{"as_of":"2026-08-20T22:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:73532e151bab1c4e8ff2f784cff6c7497798852a0e952af34762eb64e0aac953","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":21,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":21,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":21,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":21,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T14:26:21.996386Z","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":"2026-05-23T07:02:41.761466Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":"2405.18750","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":"ff6697e3-f795-435f-96bc-609ee5fb53dd","year":2024},"citing_paper":{"arxiv_id":"2408.06072","last_updated":"2025-03-26T08:33:10Z","snapshot_observed_at":"2026-08-15T19:52:28.153954Z","submitted_at":"2024-08-12T11:47:11Z","title":"CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer","version":3},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-05-10T18:26:22.224924Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2408.06072"},"observation_digest":"sha256:33214f99ada8f7c96dfa113be381fa732d4a635c8c106dc6688410b49befcf9c","observation_id":"d7f15538-722a-4a8c-9e85-3090e06296c0","resolution":{"observed_at":"2026-05-10T18:26:22.324772Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":"2405.18750","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":"ff6697e3-f795-435f-96bc-609ee5fb53dd","year":2024},"citing_paper":{"arxiv_id":"2409.18869","last_updated":"2024-09-27T16:06:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-09-27T16:06:11Z","title":"Emu3: Next-Token Prediction is All You Need","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-11T10:56:06.418360Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2409.18869"},"observation_digest":"sha256:335bb31e1f65a5b7927738f038762ea0f1edb0e7e74375cfd1a88ca4ebb11f37","observation_id":"d6ba3f1e-ce19-4a5a-96aa-163764b662ed","resolution":{"observed_at":"2026-05-11T10:56:08.776459Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-12T14:26:21.996386Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.16718","last_updated":"2025-04-25T02:50:58Z","snapshot_observed_at":"2026-08-18T14:50:45.868697Z","submitted_at":"2024-11-22T23:59:12Z","title":"Neuro-Symbolic Evaluation of Text-to-Video Models using Formal Verification","version":5},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T14:26:21.996386Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2411.16718"},"observation_digest":"sha256:c9cb67d112b5ff70e6c4a18da4c944b9a2cff408a9c924a8bd4de0d661745241","observation_id":"5d4e8c6e-447c-451c-8788-3dcf96766249","resolution":{"observed_at":"2026-08-12T14:26:21.996386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-11T20:17:52.613147Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.05899","last_updated":"2024-12-08T11:36:32Z","snapshot_observed_at":"2026-08-14T20:30:41.597939Z","submitted_at":"2024-12-08T11:36:32Z","title":"Accelerating Video Diffusion Models via Distribution Matching","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T20:17:52.613147Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2412.05899"},"observation_digest":"sha256:5c362e39e9f24ebd7ea91b8b294e35fa7d98575a5c93e576eb45d7987aee10b4","observation_id":"9cc7045f-8204-4314-bff3-e01eeb5b52e5","resolution":{"observed_at":"2026-08-11T20:17:52.613147Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-11T16:43:08.327092Z","title":"T2V- Turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.09856","last_updated":"2025-05-24T21:49:46Z","snapshot_observed_at":"2026-08-15T01:14:53.670017Z","submitted_at":"2024-12-13T04:55:10Z","title":"LinGen: Towards High-Resolution Minute-Length Text-to-Video Generation with Linear Computational Complexity","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T16:43:08.327092Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2412.09856"},"observation_digest":"sha256:5268f69a1301bfe73be1d694aac4788bc5f6f75e341790cdda42df7edd5b2bc9","observation_id":"49a8df5e-1cf7-4675-a3cd-d7887bad7f70","resolution":{"observed_at":"2026-08-11T16:43:08.327092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-11T15:58:35.736814Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10494","last_updated":"2025-06-09T22:48:33Z","snapshot_observed_at":"2026-08-16T09:38:59.229931Z","submitted_at":"2024-12-13T18:59:56Z","title":"SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T15:58:35.736814Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2412.10494"},"observation_digest":"sha256:ba8dbfa059159a3fd3f0adfdfb7cc7adfa2bd75507f2a04baace847e0d9087d0","observation_id":"4b4f4a45-88a1-4813-b3c3-94f17a9983c9","resolution":{"observed_at":"2026-08-11T15:58:35.736814Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":"2405.18750","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":"ff6697e3-f795-435f-96bc-609ee5fb53dd","year":2024},"citing_paper":{"arxiv_id":"2412.15689","last_updated":"2026-05-06T21:36:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-20T09:07:36Z","title":"DOLLAR: Few-Step Video Generation via Distillation and Latent Reward Optimization","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-23T06:57:50.897865Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2412.15689"},"observation_digest":"sha256:6fbc3a2fac03258abab9b9e460e6cda48369b19f5dec0a879c8bf38234c6e293","observation_id":"90c5a284-39b7-4a49-8c32-f32ce2b82b28","resolution":{"observed_at":"2026-05-23T07:02:41.764798Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-10T20:41:46.753046Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.07647","last_updated":"2025-01-13T19:17:06Z","snapshot_observed_at":"2026-08-18T02:24:03.216298Z","submitted_at":"2025-01-13T19:17:06Z","title":"BlobGEN-Vid: Compositional Text-to-Video Generation with Blob Video Representations","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T20:41:46.753046Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2501.07647"},"observation_digest":"sha256:63a685be1d4843d95a4e054ea526aa8ced90aeefb0e55e465e1042d29c6c35f0","observation_id":"4f48b987-b94a-4382-80d7-4a9ce3047b56","resolution":{"observed_at":"2026-08-10T20:41:46.753046Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":"2405.18750","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":"ff6697e3-f795-435f-96bc-609ee5fb53dd","year":2024},"citing_paper":{"arxiv_id":"2501.13918","last_updated":"2025-10-27T08:22:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-23T18:55:41Z","title":"Improving Video Generation with Human Feedback","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-13T15:30:02.578430Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2501.13918"},"observation_digest":"sha256:2833ad6cf4aee404b0fac0f405a440f4b2825d4f496452e8052ce72bc0f1aaff","observation_id":"a1c60612-ad5a-42a4-a2fd-492a0722c019","resolution":{"observed_at":"2026-05-13T15:30:02.717396Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-08T22:37:42.061479Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04507","last_updated":"2025-06-04T23:21:39Z","snapshot_observed_at":"2026-08-17T20:33:39.027283Z","submitted_at":"2025-02-06T21:17:09Z","title":"Fast Video Generation with Sliding Tile Attention","version":3},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-08T22:37:42.061479Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2502.04507"},"observation_digest":"sha256:71cd0a36532c3906aeda9b1bec72bec782c1bf9057f7a7cce734c38b1ba7cab8","observation_id":"7815a47c-4b65-4272-a143-e39145aebd2e","resolution":{"observed_at":"2026-08-08T22:37:42.061479Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-08T16:36:00.669349Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06155","last_updated":"2025-02-17T07:08:23Z","snapshot_observed_at":"2026-08-17T12:25:57.382548Z","submitted_at":"2025-02-10T05:00:56Z","title":"Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:00.669349Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2502.06155"},"observation_digest":"sha256:d2a63d2590030a37ad7eb058d6b8eac613f29a61768d3a4b9b61d0465fffa654","observation_id":"f1194f38-bc35-473c-bff2-3b3ba0fd07fa","resolution":{"observed_at":"2026-08-08T16:36:00.669349Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-09T11:26:17.328708Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06812","last_updated":"2025-02-17T20:35:45Z","snapshot_observed_at":"2026-08-19T19:06:39.656928Z","submitted_at":"2025-02-04T21:10:25Z","title":"Harness Local Rewards for Global Benefits: Effective Text-to-Video Generation Alignment with Patch-level Reward Models","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-09T11:26:17.328708Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2502.06812"},"observation_digest":"sha256:e3fa794279b00a862eebc4bd2f949a81646c4dc1dadd88066c4cae8d6ce9c9c1","observation_id":"9bc82d02-afd8-4e98-b2cb-a35855234460","resolution":{"observed_at":"2026-08-09T11:26:17.328708Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-07T04:55:28.761207Z","title":"T2v-turbo: Breaking the quality bottleneck of video consistency model with mixed reward feedback","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.11144","last_updated":"2025-06-11T05:33:03Z","snapshot_observed_at":"2026-08-07T04:46:32.123425Z","submitted_at":"2025-06-11T05:33:03Z","title":"AlignHuman: Improving Motion and Fidelity via Timestep-Segment Preference Optimization for Audio-Driven Human Animation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T04:55:28.761207Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2506.11144"},"observation_digest":"sha256:f795cad5c27d3c845a3ab1b0033c625efe18e059cfee5f6ce22e2061c58345ba","observation_id":"fd030be6-b309-445a-b29d-afe56d43af43","resolution":{"observed_at":"2026-08-07T04:55:28.761207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-06T23:20:47.758591Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.18564","last_updated":"2025-06-23T12:20:14Z","snapshot_observed_at":"2026-08-14T20:37:45.346566Z","submitted_at":"2025-06-23T12:20:14Z","title":"VQ-Insight: Teaching VLMs for AI-Generated Video Quality Understanding via Progressive Visual Reinforcement Learning","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T23:20:47.758591Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2506.18564"},"observation_digest":"sha256:7c0047443974e9b3e87dddfab07418addaf1a2e9536d854d2553b633e173c912","observation_id":"8114b6c2-c089-4c25-a59c-d1939486774b","resolution":{"observed_at":"2026-08-06T23:20:47.758591Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-06T23:12:52.904057Z","title":"T2v-turbo: Breaking the quality bottleneck of video consistency model with mixed reward feedback","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19348","last_updated":"2026-07-08T01:33:00Z","snapshot_observed_at":"2026-08-09T02:19:01.382750Z","submitted_at":"2025-06-24T06:20:15Z","title":"When Distillation Breaks Motion Control: Restoring Generative Trajectories for Fast Video Generators","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T23:12:52.904057Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2506.19348"},"observation_digest":"sha256:2e59df938833725c99e6ae414a4f05e4a5c11d523af6dba4d8571838ef1c2bc3","observation_id":"789be283-39b0-44f1-8fed-055e3d76aa16","resolution":{"observed_at":"2026-08-06T23:12:52.904057Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":"2405.18750","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":"ff6697e3-f795-435f-96bc-609ee5fb53dd","year":2024},"citing_paper":{"arxiv_id":"2507.07982","last_updated":"2026-05-05T14:55:01Z","snapshot_observed_at":"2026-08-14T21:13:23.101760Z","submitted_at":"2025-07-10T17:55:08Z","title":"Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-05-19T05:13:28.767788Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2507.07982"},"observation_digest":"sha256:b790340bdea234c44917420a33b324f8b2e501c46ca14cb6167d03d8c6bb4025","observation_id":"122d9569-a45d-4016-860b-0db77d8a1db6","resolution":{"observed_at":"2026-05-19T05:17:06.729045Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-06T11:32:41.788635Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.22604","last_updated":"2025-07-30T12:19:01Z","snapshot_observed_at":"2026-08-15T17:40:29.158367Z","submitted_at":"2025-07-30T12:19:01Z","title":"ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T11:32:41.788635Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2507.22604"},"observation_digest":"sha256:6d568d78b4759b09ab5da9ebd3a565ab8b8a388cc020c05126f37c95e4416bcb","observation_id":"07ef3d34-9444-4738-a6f1-6d3f3f07fe95","resolution":{"observed_at":"2026-08-06T11:32:41.788635Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-06T04:36:13.480170Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback.arXiv preprint arXiv:2405.18750, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.03252","last_updated":"2025-08-27T11:39:11Z","snapshot_observed_at":"2026-08-14T04:57:20.721064Z","submitted_at":"2025-08-05T09:30:39Z","title":"Robust Single-Stage Fully Sparse 3D Object Detection via Detachable Latent Diffusion","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T04:36:13.480170Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2508.03252"},"observation_digest":"sha256:3d6592d71528e4adae607f4e3d6f4cac9cd0cc2c6645c4bd231a9f947af08c1e","observation_id":"53f460a6-c475-454f-8a14-175e3d47424d","resolution":{"observed_at":"2026-08-06T04:36:13.480170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":"2405.18750","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T2v- turbo: Breaking the quality bottleneck of video consis- tency model with mixed reward feedback","venue":null,"work_id":"ff6697e3-f795-435f-96bc-609ee5fb53dd","year":2024},"citing_paper":{"arxiv_id":"2510.20206","last_updated":"2026-05-14T08:53:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-10-23T04:45:09Z","title":"RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-18T05:13:42.934115Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2510.20206"},"observation_digest":"sha256:46f0026c5503d223cc1d933cd4448c038df3677b89661541d0071f0168fa6bf6","observation_id":"82e642ad-4ac0-4888-ae1c-69e8054d0bf5","resolution":{"observed_at":"2026-05-18T05:15:54.481132Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-07-14T03:51:24.547781Z","title":"arXiv preprint arXiv:2405.18750 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.11689","last_updated":"2026-07-13T15:22:56Z","snapshot_observed_at":"2026-08-20T06:23:24.871101Z","submitted_at":"2026-07-13T15:22:56Z","title":"From World Action Models to Embodied Brains: A Roadmap for Open-World Physical Intelligence","version":1},"reference_index":142,"source":"arxiv_source","source_observed_at":"2026-07-14T03:51:24.547781Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2607.11689"},"observation_digest":"sha256:b7c5347b8820d1c7dd0a6006509d6101d1c2e7877f9b690be78a25d8178e8bbb","observation_id":"9133d09b-e088-45b7-8f58-df14cfd378ed","resolution":{"observed_at":"2026-07-14T03:51:24.547781Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18750","snapshot_observed_at":"2026-08-01T17:45:04.688549Z","title":"arXiv preprint arXiv:2405.18750 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17560","last_updated":"2026-07-20T05:09:36Z","snapshot_observed_at":"2026-08-19T20:20:37.349402Z","submitted_at":"2026-07-20T05:09:36Z","title":"Reinforcement Learning: From Algorithms To Foundation Models","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-01T17:45:04.688549Z"},"links":{"cited_paper":"/paper/2405.18750","citing_paper":"/paper/2607.17560"},"observation_digest":"sha256:01478a8c548b578b397e8b86ed34c85dabb0370ed715c386a4806c88b0c4ab02","observation_id":"9714246d-8506-4c44-867d-638f3bbd9dce","resolution":{"observed_at":"2026-08-01T17:45:04.688549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2405.18750/citation-record","integrity":"/paper/2405.18750/integrity","json":"/paper/2405.18750/citation-record.json","paper":"/paper/2405.18750"},"outbound":[],"paper":{"arxiv_id":"2405.18750","last_updated":"2024-10-11T07:50:49Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T13:48:21.513276Z","submitted_at":"2024-05-29T04:26:17Z","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback"},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2405.18750."}