{"as_of":"2026-08-10T07:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8e33ff5976fec3e9bb38e4923f53fc44037ca51b9b2536c085912ae6d81e5620","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:03:14.996741Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-02T20:27:22.783676Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":"2406.10981","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-07-02T20:27:22.783676Z","title":"Vid-gpt: Introducing gpt-style autoregressive generation in video diffusion models","venue":null,"work_id":"adee2c01-4d22-4677-93f9-1dee5e6d7406","year":2024},"citing_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},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-13T17:50:29.675358Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2503.00200"},"observation_digest":"sha256:7cfc87d3d65cd1048c5ce4e819ac4ddc180c85a79901d82eea1fb0b6aa3ef7f2","observation_id":"6b526176-ebda-4030-9f11-a1a7e8a1767a","resolution":{"observed_at":"2026-05-13T17:50:29.733860Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-08-07T14:03:14.996741Z","title":"Vid-gpt: Introducing gpt-style autoregres- sive generation in video diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20171","last_updated":"2025-05-26T16:12:41Z","snapshot_observed_at":"2026-08-07T13:55:36.207486Z","submitted_at":"2025-05-26T16:12:41Z","title":"Long-Context State-Space Video World Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T14:03:14.996741Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2505.20171"},"observation_digest":"sha256:53133074111f891f12b94ac85b0bd15dd2f716d000896b3a108e2a3a08200d71","observation_id":"a96975dc-4aeb-444e-9db7-10a4edf6f0c6","resolution":{"observed_at":"2026-08-07T14:03:14.996741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-08-07T10:28:37.579879Z","title":"Vid-gpt: Introducing gpt-style autoregressive generation in video diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.05284","last_updated":"2025-06-05T17:42:34Z","snapshot_observed_at":"2026-08-07T11:02:24.060549Z","submitted_at":"2025-06-05T17:42:34Z","title":"Video World Models with Long-term Spatial Memory","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T10:28:37.579879Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2506.05284"},"observation_digest":"sha256:e82c16fc08c28af5ed0ea48b52dd197f4d9250ea8ff898edf5da667e43f16bc4","observation_id":"9fe474e8-794c-45fa-b6ea-aea7aff9f106","resolution":{"observed_at":"2026-08-07T10:28:37.579879Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-08-06T23:35:01.995520Z","title":"Vid-gpt: Introducing gpt-style autoregres- sive generation in video diffusion models.arXiv preprint arXiv:2406.10981, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.17201","last_updated":"2025-06-20T17:50:37Z","snapshot_observed_at":"2026-08-06T23:28:21.347321Z","submitted_at":"2025-06-20T17:50:37Z","title":"Hunyuan-GameCraft: High-dynamic Interactive Game Video Generation with Hybrid History Condition","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:01.995520Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2506.17201"},"observation_digest":"sha256:23095f518219573fc7d9e9d1d476c641f16f69480b33a983e616f1983fb642ce","observation_id":"7a8cc20c-fdd8-473c-91b6-84cb02db06b7","resolution":{"observed_at":"2026-08-06T23:35:01.995520Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-08-06T16:39:22.906941Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12952","last_updated":"2025-07-17T09:46:43Z","snapshot_observed_at":"2026-08-07T11:02:23.505503Z","submitted_at":"2025-07-17T09:46:43Z","title":"LoViC: Efficient Long Video Generation with Context Compression","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T16:39:22.906941Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2507.12952"},"observation_digest":"sha256:cc351cd826894b6b9b70d4c78e28ccb02a06e1fd78ca64fb40b2eac94e6045e2","observation_id":"b033239e-d88d-4a8f-89dd-46da93d05877","resolution":{"observed_at":"2026-08-06T16:39:22.906941Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-08-06T05:19:30.168927Z","title":"Vid-gpt: Introducing gpt-style autoregressive generation in video diffusion models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.02056","last_updated":"2025-08-09T02:25:59Z","snapshot_observed_at":"2026-08-08T20:55:30.906593Z","submitted_at":"2025-08-04T04:50:05Z","title":"StarPose: 3D Human Pose Estimation via Spatial-Temporal Autoregressive Diffusion","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T05:19:30.168927Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2508.02056"},"observation_digest":"sha256:ad528cb5b2ffb3beeb84e3e28a7662d72800fa42b462afc7d0f8a97d67e3a238","observation_id":"ae3038c0-872c-4636-be66-323e54d6ebd4","resolution":{"observed_at":"2026-08-06T05:19:30.168927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-08-03T19:41:56.337223Z","title":"Vid-gpt: Introducing gpt-style autoregressive generation in video diffusion models.arXiv preprint arXiv:2406.10981, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.22973","last_updated":"2026-06-22T15:51:03Z","snapshot_observed_at":"2026-08-03T19:41:54.757475Z","submitted_at":"2025-11-28T08:25:59Z","title":"BIFE: Better Interaction, Fewer Errors for Minute-Long Video Generation","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T19:41:56.337223Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2511.22973"},"observation_digest":"sha256:cf788b7439f8484f650a27e763318ddc51a2bdcc500e16aa7ac42312f2547174","observation_id":"8855a3fc-8ce9-4d51-8efd-a89d56a2551c","resolution":{"observed_at":"2026-08-03T19:41:56.337223Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":"2406.10981","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-07-02T20:27:22.783676Z","title":"Vid-gpt: Introducing gpt-style autoregressive generation in video diffusion models","venue":null,"work_id":"adee2c01-4d22-4677-93f9-1dee5e6d7406","year":2024},"citing_paper":{"arxiv_id":"2603.00110","last_updated":"2026-04-23T12:54:44Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-02-18T14:58:18Z","title":"Learning Physics from Pretrained Video Models: A Multimodal Continuous and Sequential World Interaction Models for Robotic Manipulation","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-15T21:22:41.935691Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2603.00110"},"observation_digest":"sha256:64421d7618299f87032048753ba7a9677a1d84730c513c86ebcd63e531d9d4da","observation_id":"86a7ef8b-4e70-4894-baab-f7e938850f91","resolution":{"observed_at":"2026-05-15T21:30:20.926227Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":"2406.10981","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-07-02T20:27:22.783676Z","title":"Vid-gpt: Introducing gpt-style autoregressive generation in video diffusion models","venue":null,"work_id":"adee2c01-4d22-4677-93f9-1dee5e6d7406","year":2024},"citing_paper":{"arxiv_id":"2604.15911","last_updated":"2026-04-17T10:11:39Z","snapshot_observed_at":"2026-07-06T23:03:21.422544Z","submitted_at":"2026-04-17T10:11:39Z","title":"Efficient Video Diffusion Models: Advancements and Challenges","version":1},"reference_index":273,"source":"pdf_text","source_observed_at":"2026-05-10T08:28:29.706249Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2604.15911"},"observation_digest":"sha256:5c0d0f74009d47a8b5bec48146158e13a5ccb1f5d46f14761ada458a5738d91f","observation_id":"4d3e3561-75f3-4ceb-a85e-91759b8477e9","resolution":{"observed_at":"2026-05-10T09:03:26.111933Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":"2406.10981","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-07-02T20:27:22.783676Z","title":"Vid-gpt: Introducing gpt-style autoregressive generation in video diffusion models","venue":null,"work_id":"adee2c01-4d22-4677-93f9-1dee5e6d7406","year":2024},"citing_paper":{"arxiv_id":"2605.16054","last_updated":"2026-05-15T15:21:25Z","snapshot_observed_at":"2026-08-03T10:16:57.496693Z","submitted_at":"2026-05-15T15:21:25Z","title":"Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making","version":1},"reference_index":293,"source":"arxiv_source","source_observed_at":"2026-05-20T20:54:31.025488Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2605.16054"},"observation_digest":"sha256:9b1febe7eb1d8888beaee4db674069cdfb5634f6a6134c03d66d8f32f500991f","observation_id":"bc135bba-4dc1-415d-b394-a999b6f0ad3e","resolution":{"observed_at":"2026-05-20T20:59:01.972424Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models","version":1},"cited_work":{"arxiv_id":"2406.10981","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.10981","snapshot_observed_at":"2026-07-02T20:27:22.783676Z","title":"Vid-gpt: Introducing gpt-style autoregressive generation in video diffusion models","venue":null,"work_id":"adee2c01-4d22-4677-93f9-1dee5e6d7406","year":2024},"citing_paper":{"arxiv_id":"2606.07967","last_updated":"2026-06-06T03:50:45Z","snapshot_observed_at":"2026-07-06T23:47:33.680573Z","submitted_at":"2026-06-06T03:50:45Z","title":"DisCo: World Models with Discrete Camera Motion Control","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-27T20:21:20.257532Z"},"links":{"cited_paper":"/paper/2406.10981","citing_paper":"/paper/2606.07967"},"observation_digest":"sha256:dfdcadaea883d2c77588718f0db9cc63672d0ac34af860c066205f4507001b5a","observation_id":"a7f1120a-d747-4d7f-84b0-b72872c62208","resolution":{"observed_at":"2026-07-02T20:27:22.785256Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2406.10981/citation-record","integrity":"/paper/2406.10981/integrity","json":"/paper/2406.10981/citation-record.json","paper":"/paper/2406.10981"},"outbound":[],"paper":{"arxiv_id":"2406.10981","last_updated":"2024-06-16T15:37:22Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T18:31:45.125236Z","submitted_at":"2024-06-16T15:37:22Z","title":"ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2406.10981."}