},"links":{"cited_paper":"/paper/2302.01327","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:de0de8d76ed5b44d5abfac17157788cb645d3c10f26cf19c19a148f932184d3b","observation_id":"5f3d7c36-6692-421e-8af4-341ce0394667","resolution":{"observed_at":"2026-08-12T00:48:44.173965Z","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":"2026-08-12T00:48:44.179034Z","title":"Neural Networks: Tricks of the trade , pages=","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.179034Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:40695702ddf3d76c972edd8ee8c4bfbf4617550df4d1a1d9c8cc660c73c97928","observation_id":"6e5d77ba-9bca-45a6-9596-99d4cc7545b6","resolution":{"observed_at":"2026-08-12T00:48:44.179034Z","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":"2026-08-12T00:48:44.196180Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.196180Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:229bf509b9041b1a8b651a22c778daffe154d2c8239363165341abc45eea52cc","observation_id":"89892540-148f-41c9-8199-3c3757fef08d","resolution":{"observed_at":"2026-08-12T00:48:44.196180Z","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":"2026-08-12T00:48:44.230892Z","title":"Neural computation , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.230892Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:766ad06928f1cfd3afc437208bf9269b9043f73641548c2923cbe44011816fca","observation_id":"656a39ed-5baf-4ff7-ae54-47192e079f5f","resolution":{"observed_at":"2026-08-12T00:48:44.230892Z","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":"2026-08-12T00:48:44.264251Z","title":"Proceedings of the IEEE international conference on computer vision , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.264251Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:9ce8239574ce445549988ae540dcc39b7dad03c81a843c948eaa2446bfad85da","observation_id":"eec08843-19a2-4d19-abf2-c7bcd0c556bc","resolution":{"observed_at":"2026-08-12T00:48:44.264251Z","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":"2026-08-12T00:48:44.320932Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.320932Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:8b0a0352e2cd17b916bb90727159faba7d33f1e209ff5e01baa1a18b1c1e09b5","observation_id":"7a978f6a-975e-4358-b266-4072dd8a47da","resolution":{"observed_at":"2026-08-12T00:48:44.320932Z","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":"2026-08-12T00:48:44.343414Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.343414Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:dd8a731842ef79ccf2cfc9273211be996a7e5c2b83f67471c4a64c25021acf86","observation_id":"5c1560b4-eaec-41f4-9ffd-8313f288d136","resolution":{"observed_at":"2026-08-12T00:48:44.343414Z","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":"2026-08-12T00:48:44.397908Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.397908Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:1fd0768b74a371c3f055b0e4836c0dc37b37fed39cd6fd3b56fd782c464468d3","observation_id":"092922f2-095b-4ee8-8015-1802f4ca0e8c","resolution":{"observed_at":"2026-08-12T00:48:44.397908Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.07507","last_updated":"2023-03-13T22:37:15Z","snapshot_observed_at":"2026-08-10T20:20:21.570385Z","submitted_at":"2023-03-13T22:37:15Z","title":"Loss of Plasticity in Continual Deep Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.07507","snapshot_observed_at":"2026-08-12T00:48:44.416722Z","title":"arXiv preprint arXiv:2303.07507 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.416722Z"},"links":{"cited_paper":"/paper/2303.07507","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:6388e529b0e47feb992e20a7fd75d1cafb23b2e86449922160b0d419db286028","observation_id":"4a6eba36-c76c-475c-baf8-4355bc403b0b","resolution":{"observed_at":"2026-08-12T00:48:44.416722Z","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":"2026-08-12T00:48:44.422601Z","title":"international conference on machine learning , pages=","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.422601Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:b25b885dc57533cebb626860ffea4b8c29e6bd3ec7689ef4e03ca8bfe1d81d6d","observation_id":"3083b5e7-f1ff-4425-bf69-49df7a39c65b","resolution":{"observed_at":"2026-08-12T00:48:44.422601Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.05990","last_updated":"2020-06-10T17:59:03Z","snapshot_observed_at":"2026-07-06T09:27:47.020846Z","submitted_at":"2020-06-10T17:59:03Z","title":"What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.05990","snapshot_observed_at":"2026-08-12T00:48:44.428924Z","title":"arXiv preprint arXiv:2006.05990 , year=","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.428924Z"},"links":{"cited_paper":"/paper/2006.05990","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:0f459cdb5575aea205a6b2b0f6a518b0a238cfc069d16662b56b2c98a44ddebd","observation_id":"cc5631e0-0328-4c37-8697-398b072ed5b0","resolution":{"observed_at":"2026-08-12T00:48:44.428924Z","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":"2026-08-12T00:48:44.434101Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.434101Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:b6a34e624ba86cacff092324acf1df2ba7e60b7e4766db36debf66c315c65a1f","observation_id":"f1048067-a307-4dd2-aefb-2b27646ef0d1","resolution":{"observed_at":"2026-08-12T00:48:44.434101Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.10466","last_updated":"2023-04-20T17:11:05Z","snapshot_observed_at":"2026-07-06T15:18:03.563300Z","submitted_at":"2023-04-20T17:11:05Z","title":"Efficient Deep Reinforcement Learning Requires Regulating Overfitting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.10466","snapshot_observed_at":"2026-08-12T00:48:44.439522Z","title":"arXiv preprint arXiv:2304.10466 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.439522Z"},"links":{"cited_paper":"/paper/2304.10466","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:1d5f60d6e04f58598e6394bf40a6012f14d795d4b86b0498941f5d8889592034","observation_id":"ac1316a7-b1ff-449e-87d7-9f2ebf58db65","resolution":{"observed_at":"2026-08-12T00:48:44.439522Z","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":"2026-08-12T00:48:44.446555Z","title":"The Twelfth International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.446555Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e45041528c8fd38529dded4a72b0b6c8347979a494803821f35a940afc986b5d","observation_id":"48e6131f-5c0d-4be8-8b2f-04f73cc9ef8e","resolution":{"observed_at":"2026-08-12T00:48:44.446555Z","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":"2026-08-12T00:48:44.454142Z","title":"The Eleventh International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.454142Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:338e5ce49997dae9fd21f8e11e55959c0205404d5511235aa680739bdfd08667","observation_id":"3621492d-7eb3-494d-ac9d-af93697f62c6","resolution":{"observed_at":"2026-08-12T00:48:44.454142Z","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":"2026-08-12T00:48:44.459722Z","title":"International Conference on Machine Learning , pages=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.459722Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:a82ee02de53a75ed67b6377b48c5aed54c2c02efb515a0325502744f3e184f34","observation_id":"e74d3c0f-1377-4b60-bc1c-b54ecebacb77","resolution":{"observed_at":"2026-08-12T00:48:44.459722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11958","last_updated":"2024-10-24T23:03:41Z","snapshot_observed_at":"2026-08-10T17:19:36.793903Z","submitted_at":"2023-08-23T06:57:05Z","title":"Maintaining Plasticity in Continual Learning via Regenerative Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11958","snapshot_observed_at":"2026-08-12T00:48:44.464619Z","title":"arXiv preprint arXiv:2308.11958 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.464619Z"},"links":{"cited_paper":"/paper/2308.11958","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:ad117789f44c1f7fad808f5519fc3037f926c72fd9d67c172c41e7700e4f5d63","observation_id":"8c078f70-f851-4f6d-ba70-56c10cbd7c74","resolution":{"observed_at":"2026-08-12T00:48:44.464619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.13812","last_updated":"2024-04-09T21:01:56Z","snapshot_observed_at":"2026-08-12T23:26:31.478881Z","submitted_at":"2023-06-23T23:19:21Z","title":"Maintaining Plasticity in Deep Continual Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.13812","snapshot_observed_at":"2026-08-12T00:48:44.469730Z","title":"arXiv preprint arXiv:2306.13812 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.469730Z"},"links":{"cited_paper":"/paper/2306.13812","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:fbfe03289856176f802638954bd0c03b73d1a0a0a365403e6cf09ea2d6e11f58","observation_id":"b1338b8b-881d-4944-bd49-7cc6e514922c","resolution":{"observed_at":"2026-08-12T00:48:44.469730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00246","last_updated":"2024-10-05T00:41:30Z","snapshot_observed_at":"2026-08-09T17:21:57.449710Z","submitted_at":"2023-11-30T23:24:45Z","title":"Directions of Curvature as an Explanation for Loss of Plasticity","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00246","snapshot_observed_at":"2026-08-12T00:48:44.475182Z","title":"arXiv preprint arXiv:2312.00246 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.475182Z"},"links":{"cited_paper":"/paper/2312.00246","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:15cfbb1ff14085e1ab70581be8c2c91b2104ffd434deb641356391a6f3981797","observation_id":"a540b251-0436-4bb3-b40a-c6a3b011decd","resolution":{"observed_at":"2026-08-12T00:48:44.475182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.04345","last_updated":"2025-06-26T16:08:44Z","snapshot_observed_at":"2026-07-06T15:51:58.017259Z","submitted_at":"2023-07-10T05:06:41Z","title":"Continual Learning as Computationally Constrained Reinforcement Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.04345","snapshot_observed_at":"2026-08-12T00:48:44.481432Z","title":"arXiv preprint arXiv:2307.04345 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.481432Z"},"links":{"cited_paper":"/paper/2307.04345","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:892d0e05431be7ffa408825956d1065bdbc58e0d3ce88b55c1d778ac537c8af5","observation_id":"42e671c6-30d9-48c4-a982-7ee30ad37c4b","resolution":{"observed_at":"2026-08-12T00:48:44.481432Z","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":"2026-08-12T00:48:44.487020Z","title":"Proceedings of the thirteenth international conference on artificial intelligence and statistics , pages=","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.487020Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:6f6c9cfa09526447d0f394433ec22c321a5aeb2dddd66633f80321a25293af56","observation_id":"5b658bb8-0a54-45f2-bffb-f9ae7a1703dd","resolution":{"observed_at":"2026-08-12T00:48:44.487020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02178","last_updated":"2019-12-04T18:58:26Z","snapshot_observed_at":"2026-07-06T08:42:06.688732Z","submitted_at":"2019-12-04T18:58:26Z","title":"Fantastic Generalization Measures and Where to Find Them","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02178","snapshot_observed_at":"2026-08-12T00:48:44.492251Z","title":"arXiv preprint arXiv:1912.02178 , year=","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.492251Z"},"links":{"cited_paper":"/paper/1912.02178","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:5f39b3217aee0c89a03eda20885139d427706b1ad6a8689afc0f890173f9841c","observation_id":"939ebcf0-c446-41c6-addd-c322d521372b","resolution":{"observed_at":"2026-08-12T00:48:44.492251Z","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":"2026-08-12T00:48:44.532328Z","title":"International Conference on Machine Learning , pages=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.532328Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:ec4dde75532cebbeae03ea311bbeec1665ffbe42c27422c1bf958f1d818cef8c","observation_id":"e431a621-eb13-49e9-b1ca-0682e4555641","resolution":{"observed_at":"2026-08-12T00:48:44.532328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-08-12T14:19:29.389332Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-12T00:48:44.565673Z","title":"arXiv preprint arXiv:1409.1556 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":87,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.565673Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:137218ca4e3b34957e700714cabdf59841eaaf6e2cf90740eb394e8937dfdf0b","observation_id":"03aa83d4-fd71-4c1d-b067-36639e57df63","resolution":{"observed_at":"2026-08-12T00:48:44.565673Z","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":"2026-08-12T00:48:44.594067Z","title":"Proceedings of the IEEE conference on computer vision and pattern recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.594067Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:9c53b488c93e25debe018b75af4e2a95b08b8fc2c69123fb8ea82446f715fe41","observation_id":"01a53970-1303-4af8-9233-dd8b5f0e2875","resolution":{"observed_at":"2026-08-12T00:48:44.594067Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-13T02:40:23.887636Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-12T00:48:44.632705Z","title":"arXiv preprint arXiv:2010.11929 , year=","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.632705Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:f4b851723f24f553df67835ac12987f6c2b97581e5f4a92354cdfd3af5046905","observation_id":"0733bf70-d8c7-4548-952e-dc4d006018cb","resolution":{"observed_at":"2026-08-12T00:48:44.632705Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-12T00:48:44.662535Z","title":"arXiv preprint arXiv:2303.08774 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.662535Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:418c538ceb69259ad675530ec21082c1ba7262a0a5b733343786d963e9ab4ab8","observation_id":"c9b395ce-24c1-40c4-8e06-7e113214e74f","resolution":{"observed_at":"2026-08-12T00:48:44.662535Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-12T00:48:44.699620Z","title":"arXiv preprint arXiv:2312.11805 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":91,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.699620Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:30ce9b76db27daaa8f2a2ec9bd2ffea0b248fdf2b31ea752c29bf45d1ff7f9c8","observation_id":"ce4d376a-584b-4940-b510-3a5af02928f5","resolution":{"observed_at":"2026-08-12T00:48:44.699620Z","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":"2026-08-12T00:48:44.705590Z","title":"2009 , institution=","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.705590Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:2c7a6a6b9de7893c3875207b141d3a379f82bf45d72cf4e120906ec06213b06b","observation_id":"250fcb3d-91fb-4ccb-9fa3-0cf71b0967b9","resolution":{"observed_at":"2026-08-12T00:48:44.705590Z","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":"2026-08-12T00:48:44.710831Z","title":"http://yann.lecun.com/exdb/mnist/ , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":93,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.710831Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:81ec93d9f164faef5ff74c3892b7df61fef5ffa4ada035f2040d9e596c618da5","observation_id":"11008eb8-e879-48f1-a295-7a029984a27e","resolution":{"observed_at":"2026-08-12T00:48:44.710831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-08-09T20:34:52.923500Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-12T00:48:44.715365Z","title":"arXiv preprint arXiv:1711.05101 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":94,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.715365Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:2b391279b6cd299bb73c86d749975001e37d6dbbaa4374c1444ea2e935cd3ad2","observation_id":"171825c9-837a-4b80-bdd9-d3643d880535","resolution":{"observed_at":"2026-08-12T00:48:44.715365Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.02677","last_updated":"2018-04-30T21:53:41Z","snapshot_observed_at":"2026-08-09T05:23:26.365677Z","submitted_at":"2017-06-08T16:51:53Z","title":"Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.02677","snapshot_observed_at":"2026-08-12T00:48:44.721218Z","title":"arXiv preprint arXiv:1706.02677 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":95,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.721218Z"},"links":{"cited_paper":"/paper/1706.02677","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:982308d9373324edd3c05cdcf70622c69aec1e7df7213e91b7ac98c83b6f12a7","observation_id":"57338cf0-9981-44cc-baf3-464c9f27ba0d","resolution":{"observed_at":"2026-08-12T00:48:44.721218Z","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":"2026-08-12T00:48:44.726473Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.726473Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:e5e30361711e99661c5347ff5f88c631e75384246c5793be2c7dd9c88251f8ab","observation_id":"da8aa900-e90f-42fa-ae55-5bb26bb1c785","resolution":{"observed_at":"2026-08-12T00:48:44.726473Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1607.06450","last_updated":"2016-07-21T19:57:52Z","snapshot_observed_at":"2026-08-12T08:59:05.030983Z","submitted_at":"2016-07-21T19:57:52Z","title":"Layer Normalization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1607.06450","snapshot_observed_at":"2026-08-12T00:48:44.731432Z","title":"arXiv preprint arXiv:1607.06450 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":97,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.731432Z"},"links":{"cited_paper":"/paper/1607.06450","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:0bc4c1d58b7b73e46bd8ddabeb413c4c79631d7c6079f6cd1a0d3d6bd234ea65","observation_id":"e41de224-c6e4-4d61-96a2-cfd42fd61d95","resolution":{"observed_at":"2026-08-12T00:48:44.731432Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.17833","last_updated":"2023-11-15T00:47:58Z","snapshot_observed_at":"2026-08-10T14:08:43.493396Z","submitted_at":"2023-06-30T17:53:50Z","title":"Resetting the Optimizer in Deep RL: An Empirical Study","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.17833","snapshot_observed_at":"2026-08-12T00:48:44.737121Z","title":"arXiv preprint arXiv:2306.17833 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":98,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.737121Z"},"links":{"cited_paper":"/paper/2306.17833","citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:689b33c3ca6b973e5cd9c455e052016871a08582c9aa3941fa4552800114a96e","observation_id":"2ee77a5a-2619-40d5-a0fd-0aa89e696a3b","resolution":{"observed_at":"2026-08-12T00:48:44.737121Z","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":"2026-08-12T00:48:44.743105Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":99,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.743105Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:6b007785ec62bcf36184fa174073fc27251a7ea3ffc5677781030e951fa78492","observation_id":"c087bb13-2e33-4eb3-9917-a72127cbb8a4","resolution":{"observed_at":"2026-08-12T00:48:44.743105Z","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":"2026-08-12T00:48:44.749058Z","title":"International journal of computer vision , volume=","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control","version":1},"reference_index":100,"source":"arxiv_source","source_observed_at":"2026-08-12T00:48:44.749058Z"},"links":{"citing_paper":"/paper/2608.07870"},"observation_digest":"sha256:6964c56f9115db1cc5296cd7c464d0166bf71e9b0ddeb39475c9ae3e7374a2df","observation_id":"99a9f70a-aaba-457c-88c4-3832fdb5da5b","resolution":{"observed_at":"2026-08-12T00:48:44.749058Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.07870","last_updated":"2026-08-08T02:44:43Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T03:11:11.597169Z","submitted_at":"2026-08-08T02:44:43Z","title":"V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":100,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":294},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 100 of 294 outbound references and 0 inbound Pith citation observations for arXiv:2608.07870."}