{"as_of":"2026-08-10T14:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:88fbe0fc11991db9fc18eb54b221d2aed5749c96f871e4aa6553f96862558e62","coverage":[{"denominator":69,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":69,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T18:58:03.161257Z","state":"measured"},{"denominator":69,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":69,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2502.00466/citation-record","integrity":"/paper/2502.00466/integrity","json":"/paper/2502.00466/citation-record.json","paper":"/paper/2502.00466"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.303514Z","title":"Recurrent world models facilitate policy evolution","venue":null,"work_id":"38244200-dfea-4a6f-a309-915d61c48bb0","year":2018},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.498253Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:9287c245324687ea8e90d187bae0a7388da7060788aaa070cd1c9550a9b6a1b2","observation_id":"4df121f6-b5c0-4ea7-a8ce-6a5308aa4084","resolution":{"observed_at":"2026-08-09T18:58:05.309963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.04104","last_updated":"2024-04-17T17:41:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-01-10T18:12:16Z","title":"Mastering Diverse Domains through World Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.04104","snapshot_observed_at":"2026-08-09T18:58:02.505995Z","title":"Mastering diverse domains through world models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.505995Z"},"links":{"cited_paper":"/paper/2301.04104","citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:e48be7a2222698c300ece1db7edd42c99671073f9d90a5c03ff2ae6bc1e13f1c","observation_id":"0decbfd3-2741-4452-aa3c-df6721d4089a","resolution":{"observed_at":"2026-08-09T18:58:02.505995Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.283178Z","title":"Mastering atari, go, chess and shogi by planning with a learned model.Nature, 2020","venue":null,"work_id":"aee0b61d-cd78-43a6-8fd8-af898dca2d5a","year":2020},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.515532Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:970130902b9603d81bacbcf5f42bbbd0d463b69ac4644bff8a888fa4ebccc05c","observation_id":"83231a6d-9685-41ee-8843-d8369a015480","resolution":{"observed_at":"2026-08-09T18:58:05.290136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.257367Z","title":"Mastering atari games with limited data","venue":null,"work_id":"e8e68b46-1fa9-44a5-a222-e3cc6dd7b5f3","year":2021},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.523626Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:1239e30b72b2c5256ef22563068aa39e193ce2ac6382cbc0174a3ea2ad9069a7","observation_id":"7127d582-2752-4efe-b5a2-da8574ba6662","resolution":{"observed_at":"2026-08-09T18:58:05.263683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.236744Z","title":"Day- dreamer: World models for physical robot learning","venue":null,"work_id":"8d46d00c-4a61-449b-8959-c2e5fac4210b","year":2022},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.530937Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:9f4af2c6d9cf0c38bbbcd01bdaaafefc7f47d12af383db4b27191b9f72cc6b99","observation_id":"eb50185c-8934-4c62-a3c5-f1b28966b818","resolution":{"observed_at":"2026-08-09T18:58:05.243920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:02.537734Z","title":"Dream to control: Learning behaviors by latent imagination","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.537734Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:3477689cf07bd9ee233a61e47b31a1110fb92d720965a8a6cda14c1bce47a44c","observation_id":"74699c8f-cecc-46cd-8b21-9e2df6465bb5","resolution":{"observed_at":"2026-08-09T18:58:02.537734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.201322Z","title":"Mastering atari with discrete world models","venue":null,"work_id":"2431b48e-279c-4317-b2bb-93c962feac2a","year":2021},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.548757Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:6294bd79acbaacb747cb59d08bfd53dfc11e205fa8a9f24c581d9c6bfdfc0e2d","observation_id":"0cc5a143-e862-4360-aeb9-e3b3375a471f","resolution":{"observed_at":"2026-08-09T18:58:05.210229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.176418Z","title":"Diffu- sion for world modeling: Visual details matter in atari","venue":null,"work_id":"95d515d0-7f9a-4862-b91e-18d0fbd36369","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.554975Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:6004379369f17a2d8697032efe13d196af9c58ddae392187860d2dfb08f4a264","observation_id":"3fd1d411-1b04-40fe-8d20-09f090ad447f","resolution":{"observed_at":"2026-08-09T18:58:05.184638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.151257Z","title":"Efficiently modeling long sequences with structured state spaces","venue":null,"work_id":"83f8c901-d958-4927-afbc-aefa6be715b1","year":2022},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.561092Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:715f48cd78c109d97db6c275cdf57c3671c634658294e439e360ab549f887a98","observation_id":"6ff22636-4643-4456-903b-952f9619da2f","resolution":{"observed_at":"2026-08-09T18:58:05.159157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.129040Z","title":"On the parameterization and initialization of diagonal state space models","venue":null,"work_id":"2bc051fd-941e-40b5-9fe1-5bb36fd4a7b7","year":2022},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.566746Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:ca3032eea9e4ad8a98d3c8765dbc178420025c55f38b40fa78c4745bd95513f6","observation_id":"756fff41-9c54-4ae1-84c4-f2abfc0ebb88","resolution":{"observed_at":"2026-08-09T18:58:05.135871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.104635Z","title":"Smith, Andrew Warrington, and Scott Linderman","venue":null,"work_id":"7cde1da6-de61-428a-b0c7-bb3518ec9990","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.579969Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:5a978a488d011cf853f5ed017ac73551209ead7cebfa0464988f257e9a16816e","observation_id":"2017cfae-cb54-4e17-862b-a06779242f84","resolution":{"observed_at":"2026-08-09T18:58:05.113064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.069719Z","title":"Mamba: Linear-time sequence modeling with selective state spaces","venue":null,"work_id":"8abf1976-a74a-4f51-a17c-a3b5bb20b5eb","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.595151Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:9e658dd11e2160403168a8f96ed1c7eae97b5dd5fa0fc794e97f3738b700e5fa","observation_id":"d3a908ba-db65-4624-aba8-72eed72139fd","resolution":{"observed_at":"2026-08-09T18:58:05.076387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.044509Z","title":"Transformers are ssms: Generalized models and efficient algorithms through structured state space duality","venue":null,"work_id":"9aaee9d5-37d0-491f-bbba-bbdc320102aa","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.601129Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:ac6d239b9049ac8656865c29877429631266f0fb279e6f41ced733271986b428","observation_id":"132e978a-b594-463e-996b-708c9c8d3b33","resolution":{"observed_at":"2026-08-09T18:58:05.051849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:05.026070Z","title":"Mas- tering memory tasks with world models","venue":null,"work_id":"718c2751-592b-4d59-ad6f-6d364209f9db","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.611074Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:519bc4e0d8339e2ef325813fff84e47f9ef5dcc1118f5adef6c5f4d8dd9d4374","observation_id":"274787c8-5086-4420-b86d-6c9a1a1d1447","resolution":{"observed_at":"2026-08-09T18:58:05.031871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.999541Z","title":"Model based reinforcement learning for atari","venue":null,"work_id":"afc582f4-6ecf-4fd1-bca4-dc1390942d0d","year":2020},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.626384Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:c950e96ac69cef76a3744e07c7bf6f5b770a8465bdddb41d3464499f65ee1815","observation_id":"32f7d157-a061-4a80-a13e-1d0390ee7fc3","resolution":{"observed_at":"2026-08-09T18:58:05.008492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.972182Z","title":"Minigrid & miniworld: Modular & customizable reinforcement learning environments for goal-oriented tasks","venue":null,"work_id":"3e41624d-3795-4be5-a66b-e0a51d591049","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.635024Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:538b8758cbefca22644e66c6afb6518055e4d9a0475e4d4071dced877dbdfec7","observation_id":"d004d802-1126-413d-bf85-fb69c6fe182a","resolution":{"observed_at":"2026-08-09T18:58:04.979877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.944299Z","title":"Benchmarking the spectrum of agent capabilities","venue":null,"work_id":"25cc0489-cdbf-43ef-bdf8-fed0dc066486","year":2022},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.646275Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:44797fb864e81f757a2dc043b17172d0dead04648c0d19623292d78cc10b899d","observation_id":"4b9a6c6c-3d33-41f8-9fb1-45228a89be04","resolution":{"observed_at":"2026-08-09T18:58:04.953051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.02097","last_updated":"2016-09-20T19:12:49Z","snapshot_observed_at":"2026-08-10T09:46:02.795273Z","submitted_at":"2016-05-06T20:46:34Z","title":"ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.02097","snapshot_observed_at":"2026-08-09T18:58:02.652160Z","title":"Viz- doom: A doom-based ai research platform for visual reinforcement learning","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.652160Z"},"links":{"cited_paper":"/paper/1605.02097","citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:fc302ce808aba0072d7af267106dfcc3ab0c824ae990b4633b2cbf146a1bc456","observation_id":"a1e3ca45-420a-4508-84b3-1c009bd287d0","resolution":{"observed_at":"2026-08-09T18:58:02.652160Z","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":"2026-08-09T18:58:02.660880Z","title":"Denoising diffusion probabilistic models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.660880Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:e3d7e6ef9092e1c5edf52a30a2fc27241607cb4b17e730acdf9646416b97e5b1","observation_id":"2ffb24b7-54e1-4ee5-99d6-6e46e080d628","resolution":{"observed_at":"2026-08-09T18:58:02.660880Z","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":"2026-08-09T18:58:02.669247Z","title":"Denoising diffusion implicit models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.669247Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:e0d6d7d0444b143549f74394fb461d2fb7e18d1e0c810f505198fbf830429b4b","observation_id":"439873c0-9585-4d01-b48c-5f15630197ba","resolution":{"observed_at":"2026-08-09T18:58:02.669247Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.884752Z","title":"Generative modeling by estimating gradients of the data distribution","venue":null,"work_id":"d22bcd4c-08c8-4b94-8218-cd116c350d48","year":2019},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.677548Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:276fd6586d7cae0d1c5a624b01c7cb21451b1ef7c3dd3cf77a1f337793e3193b","observation_id":"d8571c75-ca07-427e-9390-80a3c199b390","resolution":{"observed_at":"2026-08-09T18:58:04.891833Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.852236Z","title":"Score-based generative modeling through stochastic differential equations","venue":null,"work_id":"3c495c02-1e81-415e-acdc-331da265e9ab","year":2021},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.686175Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:4b1abfd088d6672c92a231745c6dad7debeb0a665def77a8971a5c72df35b9ed","observation_id":"2e311af2-d58b-46cb-986d-c7018aa49872","resolution":{"observed_at":"2026-08-09T18:58:04.858957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.825058Z","title":"Tenenbaum, Sander Dieleman, and et al","venue":null,"work_id":"34fae2ab-272b-46fc-9346-4608ece4a044","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.696697Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:7d70c2758c44e23ba17e4e7aeda742d756fb3897233ab99d921c041e92395f88","observation_id":"52134006-ab7b-49f3-9e90-4d9cad9f8e67","resolution":{"observed_at":"2026-08-09T18:58:04.832316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.795963Z","title":"Diffusion policies as an expressive policy class for offline reinforcement learning","venue":null,"work_id":"4ae34c01-2941-4853-b53a-3d74ba6ea0da","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.702117Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:138b27321d57a7d625afb9327f0abdfa1a7a301fdadaf8feaf08a35e8fd3b7c8","observation_id":"55157e0c-50d7-485a-9925-e445829c2dbf","resolution":{"observed_at":"2026-08-09T18:58:04.802397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.772026Z","title":"Tenenbaum Joshua, S","venue":null,"work_id":"af84f899-3eef-4adc-a437-c5febbd1dc32","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.720604Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:c6d91acb0a8aa0672f74a22ef89f4dd6327b73e54efb2d38daa4740844abc27e","observation_id":"a97155ef-24d1-4e76-bfbc-d9b8bb95f071","resolution":{"observed_at":"2026-08-09T18:58:04.778065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.742185Z","title":"Imitating human behaviour with diffusion models","venue":null,"work_id":"13d73834-18b8-4564-9343-c7a1a3080e9a","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.729528Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:e3993a013bcbfa5806c7e0d5d5289647bbff1cafc8dbc2895261aaa5bb916a50","observation_id":"fea711b7-135d-4cb3-9c14-fefdcfce05dc","resolution":{"observed_at":"2026-08-09T18:58:04.751086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.708045Z","title":"Tenenbaum Joshua, and Levine Sergey","venue":null,"work_id":"8aae5730-86bc-4022-87d4-def82eb7419f","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.743578Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:6111e0455a815e3fee06381114f0ce67f7f21f25c80af14dbdfc20af6bfa06bd","observation_id":"92d222ab-d74a-4223-9077-c673a18a3497","resolution":{"observed_at":"2026-08-09T18:58:04.719651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.667381Z","title":"Adaptd- iffuser: Diffusion models as adaptive self-evolving planners","venue":null,"work_id":"bd490318-4c5a-493a-9754-01c1839e4816","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.750867Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:1111af5b14614613fb9af6e3042691620f4ba07edd4c106e9b8c81a569cd7b25","observation_id":"6199ab25-5cde-46c3-9576-6d86b4c21dac","resolution":{"observed_at":"2026-08-09T18:58:04.677332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.644004Z","title":"Extracting reward functions from diffusion models","venue":null,"work_id":"ae6d008e-d084-4a87-914c-dde8747bd8e8","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.759806Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:35a3f4f30be9878084f89096e317e981a577b7022df0e3c3ee54f21bf2137934","observation_id":"782329b9-5e0a-4edb-a75b-8efdbd00b494","resolution":{"observed_at":"2026-08-09T18:58:04.650886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.619331Z","title":"Metadiffuser: Diffusion model as conditional planner for offline meta-rl","venue":null,"work_id":"1a2213cb-8e4b-45b2-b15e-7e2af00fcf36","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.775512Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:4fac1b72eb37fd16594328fbb5db3523e54a6d41f3db40fb066eddbefd555fc9","observation_id":"9b6038a6-0c0c-4032-92f5-7bde9980f5ec","resolution":{"observed_at":"2026-08-09T18:58:04.625902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.594380Z","title":"Synthetic experience replay","venue":null,"work_id":"fa0049d4-5511-4814-b6a4-38480e38d014","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.789254Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:17826a87e8d0673aadd64149f6e3f3bdceee8a81636d7bd11f24aac2800570ec","observation_id":"6cd035e8-9d1d-4343-89dd-d4935bc9228d","resolution":{"observed_at":"2026-08-09T18:58:04.600529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.567763Z","title":"Transformer-based world models are happy with 100k interactions","venue":null,"work_id":"24cfc048-f602-4653-97ff-235953b95994","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.797071Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:79835040ccf88feeaf76cabb9691e4833564528bdc4a315341ca4506ce3cc1cc","observation_id":"41152686-902c-44a2-8b4e-93b46d122798","resolution":{"observed_at":"2026-08-09T18:58:04.575970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.535426Z","title":"STORM: Efficient stochas- tic transformer based world models for reinforcement learning","venue":null,"work_id":"77eab3c0-f1ce-4b9c-8647-2b32c80a6bd2","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.805874Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:ba66709e4e8bdac20ee18d00966d326176745a610863f3381a4eb7f9b563c34a","observation_id":"7dd9ed3a-2df4-4c7b-8cf4-027d01074067","resolution":{"observed_at":"2026-08-09T18:58:04.542951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:02.817309Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.817309Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:1ba0d228ddd243fe34d08c16592c8d855ca89ea8431ab9f21d8001dee999164c","observation_id":"d254397e-c752-4e41-a2b4-1563b0a4eb3c","resolution":{"observed_at":"2026-08-09T18:58:02.817309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.490852Z","title":"Transformers are sample-efficient world models","venue":null,"work_id":"dfe272b9-d9b7-428d-89ee-279da3d8e566","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.825911Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:de666c12b5240b7f9baa8e5765257dc72ba995cb708ba3e92fd245114deced4b","observation_id":"c80d240c-8c15-4bcd-a2e2-6517f36b2d19","resolution":{"observed_at":"2026-08-09T18:58:04.499638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.453924Z","title":"Learning to Simulate Dynamic Environments with GameGAN","venue":null,"work_id":"dad24f84-9ea3-4166-8d6d-d1180e501136","year":2020},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.833013Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:ba38b6ce5c4b653f357bf116a38a07251712d627b142933b3e42201129626d09","observation_id":"93e7b57b-766f-45e4-ba02-67d5137d9638","resolution":{"observed_at":"2026-08-09T18:58:04.469526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.420538Z","title":"Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, and Tim Rocktäschel","venue":null,"work_id":"8bcce758-a55e-4e21-80b4-35576b7fd41f","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.841741Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:978b1dbdc05b41b8d7e38fc13bbcf988743db78b74b4df5abfc1de110d2545a7","observation_id":"4eb45a31-4934-49a9-bf77-74d2b317327b","resolution":{"observed_at":"2026-08-09T18:58:04.430238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.14837","last_updated":"2025-04-24T03:03:57Z","snapshot_observed_at":"2026-07-06T19:06:23.640089Z","submitted_at":"2024-08-27T07:46:07Z","title":"Diffusion Models Are Real-Time Game Engines","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.14837","snapshot_observed_at":"2026-08-09T18:58:02.848431Z","title":"Diffusion models are real-time game engines","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.848431Z"},"links":{"cited_paper":"/paper/2408.14837","citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:bb68ba3217287024f7d9ac0a9caafd803a8de1c9d025fc2e7228f8e462c71a3d","observation_id":"f67418a1-b8c7-479e-8dd0-b8b3df14621d","resolution":{"observed_at":"2026-08-09T18:58:02.848431Z","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":"2026-08-09T18:58:02.855341Z","title":"Gaia-1: A generative world model for autonomous driving, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.855341Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:3f79cc7dbf100eebc08da5bb49e359f23f998da72df71d65e3df658652be7877","observation_id":"86ce5179-ecb4-4742-b060-4756149549cf","resolution":{"observed_at":"2026-08-09T18:58:02.855341Z","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":"2026-08-09T18:58:02.862904Z","title":"Gaia-2: A controllable multi-view generative world model for autonomous driving, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.862904Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:ee4657f8d8e47a1a7794d59d78ed928c265174176da98a5ea81e40c4a273e18f","observation_id":"7ea2b069-fa0a-4338-bfff-7b27acd73999","resolution":{"observed_at":"2026-08-09T18:58:02.862904Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.359519Z","title":"Xing, and Zhiting Hu","venue":null,"work_id":"4537f5cb-7c05-43d9-986e-a33fc52bfd17","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.868683Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:f415a01b4a9c655078c5afd24a447ede5abd5d09b5dc1cbba496399f7b73d0e6","observation_id":"9839cd65-d8d4-4218-88bb-1754a310e6cf","resolution":{"observed_at":"2026-08-09T18:58:04.366528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.331544Z","title":"Hippo: Recurrent memory with optimal polynomial projections","venue":null,"work_id":"59b28f21-1a5b-48a4-aa88-ed5435a671c5","year":2020},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.875450Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:f2307b1bd0aceed1bfd32f8d17d69a4cabb91e45e23252e13c30136ab94e5a26","observation_id":"4fc811c2-9854-40e8-a315-85d528ffc3b5","resolution":{"observed_at":"2026-08-09T18:58:04.341967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.308347Z","title":"Diagonal state spaces are as effective as structured state spaces","venue":null,"work_id":"6d08cc57-f1fc-44d1-93e0-c573ce707b45","year":2022},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.883372Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:a322fac0f1e5200639d36f969bf83b50b2f227194e9d2f99e0bb397c3a2d536b","observation_id":"1ef1388d-b81b-46c0-a34b-df87fa21ab01","resolution":{"observed_at":"2026-08-09T18:58:04.315625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.277436Z","title":"Liquid structural state-space models","venue":null,"work_id":"f997e354-e148-49cd-b6e7-b2caa0648572","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.890888Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:bd32a890497724fded6e5a3ea490a5488b79a125aed5e4e1f2b773a670979f5b","observation_id":"60c57300-b502-4a15-899e-7119f4849896","resolution":{"observed_at":"2026-08-09T18:58:04.289110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.234800Z","title":"Structured state space models for in-context reinforcement learning","venue":null,"work_id":"288a2c3e-4bfd-4eca-9e46-6d8b50562491","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.898205Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:3910cd9e088965d515f92ef7f17edae9ac7493d8de49b98ee1aa7e23334ed82e","observation_id":"2afea137-90bb-4e7e-9df7-cc240d21bba0","resolution":{"observed_at":"2026-08-09T18:58:04.243282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.208095Z","title":"Decision mamba: Reinforcement learning via hybrid selective sequence modeling","venue":null,"work_id":"ee8b7079-773c-4f00-96cd-e9917d2b8f00","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.904938Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:ca765306dfedef13d6bfd3c0089cd480c2d3f57deb0308de6e8aeb4e0aeea08b","observation_id":"d6c9d9ff-fd5d-457c-ba0e-ad9642743ff5","resolution":{"observed_at":"2026-08-09T18:58:04.215162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.179931Z","title":"Decision trans- former: Reinforcement learning via sequence modeling","venue":null,"work_id":"8974fd1c-0337-4efd-8059-8fbc72b9dbfd","year":2021},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.913136Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:f1ec7be29379da1ac3a286d9aa76f7843a1aec2b2bcebb0b63532fd1726eb2e9","observation_id":"2f6a77fe-39b8-40ea-8fc9-e9bfaab6c57f","resolution":{"observed_at":"2026-08-09T18:58:04.186813Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08893","last_updated":"2025-05-16T15:49:48Z","snapshot_observed_at":"2026-07-06T19:31:53.397265Z","submitted_at":"2024-10-11T15:10:40Z","title":"Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient","version":4},"cited_work":{"arxiv_id":"2410.08893","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.08893","snapshot_observed_at":"2026-08-09T18:58:03.543677Z","title":"Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient","venue":"cs.LG","work_id":"f988f9c8-7f52-4b21-90b1-b594f294e279","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.924204Z"},"links":{"cited_paper":"/paper/2410.08893","citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:bc725466bdcea6dbf970ea6334078acea7fe44031d8931552317d906338c95fa","observation_id":"1d2e67ba-cde8-41b4-8b94-ff0fb8e09ad8","resolution":{"observed_at":"2026-08-09T18:58:03.555549Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.154621Z","title":"Optimal control of markov processes with incomplete state information","venue":null,"work_id":"3c5c2cdb-77d6-463e-8e49-4f0eae36f96c","year":1965},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.931453Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:731aa333158d7d0a3c9aa2dd2825c56271865e0a3925a8364a816f28e181abe3","observation_id":"3f79d976-cce3-4c7a-9de6-fa6b9190cef8","resolution":{"observed_at":"2026-08-09T18:58:04.161594Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.130467Z","title":null,"venue":null,"work_id":"a68bec1b-3fa3-4ff3-a0f4-ff6d1a4c8840","year":1988},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.938088Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:ac4abc2a41e2174c0756aa9692cfa49f4536998257a3936abe9f03506621a2e9","observation_id":"9be24e13-7d4b-443f-8cbd-4a8c81174a54","resolution":{"observed_at":"2026-08-09T18:58:04.137037Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1801.01263","last_updated":"2018-01-04T07:26:55Z","snapshot_observed_at":"2026-08-08T15:14:09.707574Z","submitted_at":"2018-01-04T07:26:55Z","title":"Improving the Closed-Loop Tracking Performance Using the First-Order Hold Sensing Technique with Experiments","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.01263","snapshot_observed_at":"2026-08-09T18:58:02.946927Z","title":"Improving the closed-loop tracking performance using the first-order hold sensing technique with experiments","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.946927Z"},"links":{"cited_paper":"/paper/1801.01263","citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:46af9e01093f96f5f9dee0dd10624a1533679ac34d2f2ff7cd257c8b41bb43bf","observation_id":"7d16d97f-826d-4cd7-b752-d15a240491cb","resolution":{"observed_at":"2026-08-09T18:58:02.946927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.100580Z","title":"Hochreiter and J","venue":null,"work_id":"31caf901-0a28-41e1-84f6-f8a396f46636","year":1997},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.960402Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:e13c66f06e4871fa3301479f85db9d2159147e6c9135f6c919bbb1e54d10df7f","observation_id":"5eb44454-6a0a-4977-a0bc-b741d3ea605c","resolution":{"observed_at":"2026-08-09T18:58:04.109185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.074123Z","title":"Chung, C","venue":null,"work_id":"46c17451-ca60-4ab2-bfe6-1ad101e48611","year":2014},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.966410Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:5ec92b79b907a6b3f8c0ab5fa9f48efa528582a9fb80f18b703f3bd3d7f4a82d","observation_id":"af0674f3-1207-42aa-8d24-027aff1db4a1","resolution":{"observed_at":"2026-08-09T18:58:04.084293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.051530Z","title":"Learning semantic- aware normalization for generative adversarial networks","venue":null,"work_id":"267f79fa-4789-4a85-8b00-34b3d5a95f52","year":2020},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.975317Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:9f95b6d6da9c82b1e668ba5166948857b7b9bac916effcf63411940cff78a73c","observation_id":"bcb79119-2b76-45cd-b3b0-2ac0119bb909","resolution":{"observed_at":"2026-08-09T18:58:04.059338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:04.022651Z","title":"Harmonydream: Task harmonization inside world models","venue":null,"work_id":"76bcb6bb-43f4-4917-ac5c-19c27bd92821","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.985020Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:a435e8a4126960784efd75d1e01c93a7ac4358ab610f301107d8d9c9d13721fd","observation_id":"cb3b3d90-ee9f-48d1-b2a5-04c4b8c065ef","resolution":{"observed_at":"2026-08-09T18:58:04.031691Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.999096Z","title":"Dueling network architectures for deep reinforcement learning","venue":null,"work_id":"5300f408-8884-4da1-a7e5-301631f9547c","year":2016},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:02.997301Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:10106c3e3a95679b81ef6fa6cb13afd09155ef264c77da06eccdb3e0ec0c8c41","observation_id":"b568bcf2-905d-48f9-9b87-fb1bb5a6ca87","resolution":{"observed_at":"2026-08-09T18:58:04.007800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.966238Z","title":"Deep reinforcement learning at the edge of the statistical precipice.Advances in Neural Information Processing Systems (NeurIPS), 2021","venue":null,"work_id":"90788c06-2743-4b05-bed0-d78009a31d58","year":2021},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.005459Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:6ddb491cbeb9a698fe2a893ff630eb983a2aebf828b9f6542be9b9768e82df0a","observation_id":"c8ecdcf3-6e0a-44ea-b6e0-605ddf169ee4","resolution":{"observed_at":"2026-08-09T18:58:03.977032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.942285Z","title":"Towards efficient world models","venue":null,"work_id":"c4add7be-8a30-4d1d-8f5c-ad12b4975bf0","year":2023},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.013250Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:22fc592008b9136ff086d0c872ad776c4fd10d5c98bc5c500594fc25fc1fdcae","observation_id":"3511ad0b-3ed1-42b2-9fdd-791ecdca2e16","resolution":{"observed_at":"2026-08-09T18:58:03.949042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.029432Z","title":"Deep unsuper- vised learning using nonequilibrium thermodynamics","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.029432Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:d5c2f3a642ebd5c51c4f7dfe5c072c11d338f52a41739d6e9e7b6a91da33bcb0","observation_id":"c46fa698-bdf0-4fb3-a2f9-2b77c75c7cec","resolution":{"observed_at":"2026-08-09T18:58:03.029432Z","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":"2026-08-09T18:58:03.038838Z","title":"Diffusion models beat gans on image synthesis","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.038838Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:62b7a05cdad87f3fff83c4da9db856c73b654ffd7c318b8e2551f7f4fd82581b","observation_id":"09440ecc-de37-4045-86ae-b73ea5ccfcd1","resolution":{"observed_at":"2026-08-09T18:58:03.038838Z","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":"2026-08-09T18:58:03.048364Z","title":"Improved techniques for training score-based generative models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.048364Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:3ffc54805ca9d4edf08bb3bfed968119b159294154d761d83a1bf1a5b9fc334d","observation_id":"f93fe439-193a-441b-9243-252d1824cff8","resolution":{"observed_at":"2026-08-09T18:58:03.048364Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.848967Z","title":"Denoising likelihood score matching for con- ditional score-based data generation","venue":null,"work_id":"cac94479-a578-4936-8b32-22c2781375d2","year":2022},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.055799Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:301408874ce2083a6a1e32f7881587952e1578dad32f6bcaeecdeaa875219417","observation_id":"c6bbf1fc-25d1-4845-9b92-e9f8b92f9386","resolution":{"observed_at":"2026-08-09T18:58:03.858324Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.066711Z","title":"Elucidating the design space of diffusion-based generative models.Advances in neural information processing systems, 35:26565–26577, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.066711Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:fffe6929bc084b65ab989e19d95439a35a1d5a419ae3b5d07758d48f4c14eb5d","observation_id":"6ad4d1f8-b260-42de-bb27-e19a160b54cc","resolution":{"observed_at":"2026-08-09T18:58:03.066711Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.791819Z","title":"Multitask learning.Machine Learning, 28:41–75, 1997","venue":null,"work_id":"cbb8561e-7a3c-49fc-bfcc-9f41c0606137","year":1997},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.108257Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:3d0edf38ae97758cce5411e27b045c9a4f0f7ae1604b68cbc5762a26ff83c2a4","observation_id":"e6ae9bc3-8b85-4167-a7ac-b6c23fb7d142","resolution":{"observed_at":"2026-08-09T18:58:03.801575Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.755125Z","title":"Improving token-based world models with parallel observation prediction","venue":null,"work_id":"ecc9d83a-b101-4618-91f0-81827a70a7f2","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.121815Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:f9738865baf44f55574ed334eaf9ccf9c06619d4fca2e0a5daa788d2fabc96d0","observation_id":"fd0bf9d0-18b8-4fd8-940c-4422a936967c","resolution":{"observed_at":"2026-08-09T18:58:03.761918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.722603Z","title":"Learning transformer-based world models with contrastive predictive coding","venue":null,"work_id":"f0e1b72e-a019-46e5-9ab2-6693811bcd5e","year":null},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.132097Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:e251b0a595f658d90cac9310315bbedba7aba7bdb3b1a690b3aa7c2b99ba52fb","observation_id":"bb8d215f-4db7-4feb-92b4-aec620109750","resolution":{"observed_at":"2026-08-09T18:58:03.733991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.671118Z","title":"Parallelizing model-based reinforce- ment learning over the sequence length","venue":null,"work_id":"90206154-2dbe-4f1d-9a46-bcd626b4721c","year":2024},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.151708Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:d51a3b4ed43d820363dfada39bf98271bbd98a4dd60da682c26d726590361555","observation_id":"fd0fc18c-5bb4-4033-96db-52e4b6be1b34","resolution":{"observed_at":"2026-08-09T18:58:03.679552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"4340.06630","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.432985Z","title":"Sutton and Andrew G","venue":null,"work_id":"0995c6ff-87d2-4c7c-bbd7-f506e6482e2f","year":2018},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.161257Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:94f3892ff1e3a21461fafb5a569fffc2dbeae7c5c6421b74b0d18f619a223271","observation_id":"26353fe6-af1c-49fb-8424-2239025a5653","resolution":{"observed_at":"2026-08-09T18:58:03.453652Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:58:03.696949Z","title":null,"venue":null,"work_id":"59b22a17-8dba-46af-a2b5-4a545199d9b6","year":null},"citing_paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-09T18:58:03.141440Z"},"links":{"citing_paper":"/paper/2502.00466"},"observation_digest":"sha256:bdf9351360ec19aa2229c716a39c346afb42ea4f10db2ab41a5b7e08247f6d49","observation_id":"b90ee21e-02d5-4735-bb06-c5898f3be68b","resolution":{"observed_at":"2026-08-09T18:58:03.703893Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.00466","last_updated":"2025-06-15T17:04:54Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T18:50:50.220174Z","submitted_at":"2025-02-01T15:49:59Z","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling"},"reference_resolution":{"displayed":69,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":1,"verified_fuzzy":51},"total_outbound_references":69},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2502.00466."}