{"as_of":"2026-08-06T06:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1321dbd0f588ae6eed5b846f962347cf5e5b7363f19b3e92d8f951a067a18517","coverage":[{"denominator":50,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":50,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-12T12:05:57.682386Z","state":"measured"},{"denominator":50,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":50,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+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/2606.26025/citation-record","integrity":"/paper/2606.26025/integrity","json":"/paper/2606.26025/citation-record.json","paper":"/paper/2606.26025"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Tran, Radu Soricut, Anikait Singh, Jaspiar Singh, Pierre Sermanet, Pannag R","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:6ac5f603df3d925a83a3941ebdf67f10b19d2959ac1158650dc046463d345a9f","observation_id":"b1df1a76-ee05-49e6-8b39-154d2e7b9ab8","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.09246","last_updated":"2024-09-05T19:46:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-13T15:46:55Z","title":"OpenVLA: An Open-Source Vision-Language-Action Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.09246","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, and Chelsea Finn","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2406.09246","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:a7889f17f65b9199cdd41576cfb051fc21be721974711ca63329d14be9bdd73b","observation_id":"8854b983-6229-4b40-8119-d8f4191cd4c2","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.24164","last_updated":"2026-01-08T17:01:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-31T17:22:30Z","title":"$\\pi_0$: A Vision-Language-Action Flow Model for General Robot Control","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.24164","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"π0: A vision-language-action flow model for general robot control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2410.24164","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:c584f931ec70474e5ac0540b7fbd34b37673e30cb676fa7edcf13780438024a7","observation_id":"7e5dd307-c5af-4138-a903-f431b656dfe0","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2510.13626","last_updated":"2025-12-26T12:19:56Z","snapshot_observed_at":"2026-07-06T22:32:42.381894Z","submitted_at":"2025-10-15T14:51:36Z","title":"LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2510.13626","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2510.13626","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:695cbcc6143612758bd1030b4fdaa5d4825ff7e33c711557a5f7dbfa74dfd6a0","observation_id":"15a18cb3-2460-47d5-9b0b-325163ef454e","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Goldberg","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:6d0b7d8acdeb6fa35e8909afe23201d564ee7fd3b1bbf560d2ca83585f848cdb","observation_id":"33548797-233d-45ab-9870-ef5bb28ef4cc","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.09769","last_updated":"2025-09-11T18:02:48Z","snapshot_observed_at":"2026-08-05T21:03:29.576416Z","submitted_at":"2025-09-11T18:02:48Z","title":"MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.09769","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Mimicdroid: In-context learning for humanoid robot manipulation from human play videos","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2509.09769","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:5561232b5aed76a9be84e534039019655709db310e85599e134e3a017c7411f6","observation_id":"10c874f3-da37-429e-a71c-642627d80fd2","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Language models are unsu- pervised multitask learners","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:82a9f2cfb740b7d289188857440a6e090ab2439e15bc6046e98ade3b451de3da","observation_id":"01eea3b5-9a98-4db3-a828-c3714bbf94fc","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Llama: Open and efficient foundation language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:56b23a48f469300e3483133da9a4dec46b5f613a8eb182b1aeb70b4d8a838891","observation_id":"89fb8244-9533-4f84-ae6a-c69f69909b7a","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Introducing chatgpt, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:c2fb976bd130d62640dc62b7640d11828ef5612ac1ff8039cd7b9ea28a8e7028","observation_id":"634f9de5-da21-43d8-ac64-6c001529eab8","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":null,"venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:7214a2d9303e5614d57bd3c94b6d83e649c7692417295722c3b687ca27d1999f","observation_id":"d7204318-91ef-4745-bf39-aab6d526410c","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:e1c942bcf188d820c34b2e8940d64082d311b2556249478c1eb51d3ed3bd511b","observation_id":"4c2e2353-54bb-47c1-b80e-5b9d827b5e66","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"A survey on in-context learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:709385899f70a1c5ea8ac41b0973c1464923f89106a99618f7fd1382b8cb25fe","observation_id":"1b2e6d06-ab0f-43f9-b416-ae5d83bd4d08","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:0d40e83e5a238800a86cd3b40d1cd61baec36caae0dab468adc0829518ae9d4a","observation_id":"2d45bfad-5859-4b5c-85e3-7871140399d3","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.02062","last_updated":"2025-08-04T05:01:11Z","snapshot_observed_at":"2026-08-06T05:14:35.807514Z","submitted_at":"2025-08-04T05:01:11Z","title":"RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.02062","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Ricl: Adding in-context adaptability to pre-trained vision-language-action models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2508.02062","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:b9708bc295cf5d0974a1a6289d9da6d86a4eba0cb8fc520512eef83b481b84da","observation_id":"991f3055-7b1e-4e86-b084-7f627d3266ab","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.12943","last_updated":"2024-08-27T23:15:11Z","snapshot_observed_at":"2026-07-06T17:47:13.814205Z","submitted_at":"2024-03-19T17:47:37Z","title":"Vid2Robot: End-to-end Video-conditioned Policy Learning with Cross-Attention Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.12943","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Joshi, Ayzaan Wahid, Danny Driess, Quan Vuong, Pannag R","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2403.12943","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:43c3ce5833593e54596e5f51c3e6c539a4447fd28ce8efe38b7bbd0245deafbd","observation_id":"a3d179df-d985-4252-8814-069ac488d1a8","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Model-agnostic meta-learning for fast adaptation of deep networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:ddc7220b216ddfe7706479e8e1dd75f2a54fc08523b2de04dfc8635763ccbe82","observation_id":"ae691da8-7d10-4b7f-9b9a-93081501e768","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Meta-learning with implicit gradients","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:819a70029eca575c9ef27de19d059fc17bddb5969f52804f2561aeed5026e75f","observation_id":"dbb5135e-6fe0-4a1c-9c50-8380b597cca4","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1611.02779","last_updated":"2016-11-10T01:17:36Z","snapshot_observed_at":"2026-08-02T07:58:55.035919Z","submitted_at":"2016-11-09T00:13:29Z","title":"RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.02779","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Rl 2: Fast reinforcement learning via slow reinforcement learning","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/1611.02779","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:c7d9ccb015ba735c3596a5f4a33824dce82d36bbb96247707986bb771646a4fe","observation_id":"a9188aa6-fa40-4ba2-968b-72c445373802","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.08348","last_updated":"2020-02-27T19:40:21Z","snapshot_observed_at":"2026-08-05T00:23:41.510866Z","submitted_at":"2019-10-18T11:44:59Z","title":"VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.08348","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Varibad: A very good method for bayes-adaptive deep rl via meta-learning","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/1910.08348","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:5d5189043d2989f4d087ae75cdfe6f79072e3d33aa320337d26ab7ab4d366e13","observation_id":"40ae2581-9fbb-4985-ba1e-cffcc7728cb5","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Recurrent world models facilitate policy evolution","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:daef056d5ea1f05b5a995907849028fdbc1b83dc3009337ccbc28dfd3714897c","observation_id":"bc72f299-86a6-4f91-974b-d650da4b97bf","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"A path towards autonomous machine intelligence version 0.9.2, 2022-06-27","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:e957735cabbb1d624f5246508d1eeb14271deaa4cf80d1f7d8fbe800a664311e","observation_id":"02dae480-14c3-4d8f-b110-f7756792684f","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Feng, Yuan Yuan, Hongyuan Su, Nian Li, Nicholas Sukiennik, Fengli Xu, and Yong Li","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:f877260f343122225713154427f23c95adfe52c1b597eacdd9dc074beb0e2006","observation_id":"f258e5c0-d90b-4198-8fe8-39e44f276f80","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"World modeling makes a better planner: Dual preference optimization for embodied task planning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:34cef65649e75b844b5e900eba0cbee20f4af71e0001026cfecaa206a1d90e85","observation_id":"8ef4dd4e-a938-4f05-be5a-96a998163478","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.12090","last_updated":"2026-05-12T13:10:52Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-12T13:10:52Z","title":"World Action Models: The Next Frontier in Embodied AI","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.12090","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"World action models: The next frontier in embodied ai","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2605.12090","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:dc8317288198d2264722aee333272c7b3565725875c37be8fe9f0e6a5da38256","observation_id":"a8472bcc-b993-47b1-8e27-10ebe7917b59","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.13139","last_updated":"2023-12-21T05:34:23Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-20T16:00:43Z","title":"Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.13139","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Unleashing large-scale video generative pre-training for visual robot manipulation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2312.13139","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:b4bfaf7b4be51b3ccbc117154790790800d92372d40af9af72ede78b577de6ae","observation_id":"11491788-8080-4c54-b82a-8f4dc8eea142","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Gr-mg: Leveraging partially- annotated data via multi-modal goal-conditioned policy.IEEE Robotics and Automation Letters, 10:1912–1919, 2024","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:8bcfcb69b1ead17d95e5252d823727d7b9162cfb898e15787bbd5c9ba069f392","observation_id":"05e812df-2eb5-4c04-bb7d-d2b3b462136b","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Cot-vla: Visual chain-of-thought reasoning for vision-language-action models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:923e889de9f1592ec4344ff9ac0cb9a0534f85a616fd703621df5ceffaacf52c","observation_id":"3d642e5d-0b08-4d52-9f4b-dfd9f1040d5e","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.21539","last_updated":"2025-06-26T17:55:40Z","snapshot_observed_at":"2026-08-06T05:50:28.186700Z","submitted_at":"2025-06-26T17:55:40Z","title":"WorldVLA: Towards Autoregressive Action World Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.21539","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Worldvla: T owards autoregressive action world model","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2506.21539","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:410a9cf92c968a059f6a1d736add70ffb9d4607e1490cab700d567fb1121b39f","observation_id":"d421a32d-c2da-4a94-a5c4-a007bd0fc9dd","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:88db282f464d2d6a95fd28845494e359d05ae457a3283fcb8c214034a6388c0a","observation_id":"d166357b-048b-4b27-8576-4eb61fe6db4b","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.01603","last_updated":"2020-03-17T17:10:58Z","snapshot_observed_at":"2026-08-03T15:20:23.515607Z","submitted_at":"2019-12-03T18:57:16Z","title":"Dream to Control: Learning Behaviors by Latent Imagination","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.01603","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Lillicrap, Jimmy Ba, and Mohammad Norouzi","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/1912.01603","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:9ba3c86453d86a2d1d1efd0d06f72ed580ce477b838fa3700a4b6d5de8e726b6","observation_id":"9207b1e0-ddf9-44f6-ae2d-c01e81b25534","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02193","last_updated":"2022-02-12T20:01:53Z","snapshot_observed_at":"2026-08-02T12:02:13.904371Z","submitted_at":"2020-10-05T17:52:14Z","title":"Mastering Atari with Discrete World Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02193","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Lillicrap, Mohammad Norouzi, and Jimmy Ba","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2010.02193","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:f5d5d9907c68f53238c2efbcf791917996514be3b7df1b92e4174126f7024f8a","observation_id":"e1af1b5d-5d00-4573-9b15-51775a892522","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:1e7bea2a560aeb6dae8a7a524c67bc8a6ba2f46037324f3a056f129325de3102","observation_id":"7e91f066-5196-47f3-88e2-f147a4071f11","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-07-12T12:05:57.682386Z","title":"Pašukonis, Jimmy Ba, and Timothy P","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2301.04104","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:5a5a8cf6db046919df9dab8e92f81f5c362bdfbedebd89959ebea238ee7aa064","observation_id":"9576160b-45d9-4763-82b9-8a9e0316e2b9","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.15659","last_updated":"2025-05-21T15:33:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-21T15:33:27Z","title":"FLARE: Robot Learning with Implicit World Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.15659","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Flare: Robot learning with implicit world modeling","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2505.15659","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:7738267f4d5659bef732485ced5713eb54c2daadac51b715defd1d943183ad5b","observation_id":"4574b55d-9165-4fbe-80a4-d7b5ebcf7bb6","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.00111","last_updated":"2023-11-20T05:38:13Z","snapshot_observed_at":"2026-08-05T19:35:53.885395Z","submitted_at":"2023-01-31T21:28:13Z","title":"Learning Universal Policies via Text-Guided Video Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.00111","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Tenenbaum, Dale Schuurmans, and P","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2302.00111","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:39df9f0938977d78af6d850585b8abbf6325b3d2bc66efea767faa8a1a083077","observation_id":"8510c816-092d-4cd2-8017-c403cec1f0a9","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Zettlemoyer, Di- eter Fox, Jan Kautz, Scott Reed, Yuke Zhu, and Linxi Fan","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:71998a9c9a51daca7a746e5bd671c968bb200e7b06ef961ee6d32ad699e31a68","observation_id":"aafaf21b-b51c-4fad-92d5-7d888d9039c3","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15109","last_updated":"2024-12-19T17:52:50Z","snapshot_observed_at":"2026-07-06T20:10:19.704368Z","submitted_at":"2024-12-19T17:52:50Z","title":"Predictive Inverse Dynamics Models are Scalable Learners for Robotic Manipulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15109","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Predictive inverse dynamics models are scalable learners for robotic manipulation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2412.15109","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:8fbdf365c139fceda2063403026fbc474c77f1e48dda61726e3d6e9a916003db","observation_id":"d7c46a45-4884-4290-9bd4-133a15ab2c91","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.11795","last_updated":"2022-06-23T16:01:11Z","snapshot_observed_at":"2026-07-06T13:24:02.173160Z","submitted_at":"2022-06-23T16:01:11Z","title":"Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.11795","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Video pretraining (vpt): Learning to act by watching unlabeled online videos","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2206.11795","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:3d0cefb2e533bc293aea9c5bd687b6b566a5384660744d4912838ba0b275e4c8","observation_id":"de3919ae-247d-4613-8294-24c54513fe49","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.02792","last_updated":"2025-05-23T00:47:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-03T17:38:59Z","title":"Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.02792","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Unified world models: Coupling video and action diffusion for pretraining on large robotic datasets","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2504.02792","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:5572a1b25c3b8867a0a29984c78f737e2746e52022df4f54bab15d4eff75af68","observation_id":"16c0885e-318f-45c7-bc04-a7ca2733857c","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.00200","last_updated":"2025-04-24T20:02:43Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-28T21:38:17Z","title":"Unified Video Action Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.00200","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Unified video action model","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2503.00200","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:e74d82874b059752470cd3012107109e3266953604a319676d77bd5aba7c1770","observation_id":"5555dc63-1091-4ee1-84b3-c38efaa6a296","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"LIBERO: bench- marking knowledge transfer for lifelong robot learning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:b6146d1a2487e6a0f28b4defc4e2a54adfd6c46c9e9b3158ac8efb54f9a39b2e","observation_id":"d82f7f79-ef3c-490e-b713-4d4e372d2351","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.19854","last_updated":"2025-04-28T14:47:34Z","snapshot_observed_at":"2026-08-04T19:02:40.317582Z","submitted_at":"2025-04-28T14:47:34Z","title":"NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.19854","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"Nora: A small open-sourced generalist vision language action model for embodied tasks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2504.19854","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:c0253e88c4d9714b321146ac63089d0e1d35810a245594584cf11fbee29d026b","observation_id":"9724045d-f132-4d00-97ba-85db2827e6fa","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:1bb093f22ff221aab80cc638214d0dd15900c8d7ef2cf10446ec747f6c69ff75","observation_id":"d8dd1ae6-f5b5-48b0-adb1-ccae9916e19d","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.09747","last_updated":"2025-01-16T18:57:04Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-16T18:57:04Z","title":"FAST: Efficient Action Tokenization for Vision-Language-Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.09747","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"FAST : efficient action tokenization for vision-language-action models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2501.09747","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:cd2b1d15a63026314fabc3b852b91712738bcbc013dd9b89ea499e40343d9a91","observation_id":"f3bf165e-ec03-4184-8d9e-a407469b9deb","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.16054","last_updated":"2025-04-22T17:31:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-22T17:31:29Z","title":"$\\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.16054","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2504.16054","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:7b25c4a7f8a1725bb1328eae771b40a90567e6e270893e37cc02e3031e7e713e","observation_id":"0727ca1a-1557-404e-a60d-bff9e890baa1","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13923","last_updated":"2025-02-19T18:00:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-19T18:00:14Z","title":"Qwen2.5-VL Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13923","snapshot_observed_at":"2026-07-12T12:05:57.682386Z","title":"pick up the black bowl next to the plate and place it on the plate","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"cited_paper":"/paper/2502.13923","citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:e358d40b8ffce9807c12d1f4513b3faef3201dbf654d22393057baaa0966b857","observation_id":"e412e9f4-ed6f-4472-b26d-980540d45bd3","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-07-12T12:05:57.682386Z","title":"Put the toy on the box into the basket","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:abb5f2a607372d4e8ce188955c4999a553e656bd200f38a72525bd2f4d39322e","observation_id":"c11c39ad-f0ba-48f8-8b49-118b3895eb22","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Stack the yellow cup onto the red cup","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:231f549b694c00f5111561e4ce539620f99043f5ba9787de7064afb25fb77e6b","observation_id":"403dd563-3d78-4766-a734-332b3132287f","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Lift the basket","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:41430b1ce8e3f81950a818ec177e1ea124aedb065fff9180f089cb9f92d6d0ca","observation_id":"02f44524-143e-4b00-8b43-ecce5a5e912a","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","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":"2026-07-12T12:05:57.682386Z","title":"Pick up the eggplant and place it onto the red plate","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-07-12T12:05:57.682386Z"},"links":{"citing_paper":"/paper/2606.26025"},"observation_digest":"sha256:3e7671f9e023e0ab56279319da0d6497248f95118ce6d12fe088d16b5e296790","observation_id":"d3564db7-25ab-4d11-8630-ba0d299882a5","resolution":{"observed_at":"2026-07-12T12:05:57.682386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.26025","last_updated":"2026-07-03T15:34:07Z","latest_version":3,"primary_category":"cs.RO","snapshot_observed_at":"2026-07-12T12:05:57.041170Z","submitted_at":"2026-06-24T16:53:36Z","title":"In-Context World Modeling for Robotic Control"},"reference_resolution":{"displayed":50,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":48,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":50},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2606.26025."}