{"as_of":"2026-08-08T09:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f524bd1c4acb255bff22147e62500fbd094dc0e16851a9eac3e485053727be83","coverage":[{"denominator":68,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":68,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T03:16:53.139337Z","state":"measured"},{"denominator":70,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":70,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T11:59:27.939168Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T14:52:36.051441Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"cited_work":{"arxiv_id":"2607.13960","doi":null,"metadata_source":"pith","pith_arxiv_id":"2607.13960","snapshot_observed_at":"2026-08-05T14:52:36.051441Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","venue":"cs.RO","work_id":"bef8cd0e-8cf6-4815-aa26-9c684095b60c","year":2026},"citing_paper":{"arxiv_id":"2608.03682","last_updated":"2026-08-05T05:24:32Z","snapshot_observed_at":"2026-08-08T09:10:46.358296Z","submitted_at":"2026-08-04T13:53:48Z","title":"PhyAI: Real-Time Physical AI at the Edge, Scalable Rollouts in the Cloud","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-05T14:52:35.416323Z"},"links":{"cited_paper":"/paper/2607.13960","citing_paper":"/paper/2608.03682"},"observation_digest":"sha256:4823fd333014c1a9abfc7fde4d2adb738abbfe0e9e1d96dca0ba7d005f6ae23b","observation_id":"da858a85-9002-4215-b1cb-ba70cb99ce5c","resolution":{"observed_at":"2026-08-05T14:52:36.054142Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.13960","snapshot_observed_at":"2026-08-06T11:59:27.939168Z","title":"arXiv preprint arXiv:2607.13960 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04996","last_updated":"2026-08-05T16:04:23Z","snapshot_observed_at":"2026-08-08T09:13:49.781656Z","submitted_at":"2026-08-05T16:04:23Z","title":"DreamWAM: Beyond RGB Future Prediction for World Action Models","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T11:59:27.939168Z"},"links":{"cited_paper":"/paper/2607.13960","citing_paper":"/paper/2608.04996"},"observation_digest":"sha256:d5065a82feaa490d4e3f1a591517d9a07e8dc5e6da92264057e9fd7b185a517e","observation_id":"ea8658ba-0d32-45b6-871b-340b39faf206","resolution":{"observed_at":"2026-08-06T11:59:27.939168Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2607.13960/citation-record","integrity":"/paper/2607.13960/integrity","json":"/paper/2607.13960/citation-record.json","paper":"/paper/2607.13960"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.03575","last_updated":"2025-07-09T19:35:31Z","snapshot_observed_at":"2026-08-03T00:21:10.886100Z","submitted_at":"2025-01-07T06:55:50Z","title":"Cosmos World Foundation Model Platform for Physical AI","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.03575","snapshot_observed_at":"2026-08-02T03:16:51.468627Z","title":"Cosmos world foundation model platform for physical ai.arXiv preprint arXiv:2501.03575, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:51.468627Z"},"links":{"cited_paper":"/paper/2501.03575","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:ba869e8b927812c9b3ef8e1df9206b60104561ad0bfbb8fe6da2dd0851ddce09","observation_id":"81faaba5-0763-4ce7-bbe1-9128ae36e20e","resolution":{"observed_at":"2026-08-02T03:16:51.468627Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.02800","last_updated":"2026-06-23T17:33:32Z","snapshot_observed_at":"2026-07-06T23:43:07.940839Z","submitted_at":"2026-06-01T19:12:30Z","title":"Cosmos 3: Omnimodal World Models for Physical AI","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.02800","snapshot_observed_at":"2026-08-02T03:16:51.556914Z","title":"Cosmos 3: Omnimodal world models for physical ai.arXiv preprint arXiv:2606.02800, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:51.556914Z"},"links":{"cited_paper":"/paper/2606.02800","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:01a89a8e04557f536ec63b646934140fdb563d9d83c7d8a23d742633c64fa6d1","observation_id":"1d25b611-2925-4a85-b2b2-b76883d1024e","resolution":{"observed_at":"2026-08-02T03:16:51.556914Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.14492","last_updated":"2025-04-01T21:14:20Z","snapshot_observed_at":"2026-08-07T16:54:09.884104Z","submitted_at":"2025-03-18T17:57:54Z","title":"Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.14492","snapshot_observed_at":"2026-08-02T03:16:51.693644Z","title":"Cosmos-transfer1: Conditional world generation with adaptive multimodal control.arXiv preprint arXiv:2503.14492, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:51.693644Z"},"links":{"cited_paper":"/paper/2503.14492","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:bf3201e2e75fb349b51878450432e49e8f4265712c398e11eb5bc1494148419a","observation_id":"babce225-27ae-4451-b350-a6b723bbe9cf","resolution":{"observed_at":"2026-08-02T03:16:51.693644Z","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":"2026-08-02T03:16:51.899948Z","title":"Motus: A unified latent action world model","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:51.899948Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:2a830e720341cd6a63da26708d51e540625519e2fbf307c14eabbcf3e8dcd4c2","observation_id":"d8e77484-50ff-43b8-9933-97ce411d7847","resolution":{"observed_at":"2026-08-02T03:16:51.899948Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.14734","last_updated":"2025-03-27T02:52:43Z","snapshot_observed_at":"2026-08-02T04:15:31.100670Z","submitted_at":"2025-03-18T21:06:21Z","title":"GR00T N1: An Open Foundation Model for Generalist Humanoid Robots","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.14734","snapshot_observed_at":"2026-08-02T03:16:52.108500Z","title":"Gr00t n1: An open foundation model for generalist humanoid robots.arXiv preprint arXiv:2503.14734, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.108500Z"},"links":{"cited_paper":"/paper/2503.14734","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:5ff3f64c0484a345e802c72ac7d14118fc4cdd6a33be974b7cfa142418b3ea87","observation_id":"5a4b76ed-6203-4d2c-8562-57f4e686a7a2","resolution":{"observed_at":"2026-08-02T03:16:52.108500Z","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":"2026-08-02T03:16:52.225686Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.225686Z"},"links":{"cited_paper":"/paper/2410.24164","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:5d077a77ad03f6b343774bd12561e7540d27f8adc5368bf9cbeb38096ef6462b","observation_id":"60c9e266-4eb8-445b-ae5d-ea01856f42d6","resolution":{"observed_at":"2026-08-02T03:16:52.225686Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06669","last_updated":"2025-08-04T04:50:21Z","snapshot_observed_at":"2026-08-04T23:08:22.516431Z","submitted_at":"2025-03-09T15:40:29Z","title":"AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06669","snapshot_observed_at":"2026-08-02T03:16:52.333915Z","title":"Agibot world colosseo: A large-scale manipulation platform for scalable and intelligent embodied systems.arXiv preprint arXiv:2503.06669, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.333915Z"},"links":{"cited_paper":"/paper/2503.06669","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:e6b01a284d9e396047017241c59f56b17212d8d52b117a3f9edcaad1f267714a","observation_id":"77976c29-3576-485f-8742-f29c62330568","resolution":{"observed_at":"2026-08-02T03:16:52.333915Z","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":"2026-08-07T12:15:14.265779Z","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":"2026-08-02T03:16:52.499150Z","title":"Worldvla: Towards autoregressive action world model.arXiv preprint arXiv:2506.21539, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.499150Z"},"links":{"cited_paper":"/paper/2506.21539","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:f6bef15e6d88cf8eadd149defd292e638b0777029a14d7e01926000f31f124fb","observation_id":"8f28fe47-9861-4ba3-b6f8-e716e3451c1b","resolution":{"observed_at":"2026-08-02T03:16:52.499150Z","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":"2026-08-02T03:16:52.575487Z","title":"Lawam: Latent world action models for efficient dynamics-aware robot policies.arXiv preprint arXiv:2606.15768, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.575487Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:dc6f86441bb8240b5218c8e118b4e098ca47fbce3420bd47723c132586b03424","observation_id":"80e94dfd-9b4c-4b44-8e76-1396f1a68e56","resolution":{"observed_at":"2026-08-02T03:16:52.575487Z","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":"2026-08-02T03:16:52.653824Z","title":"Unimax: Fairer and more effective language sampling for large-scale multilingual pretraining","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.653824Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:d5de8c402c3dff6e7230debd3d0fef7dc32a54f6ed5833dbdc19240ebd2cc5bf","observation_id":"5cdc9b33-c63c-4668-bd50-fa32edd63f59","resolution":{"observed_at":"2026-08-02T03:16:52.653824Z","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":"2026-08-02T03:16:52.735830Z","title":"Emma: Generalizing real-world robot manipulation via generative visual transfer.arXiv preprint arXiv:2509.22407, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.735830Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:7ab26ce81dc02604933695c7f7d974bb78af7718707fe6b93622c7eeef34759e","observation_id":"c07ed61b-df65-4235-b0ff-9d5e146efd88","resolution":{"observed_at":"2026-08-02T03:16:52.735830Z","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":"2026-08-02T03:16:52.800361Z","title":"Learning universal policies via text-guided video generation.Advances in neural information processing systems, 36:9156–9172, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.800361Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:e406f6c45b9f8e7e3efd60a6d7afb3ce108d6a9652f8efcb960023c74537502b","observation_id":"fa5e265c-d13c-4a96-b1bf-b72221d64e80","resolution":{"observed_at":"2026-08-02T03:16:52.800361Z","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":"2026-08-02T03:16:52.871383Z","title":"Scaling rectified flow transformers for high-resolution image synthesis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.871383Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:b85b4606a43c7dbe3737d99bb6a49dd57ce271ac75926984c67702d46bce5f6e","observation_id":"82a573c0-c1bb-4763-9889-8c269e849b00","resolution":{"observed_at":"2026-08-02T03:16:52.871383Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.14759","last_updated":"2025-11-19T04:34:49Z","snapshot_observed_at":"2026-07-06T22:36:13.287872Z","submitted_at":"2025-11-18T18:58:55Z","title":"$\\pi^{*}_{0.6}$: a VLA That Learns From Experience","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.14759","snapshot_observed_at":"2026-08-02T03:16:52.931575Z","title":"arXiv preprint arXiv:2511.14759, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.931575Z"},"links":{"cited_paper":"/paper/2511.14759","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:a3142baeebfe627bfe4f17c23a8e557f524e07d4144b76b91c967b44a3484e87","observation_id":"f5994737-809d-4e45-ad7e-2d7e255c052e","resolution":{"observed_at":"2026-08-02T03:16:52.931575Z","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":"2026-08-02T03:16:52.979043Z","title":"2, 8, 9, 10","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.979043Z"},"links":{"cited_paper":"/paper/2504.16054","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:097b7a8fc1a13673893ce854c03acd0fa962257ea310a7bcf53a6bce1b893981","observation_id":"2468ae23-d88c-4741-9bbd-173d0461a61f","resolution":{"observed_at":"2026-08-02T03:16:52.979043Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.15483","last_updated":"2026-04-24T23:18:28Z","snapshot_observed_at":"2026-08-05T18:18:04.172934Z","submitted_at":"2026-04-16T19:18:07Z","title":"${\\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.15483","snapshot_observed_at":"2026-08-02T03:16:52.982239Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.982239Z"},"links":{"cited_paper":"/paper/2604.15483","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:1eeca4d2773e6b2940a2154dfc45a988ee951569b9f45e6aa044d2c813d2aa11","observation_id":"ba7bc83f-654d-4bc5-9c77-c9215aa66c3f","resolution":{"observed_at":"2026-08-02T03:16:52.982239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.13977","last_updated":"2026-06-27T16:11:05Z","snapshot_observed_at":"2026-08-02T23:23:50.481908Z","submitted_at":"2026-02-15T03:48:20Z","title":"WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.13977","snapshot_observed_at":"2026-08-02T03:16:52.985410Z","title":"Wovr: World models as reliable simulators for post-training vla policies with rl.arXiv preprint arXiv:2602.13977, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.985410Z"},"links":{"cited_paper":"/paper/2602.13977","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:b96e78538873913e379ec5550034ededeb920761abb90cfd590b5160516cacd2","observation_id":"ab16b418-1055-4637-92fe-4f92feb62da8","resolution":{"observed_at":"2026-08-02T03:16:52.985410Z","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":"2026-08-02T03:16:52.988893Z","title":"autoresearch, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.988893Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:9eb0a48d369fe6bba700bafff2a2e35d17058213bb7c8eef428e2e6b69355922","observation_id":"22e95b37-6ee4-43eb-a173-e1b20b5f41f5","resolution":{"observed_at":"2026-08-02T03:16:52.988893Z","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":"2026-08-02T03:16:52.991539Z","title":"Freeaction: Training-free techniques for enhanced fidelity of trajectory-to-video generation.arXiv preprint arXiv:2509.24241, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.991539Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:4abc691d5c369de3a8a3bd0a5cdc71257001a40fa43490aab5e68cb6b6274f1e","observation_id":"5e11643f-9ba0-43a2-b39f-4f0f9ee238ff","resolution":{"observed_at":"2026-08-02T03:16:52.991539Z","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":"2026-08-02T03:16:52.994236Z","title":"A path towards autonomous machine intelligence version 0.9","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.994236Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:b096db14ccc2b460381f224df56f11f2f692b7f0be4d2f48ef69e9a3fea02e96","observation_id":"045f3ec5-38d5-4e8d-a152-7c4839b664f7","resolution":{"observed_at":"2026-08-02T03:16:52.994236Z","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":"2026-08-02T03:16:52.997448Z","title":"Mimicdreamer: Aligning human and robot demonstrations for scalable vla training.arXiv preprint arXiv:2509.22199, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:52.997448Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:2537ac9b466b169969f3065d2ce0c97ffabe1224404527f4f4d8c5b6922f2428","observation_id":"4e7d7400-9f16-4fb5-a35b-1f1e02d55093","resolution":{"observed_at":"2026-08-02T03:16:52.997448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.21998","last_updated":"2026-03-22T15:37:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-01-29T17:07:43Z","title":"Causal World Modeling for Robot Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.21998","snapshot_observed_at":"2026-08-02T03:16:53.000407Z","title":"Causal world modeling for robot control.arXiv preprint arXiv:2601.21998, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.000407Z"},"links":{"cited_paper":"/paper/2601.21998","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:d318777da9b3497d564c2c2830119b0b0b2e39d83c3a4ba779b5b316329b2f3c","observation_id":"f7463fcd-5db7-4323-b88e-2d205fdac65e","resolution":{"observed_at":"2026-08-02T03:16:53.000407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.02747","last_updated":"2023-02-08T15:46:05Z","snapshot_observed_at":"2026-08-02T18:24:58.914589Z","submitted_at":"2022-10-06T08:32:20Z","title":"Flow Matching for Generative Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.02747","snapshot_observed_at":"2026-08-02T03:16:53.003738Z","title":"Flow matching for generative modeling.arXiv preprint arXiv:2210.02747, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.003738Z"},"links":{"cited_paper":"/paper/2210.02747","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:b5b014c495661f864e25de72dec4b8e9c4cdc48276680be8de71200ed24a80c4","observation_id":"6515e2db-737a-42b4-901d-1e096fb72f73","resolution":{"observed_at":"2026-08-02T03:16:53.003738Z","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":"2026-08-02T03:16:53.007000Z","title":"Timestep embedding tells: It’s time to cache for video diffusion model","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.007000Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:8d2bb8f85894f024c22b3cfd32e01f0957ac227855c540a5c8023cc51347520b","observation_id":"ac94fcc8-2632-403f-8649-9758b09b65dd","resolution":{"observed_at":"2026-08-02T03:16:53.007000Z","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":"2026-08-02T03:16:53.009824Z","title":"Robotransfer: Controllable geometry-consistent video diffusion for manipulation policy transfer","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.009824Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:bc1f2cfe56e3705d64c96fc325507fd2d1072ddb0f13c1f3570dbecbaa1cbf42","observation_id":"222a2b9b-792b-42a4-8523-e7d1b5fdc4b2","resolution":{"observed_at":"2026-08-02T03:16:53.009824Z","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":"2026-08-02T03:16:53.013067Z","title":"Rdt-1b: a diffusion foundation model for bimanual manipulation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.013067Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:3e4bcefa67c191f1b2c90fe064d69c75da1e9a83a336e08e58c6c0a6400ef69f","observation_id":"c7cf7d4b-ef9f-416b-8dd3-c10caa3b1530","resolution":{"observed_at":"2026-08-02T03:16:53.013067Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.00078","last_updated":"2026-04-30T14:16:15Z","snapshot_observed_at":"2026-07-06T23:13:33.799847Z","submitted_at":"2026-04-30T14:16:15Z","title":"Being-H0.7: A Latent World-Action Model from Egocentric Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.00078","snapshot_observed_at":"2026-08-02T03:16:53.016000Z","title":"Being-h0","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.016000Z"},"links":{"cited_paper":"/paper/2605.00078","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:42729561fe1b7044b65a6ebf43608fc8fd915100896c5787751489c018ea45e5","observation_id":"e65b3ed6-65b7-459c-be83-84e080132ed3","resolution":{"observed_at":"2026-08-02T03:16:53.016000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.08168","last_updated":"2026-04-09T12:28:14Z","snapshot_observed_at":"2026-07-06T22:57:18.202215Z","submitted_at":"2026-04-09T12:28:14Z","title":"ViVa: A Video-Generative Value Model for Robot Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.08168","snapshot_observed_at":"2026-08-02T03:16:53.019586Z","title":"Viva: A video-generative value model for robot reinforcement learning.arXiv preprint arXiv:2604.08168, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.019586Z"},"links":{"cited_paper":"/paper/2604.08168","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:f1db019fb7064cec4e8ac8ebcce17bdc4ca1b6c7f7cad38f377ae9850f966b3e","observation_id":"159fbbe0-8ae9-4750-8623-802e11e201f7","resolution":{"observed_at":"2026-08-02T03:16:53.019586Z","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":"2026-08-02T03:16:53.022701Z","title":"Dit4dit: Jointly modeling video dynamics and actions for generalizable robot control.arXiv preprint arXiv:2603.10448,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.022701Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:623a106664a71663025d294bfcb19c7b1ff7d3813919d39fe25b6a8b8ab482f9","observation_id":"84001fe0-c77a-4c4b-9298-2e1b46168bff","resolution":{"observed_at":"2026-08-02T03:16:53.022701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.08170","last_updated":"2025-08-21T11:45:55Z","snapshot_observed_at":"2026-08-07T05:30:28.404314Z","submitted_at":"2025-08-11T16:45:55Z","title":"ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.08170","snapshot_observed_at":"2026-08-02T03:16:53.025755Z","title":"Recondreamer-rl: Enhancing reinforcement learning via diffusion-based scene reconstruction.arXiv preprint arXiv:2508.08170, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.025755Z"},"links":{"cited_paper":"/paper/2508.08170","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:715037e92372c19bdd9f0c4438a25634fd5d8025a91d73f66ab44d342f16aa92","observation_id":"59813907-6f9a-448b-bee4-86275d0e5643","resolution":{"observed_at":"2026-08-02T03:16:53.025755Z","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":"2026-08-02T03:16:53.029636Z","title":"Swiftvla: Unlocking spatiotemporal dynamics for lightweight vla models at minimal overhead","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.029636Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:00fd4e4922e3d1db3c0cd3f23ee90bedae67db911fdd1abdf5e4390e1558943b","observation_id":"7f33f67e-8385-4438-a9f9-1609f7d39d74","resolution":{"observed_at":"2026-08-02T03:16:53.029636Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2512.15692","last_updated":"2025-12-19T18:30:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-17T18:47:31Z","title":"mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2512.15692","snapshot_observed_at":"2026-08-02T03:16:53.032905Z","title":"mimic- video: Video-action models for generalizable robot control beyond vlas.arXiv preprint arXiv:2512.15692,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.032905Z"},"links":{"cited_paper":"/paper/2512.15692","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:8cfd65f521f0e36c30fa5af00f5abf2568500ce6bafcb8eebfb0b40ea6568685","observation_id":"41af6501-2b9c-4a8f-8cfe-8d0f919a750f","resolution":{"observed_at":"2026-08-02T03:16:53.032905Z","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":"2026-08-02T03:16:53.036196Z","title":"Videovla: Video generators can be generalizable robot manipulators.Advances in neural information processing systems, 38:95597–95621, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.036196Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:afa485131ad1f688d3d5aaf1949d94c5ead7b517fec672972509d8200d7aff45","observation_id":"30ece4c3-f35d-461f-afc8-a7b7f14a1335","resolution":{"observed_at":"2026-08-02T03:16:53.036196Z","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":"2026-08-02T03:16:53.039159Z","title":"World guidance: World modeling in condition space for action generation.arXiv preprint arXiv:2602.22010, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.039159Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:82ff4cfa3ccef7581b724947721e628a3f7017d3601331cc85bec592d0d18d9a","observation_id":"ea5750a5-3377-49a2-824d-8ff8f7b4e8ad","resolution":{"observed_at":"2026-08-02T03:16:53.039159Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.12768","last_updated":"2026-05-06T08:19:11Z","snapshot_observed_at":"2026-08-03T01:37:13.706745Z","submitted_at":"2025-07-17T03:48:57Z","title":"AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.12768","snapshot_observed_at":"2026-08-02T03:16:53.041846Z","title":"Anypos: Automated task-agnostic actions for bimanual manipulation.arXiv preprint arXiv:2507.12768,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.041846Z"},"links":{"cited_paper":"/paper/2507.12768","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:45756fba38c7f5b978f11469a62bb0871e7fefd82c9c4efcb4f2f453cef1c8e8","observation_id":"c3adf8a5-f273-422d-af66-69b6facc424a","resolution":{"observed_at":"2026-08-02T03:16:53.041846Z","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":"2026-08-02T03:16:53.045406Z","title":"Gigabrain-0: A world model-powered vision-language-action model.arXiv preprint arXiv:2510.19430, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.045406Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:1cf64d8a35db0d25abb1a7088b3482f1eed4014fd6ad97181ce0d5ebe1e8e8a6","observation_id":"81fcf3f0-f34e-41e1-a23a-8b16f32775ea","resolution":{"observed_at":"2026-08-02T03:16:53.045406Z","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":"2026-08-02T03:16:53.048225Z","title":"Gigabrain-0.5 m*: a vla that learns from world model-based reinforcement learning","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.048225Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:9d4e2591bb4ca4e19c9ce3f2452fd2ad4f56ff167a916b9751590881ecfa7977","observation_id":"7cbb8625-d910-46b4-8299-afe91d875d3d","resolution":{"observed_at":"2026-08-02T03:16:53.048225Z","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":"2026-08-02T03:16:53.051352Z","title":"Gigaworld-0: World models as data engine to empower embodied ai","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.051352Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:080f0b6618a1a909c6addb87c5172ca3042dd103cbcd58c81b84a4b677c0c286","observation_id":"db5c560a-1848-43f8-bfd4-a6672ac7135f","resolution":{"observed_at":"2026-08-02T03:16:53.051352Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2607.02642","last_updated":"2026-07-02T17:02:43Z","snapshot_observed_at":"2026-08-03T12:39:47.539491Z","submitted_at":"2026-07-02T17:02:43Z","title":"GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.02642","snapshot_observed_at":"2026-08-02T03:16:53.054370Z","title":"Gigaworld-1: A roadmap to build world models for robot policy evaluation","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.054370Z"},"links":{"cited_paper":"/paper/2607.02642","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:15a019da0ce7b4fdac4402da4bea5c8411a760d9bf44c7e53294bdb0fb13a949","observation_id":"828fb644-3e25-4b96-acba-6bdf3bb4c945","resolution":{"observed_at":"2026-08-02T03:16:53.054370Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.27792","last_updated":"2026-07-15T07:09:44Z","snapshot_observed_at":"2026-08-02T15:15:08.869109Z","submitted_at":"2026-04-30T12:34:44Z","title":"Motubrain: An Advanced World Action Model for Robot Control","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.27792","snapshot_observed_at":"2026-08-02T03:16:53.057505Z","title":"Motubrain: An advanced world action model for robot control.arXiv preprint arXiv:2604.27792, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.057505Z"},"links":{"cited_paper":"/paper/2604.27792","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:0488f75a875363eaec5d5800ec458451bed6bf9b0d09aca7a310523140adb6af","observation_id":"ca3b4035-31c5-4568-997f-bb7713de020d","resolution":{"observed_at":"2026-08-02T03:16:53.057505Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.20314","last_updated":"2025-04-19T02:22:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-26T08:25:43Z","title":"Wan: Open and Advanced Large-Scale Video Generative Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.20314","snapshot_observed_at":"2026-08-02T03:16:53.060585Z","title":"Wan: Open and advanced large-scale video generative models.arXiv preprint arXiv:2503.20314, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.060585Z"},"links":{"cited_paper":"/paper/2503.20314","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:616f1aebe600cef50d39525b3d9503278f9a3c7ff164a55e7294ab75b6394548","observation_id":"99d73420-2d6b-4919-8202-08f2e4b6ac0f","resolution":{"observed_at":"2026-08-02T03:16:53.060585Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.05198","last_updated":"2025-07-07T16:58:17Z","snapshot_observed_at":"2026-08-07T04:00:02.770729Z","submitted_at":"2025-07-07T16:58:17Z","title":"EmbodieDreamer: Advancing Real2Sim2Real Transfer for Policy Training via Embodied World Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.05198","snapshot_observed_at":"2026-08-02T03:16:53.063727Z","title":"Embodiedreamer: Advancing real2sim2real transfer for policy training via embodied world modeling.arXiv preprint arXiv:2507.05198, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.063727Z"},"links":{"cited_paper":"/paper/2507.05198","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:212bf40773e4cf450ee88d1dd71731f050b280d9c221a290084a241d58072332","observation_id":"5b1d2416-3b42-4457-8444-9e3082bb482e","resolution":{"observed_at":"2026-08-02T03:16:53.063727Z","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":"2026-08-02T03:16:53.066630Z","title":"Humandreamer-x: Photorealistic single-image human avatars reconstruction via gaussian restoration.arXiv preprint arXiv:2504.03536, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.066630Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:72d7cc60d14c78bba00b8c27a4bfbf477a5e799305bc44e5761c458fad929c83","observation_id":"bc282f01-ba83-4c0a-8d79-19f53ef1c47c","resolution":{"observed_at":"2026-08-02T03:16:53.066630Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.07882","last_updated":"2026-04-09T06:51:14Z","snapshot_observed_at":"2026-07-06T22:57:05.146373Z","submitted_at":"2026-04-09T06:51:14Z","title":"ReconPhys: Reconstruct Appearance and Physical Attributes from Single Video","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.07882","snapshot_observed_at":"2026-08-02T03:16:53.069617Z","title":"Reconphys: Reconstruct appearance and physical attributes from single video.arXiv preprint arXiv:2604.07882, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.069617Z"},"links":{"cited_paper":"/paper/2604.07882","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:fac591501ce287ef61043c5c17791ce1b4d61324a5042950c3521b2e3887807a","observation_id":"65930336-6fa1-4fb0-845b-e68251452a6a","resolution":{"observed_at":"2026-08-02T03:16:53.069617Z","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":"2026-08-02T03:16:53.072452Z","title":"Drivedreamer: Towards real-world-drive world models for autonomous driving","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.072452Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:e7bbaba48e26b702c6328a8b3f58e0ba9f5a7cc1fb70be166dd4ebac59a2cfbc","observation_id":"38d97754-3db9-429b-80f5-58f896e35cbb","resolution":{"observed_at":"2026-08-02T03:16:53.072452Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.09985","last_updated":"2024-01-18T14:01:20Z","snapshot_observed_at":"2026-08-07T06:47:36.460071Z","submitted_at":"2024-01-18T14:01:20Z","title":"WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.09985","snapshot_observed_at":"2026-08-02T03:16:53.075596Z","title":"Worlddreamer: Towards general world models for video generation via predicting masked tokens.arXiv preprint arXiv:2401.09985, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.075596Z"},"links":{"cited_paper":"/paper/2401.09985","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:7d51170a1271256041a9b9f7230f73526e2d09d8908cccfce53e0a76b49a758f","observation_id":"0f539b69-ceb2-4482-bd59-174de125e61f","resolution":{"observed_at":"2026-08-02T03:16:53.075596Z","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":"2026-08-02T03:16:53.078807Z","title":"Egovid-5m: A large-scale video-action dataset for egocentric videos generation.Advances in Neural Information Processing Systems, 38, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.078807Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:39ce7b666c1d328f26ea0b077306202d658231955221cbd892c167c9721b63e4","observation_id":"2dfd3ecc-55a7-4184-9968-c72f9945879b","resolution":{"observed_at":"2026-08-02T03:16:53.078807Z","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":"2026-08-02T03:16:53.081537Z","title":"Unleashing large-scale video generative pre-training for visual robot manipulation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.081537Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:f03b746c0fa3d996fc9d721c857039f2e1389484a4bca1bd203fad2608119cf1","observation_id":"c951ba54-fe9f-4c5e-b278-e6954a80343d","resolution":{"observed_at":"2026-08-02T03:16:53.081537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.13877","last_updated":"2025-05-27T01:46:53Z","snapshot_observed_at":"2026-07-06T20:09:14.917734Z","submitted_at":"2024-12-18T14:17:16Z","title":"RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13877","snapshot_observed_at":"2026-08-02T03:16:53.084538Z","title":"Robomind: Benchmark on multi-embodiment intelligence normative data for robot manipulation.arXiv preprint arXiv:2412.13877, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.084538Z"},"links":{"cited_paper":"/paper/2412.13877","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:16c8359bdc24b8cbcedff35533350e8bc0f9b79d72741cef85eb193da662ffc6","observation_id":"07de1111-fb3f-4882-8fe0-9c06efbab001","resolution":{"observed_at":"2026-08-02T03:16:53.084538Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.18692","last_updated":"2026-02-26T03:30:01Z","snapshot_observed_at":"2026-08-03T03:53:18.422734Z","submitted_at":"2026-01-26T17:08:04Z","title":"A Pragmatic VLA Foundation Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.18692","snapshot_observed_at":"2026-08-02T03:16:53.087819Z","title":"A pragmatic vla foundation model.arXiv preprint arXiv:2601.18692, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.087819Z"},"links":{"cited_paper":"/paper/2601.18692","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:d5e6155f39c3e874c15d16d667a498450a3cbffbc6deebf9b940477148ab16fb","observation_id":"acc6125a-cb03-47c6-8bec-9d1dbbd6b11e","resolution":{"observed_at":"2026-08-02T03:16:53.087819Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.09455","last_updated":"2024-06-12T18:55:51Z","snapshot_observed_at":"2026-08-08T08:58:45.984697Z","submitted_at":"2024-06-12T18:55:51Z","title":"Pandora: Towards General World Model with Natural Language Actions and Video States","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.09455","snapshot_observed_at":"2026-08-02T03:16:53.090709Z","title":"Pandora: Towards general world model with natural language actions and video states.arXiv preprint arXiv:2406.09455, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.090709Z"},"links":{"cited_paper":"/paper/2406.09455","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:90ea33c7cc7343608f69bba3180e5c4872b1b61d8d330e69fd5ac3092f07c8f5","observation_id":"62a1fd9c-bbcc-4b8a-a679-944154b2e172","resolution":{"observed_at":"2026-08-02T03:16:53.090709Z","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":"2026-08-02T03:16:53.093687Z","title":"S-vam: Shortcut video-action model by self-distilling geometric and semantic foresight.arXiv preprint arXiv:2603.16195, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.093687Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:9a446222e1603079d40a70389ebac4c33f674cb965b008d22369b750fe63af4c","observation_id":"6c82ef15-1974-4bfc-b7f2-e010d10b3570","resolution":{"observed_at":"2026-08-02T03:16:53.093687Z","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":"2026-08-02T03:16:53.096363Z","title":"Vla-r1: Enhancing reasoning in vision-language-action models.arXiv preprint arXiv:2510.01623, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.096363Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:b9388accd2337b5a7c1671bea75fd281db1585cc775c0e4b59fa7a13ef96a724","observation_id":"8f8d4b39-a49b-4f45-84c4-3dd93d6a9a55","resolution":{"observed_at":"2026-08-02T03:16:53.096363Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2607.04265","last_updated":"2026-07-05T12:24:14Z","snapshot_observed_at":"2026-08-03T14:46:31.336834Z","submitted_at":"2026-07-05T12:24:14Z","title":"HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.04265","snapshot_observed_at":"2026-08-02T03:16:53.099063Z","title":"Halo-wa: Hybrid-attention latent-guided online reinforcement learning for world-action models.arXiv preprint arXiv:2607.04265, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.099063Z"},"links":{"cited_paper":"/paper/2607.04265","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:e8eaaef2a3220204ba29567a576e1e109da61883aa4163ddfdb6854b2e24a21e","observation_id":"0e2be43d-316a-4b64-bad9-c41302c51ee2","resolution":{"observed_at":"2026-08-02T03:16:53.099063Z","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":"2026-08-02T03:16:53.101931Z","title":"Gigaworld-policy: An efficient action-centered world–action model.arXiv preprint arXiv:2603.17240, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.101931Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:fd9d266c96f23943f9db52542613ef5c8a9a64be783155e381b676fac176f209","observation_id":"b487279f-f53f-4c5c-b432-2b1d050e526d","resolution":{"observed_at":"2026-08-02T03:16:53.101931Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.15922","last_updated":"2026-02-17T15:04:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-02-17T15:04:02Z","title":"World Action Models are Zero-shot Policies","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.15922","snapshot_observed_at":"2026-08-02T03:16:53.104585Z","title":"World action models are zero-shot policies.arXiv preprint arXiv:2602.15922, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.104585Z"},"links":{"cited_paper":"/paper/2602.15922","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:2acd614f7418b7982332b4aae3d14f1056e741025b8c41ea248bead0d53a0a10","observation_id":"777d1df7-f0ff-4dba-b766-65dada147621","resolution":{"observed_at":"2026-08-02T03:16:53.104585Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2603.16666","last_updated":"2026-03-23T05:41:14Z","snapshot_observed_at":"2026-07-06T22:49:23.750692Z","submitted_at":"2026-03-17T15:33:43Z","title":"Fast-WAM: Do World Action Models Need Test-time Future Imagination?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2603.16666","snapshot_observed_at":"2026-08-02T03:16:53.107666Z","title":"Fast-wam: Do world action models need test-time future imagination?arXiv preprint arXiv:2603.16666, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.107666Z"},"links":{"cited_paper":"/paper/2603.16666","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:8c11d701bfaa667e6fb173748d0cbd539c47dfeba6afd6be893a376d3c4b37ed","observation_id":"8e586a8d-d2b7-4bc0-a9a8-ac2f7f8195a1","resolution":{"observed_at":"2026-08-02T03:16:53.107666Z","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":"2026-08-02T03:16:53.110746Z","title":"Igniting vlms toward the embodied space.arXiv preprint arXiv:2509.11766, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.110746Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:7476f4b10c4f77c4522cb7bde709a509ca9c5815e7232a1c93b28069d3f5df40","observation_id":"7b72f99b-1fd9-434e-aefa-3bba96e397d8","resolution":{"observed_at":"2026-08-02T03:16:53.110746Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.17030","last_updated":"2026-06-17T13:54:57Z","snapshot_observed_at":"2026-08-01T21:48:31.832288Z","submitted_at":"2026-06-15T17:52:31Z","title":"Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.17030","snapshot_observed_at":"2026-08-02T03:16:53.113554Z","title":"Qwen-robotworld technical report: Unifying embodied world modeling through language-conditioned video generation.arXiv preprint arXiv:2606.17030, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.113554Z"},"links":{"cited_paper":"/paper/2606.17030","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:a6590ba6fd6f502382ff152264998b41e6bd3e0c7c7af9f9bf61cb870c8a7e2c","observation_id":"c9bd6962-2532-4ba5-b804-06f33509fbf1","resolution":{"observed_at":"2026-08-02T03:16:53.113554Z","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":"2026-08-02T03:16:53.116430Z","title":"Drivedreamer4d: World models are effective data machines for 4d driving scene representation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.116430Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:d2827506b8dd9d1735e461b131cb7a7fd1cf15d212f29316d237ef46d20af5f7","observation_id":"17dce28c-202d-4eb2-9602-11fbc2fd2ff2","resolution":{"observed_at":"2026-08-02T03:16:53.116430Z","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":"2026-08-02T03:16:53.119201Z","title":"Recondreamer++: Harmonizing generative and reconstructive models for driving scene representation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.119201Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:4685a520d12479e7a8d60251f573a4bd92612b8bfb27abb02ed10dfac8656b4d","observation_id":"600fa4ed-481e-44d1-830a-5dda5b12f0a1","resolution":{"observed_at":"2026-08-02T03:16:53.119201Z","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":"2026-08-02T03:16:53.121822Z","title":"Drivedreamer-2: Llm-enhanced world models for diverse driving video generation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.121822Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:eb2e37254aa653edbb80ee61d6e5d8a848a0e7b6c7cfdd1a3b9df6f29575bbb6","observation_id":"2c8cc1bc-e571-4309-b386-c466cf81b9d0","resolution":{"observed_at":"2026-08-02T03:16:53.121822Z","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":"2026-08-02T03:16:53.124492Z","title":"Unidrivedreamer: A single-stage multimodal world model for autonomous driving.arXiv preprint arXiv:2602.02002, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.124492Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:5cd10d6275181b2f12f99a8a6e7ec6e43b69e06d951ad314627274ebb34955db","observation_id":"86ba7ecb-287c-494c-96b9-57ef67030699","resolution":{"observed_at":"2026-08-02T03:16:53.124492Z","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":"2026-08-02T03:16:53.127533Z","title":"Robodreamer: learning compositional world models for robot imagination","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.127533Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:2a820e2538ec68c4650fc0f11df67f7a49a8db7218630308b8af4e6f10aa0b47","observation_id":"0067d6ff-ed34-47cd-974c-ce5b0cfb1df7","resolution":{"observed_at":"2026-08-02T03:16:53.127533Z","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":"2026-08-02T03:16:53.130193Z","title":"Drivedreamer-policy: A geometry-grounded world-action model for unified generation and planning.arXiv preprint arXiv:2604.01765, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.130193Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:4f3f29a5af1e6008be2c418152ceccf07e97e340a3a748fe9f5ab59bd7b238cd","observation_id":"fc1fda4b-8a03-457a-adac-fc12d0523c6c","resolution":{"observed_at":"2026-08-02T03:16:53.130193Z","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":"2026-08-02T03:16:53.133370Z","title":"Unified world models: Coupling video and action diffusion for pretraining on large robotic datasets.arXiv preprint arXiv:2504.02792, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.133370Z"},"links":{"cited_paper":"/paper/2504.02792","citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:e529bdf41b340408aaf64dd072a7684fd5bce331a83bc2cdf23991f83fa9fe36","observation_id":"327c4baf-ae85-4e77-b149-0a71b3414ab9","resolution":{"observed_at":"2026-08-02T03:16:53.133370Z","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":"2026-08-02T03:16:53.136626Z","title":"Aether: Geometric-aware unified world modeling","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.136626Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:34fad881308dba1fed5b9b04f59142f02aa078f66232206e6d81422d2006bc48","observation_id":"2818f538-239b-43af-9ef7-d7f8fb425105","resolution":{"observed_at":"2026-08-02T03:16:53.136626Z","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":"2026-08-02T03:16:53.139337Z","title":"Is sora a world simulator? a comprehensive survey on general world models and beyond.arXiv preprint arXiv:2405.03520, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","version":3},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-02T03:16:53.139337Z"},"links":{"citing_paper":"/paper/2607.13960"},"observation_digest":"sha256:d3102362048379806428e67f040e8a976adbbab05db9a4afb696d3a9fdd92ca7","observation_id":"222db407-7b16-42ae-b6bc-f76c00cbccde","resolution":{"observed_at":"2026-08-02T03:16:53.139337Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.13960","last_updated":"2026-07-17T13:39:37Z","latest_version":3,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-03T18:30:12.569959Z","submitted_at":"2026-07-15T15:46:42Z","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch"},"reference_resolution":{"displayed":68,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":68,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":68},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:2607.13960."}