{"as_of":"2026-08-07T19:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:36ec821cfd8eadb7a89e9e3590960680da0ef84fc019fce4f09cabba5946862f","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:29:39.770200Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.10639/citation-record","integrity":"/paper/2506.10639/integrity","json":"/paper/2506.10639/citation-record.json","paper":"/paper/2506.10639"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:29:34.683768Z","title":"Photorealistic video generation with diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:34.683768Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:7a2b713adfdd1d907d7908852d2331eb7ee321a11609e4ce33c0cc9d0624563d","observation_id":"b84bcf57-58d0-462d-952d-866492ac9364","resolution":{"observed_at":"2026-08-07T04:29:34.683768Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.07667","last_updated":"2024-07-10T13:46:08Z","snapshot_observed_at":"2026-08-07T00:56:39.117883Z","submitted_at":"2024-07-10T13:46:08Z","title":"VEnhancer: Generative Space-Time Enhancement for Video Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.07667","snapshot_observed_at":"2026-08-07T04:29:34.726688Z","title":"Venhancer: Generative space-time enhancement for video generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:34.726688Z"},"links":{"cited_paper":"/paper/2407.07667","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:6990e37eb3f0062a1ed591758d0475fca2acd3b5f3547ef3a2107ccd0d8304a9","observation_id":"54a87cbf-5f78-4e5b-ac5a-2c797a55eedc","resolution":{"observed_at":"2026-08-07T04:29:34.726688Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.06571","last_updated":"2023-08-12T13:53:10Z","snapshot_observed_at":"2026-08-07T17:54:54.749604Z","submitted_at":"2023-08-12T13:53:10Z","title":"ModelScope Text-to-Video Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.06571","snapshot_observed_at":"2026-08-07T04:29:34.788118Z","title":"Modelscope text-to-video technical report.arXiv preprint arXiv:2308.06571, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:34.788118Z"},"links":{"cited_paper":"/paper/2308.06571","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:fa3881271592af76b7212b9b0de80ccb09f7b557758e390d68aa44c58d309fe4","observation_id":"61837416-4c48-4d40-a1ea-744561dedfb4","resolution":{"observed_at":"2026-08-07T04:29:34.788118Z","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":"2026-08-07T04:29:34.871711Z","title":"Videocomposer: Compositional video synthesis with motion controllability.Advances in Neural Information Processing Systems, 36:7594–7611, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:34.871711Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:fbf17a32b279ea500a97b7995e4efe24e581500b746762b5675f2822bd499b59","observation_id":"030c8769-eb0a-4444-a42b-0c9c94934cf0","resolution":{"observed_at":"2026-08-07T04:29:34.871711Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.06072","last_updated":"2025-03-26T08:33:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-12T11:47:11Z","title":"CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.06072","snapshot_observed_at":"2026-08-07T04:29:34.950538Z","title":"Cogvideox: Text-to-video diffusion models with an expert transformer.arXiv preprint arXiv:2408.06072, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:34.950538Z"},"links":{"cited_paper":"/paper/2408.06072","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:67cb7603b423d655b44d006dac9078a6104e8bf26521ad2e3e65963bbc59aad4","observation_id":"cea318d0-78ef-4cac-b84e-9d63aeffe3ff","resolution":{"observed_at":"2026-08-07T04:29:34.950538Z","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":"2026-08-07T04:29:35.068376Z","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":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:35.068376Z"},"links":{"cited_paper":"/paper/2503.20314","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:0d390ec118d0ac40703c762295b9874ecaaac0411a685d361bb97c171d233772","observation_id":"df4c2c65-6821-48b3-baf5-bbc242c71f17","resolution":{"observed_at":"2026-08-07T04:29:35.068376Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03603","last_updated":"2025-03-11T08:14:25Z","snapshot_observed_at":"2026-08-03T00:44:01.942521Z","submitted_at":"2024-12-03T23:52:37Z","title":"HunyuanVideo: A Systematic Framework For Large Video Generative Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03603","snapshot_observed_at":"2026-08-07T04:29:35.164284Z","title":"Hunyuanvideo: A systematic framework for large video generative models.arXiv preprint arXiv:2412.03603, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:35.164284Z"},"links":{"cited_paper":"/paper/2412.03603","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:0aa7c26f5703f93ce61c4167e1087872e51e8450053be7a7ed28c1a8e8300890","observation_id":"45c4edba-a8a0-4f6d-b90f-8d2bd5484fdc","resolution":{"observed_at":"2026-08-07T04:29:35.164284Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_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},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.13918","snapshot_observed_at":"2026-08-07T04:29:35.300572Z","title":"Improving video generation with human feedback","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:35.300572Z"},"links":{"cited_paper":"/paper/2501.13918","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:599827df3145ad207af95f78473e59fd74e91fae37fb95a17af076cd7fc5f55b","observation_id":"0e670b5d-ee0f-4db5-8991-267f4fa16c44","resolution":{"observed_at":"2026-08-07T04:29:35.300572Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04814","last_updated":"2025-03-05T02:43:42Z","snapshot_observed_at":"2026-07-06T20:02:39.525801Z","submitted_at":"2024-12-06T07:16:14Z","title":"LiFT: Leveraging Human Feedback for Text-to-Video Model Alignment","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04814","snapshot_observed_at":"2026-08-07T04:29:35.464597Z","title":"Lift: Leveraging human feedback for text-to-video model alignment.arXiv preprint arXiv:2412.04814, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:35.464597Z"},"links":{"cited_paper":"/paper/2412.04814","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:ef234d9e445ac07c9876e5d5ae183ec7e6e5db0ffe90468457d70b5c2023dc87","observation_id":"3a0ac913-9b07-423f-aaf0-9bc2807e32a9","resolution":{"observed_at":"2026-08-07T04:29:35.464597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14167","last_updated":"2024-12-18T18:59:49Z","snapshot_observed_at":"2026-08-07T09:25:34.609643Z","submitted_at":"2024-12-18T18:59:49Z","title":"VideoDPO: Omni-Preference Alignment for Video Diffusion Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14167","snapshot_observed_at":"2026-08-07T04:29:35.557881Z","title":"Videodpo: Omni-preference alignment for video diffusion generation.arXiv preprint arXiv:2412.14167, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:35.557881Z"},"links":{"cited_paper":"/paper/2412.14167","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:66db69cf73ec1c4c7882c994bfc675339f5cd4d7eac20378f6108f240fdddaa5","observation_id":"16fa84b6-39c8-44b6-8b70-bf336ecbad5c","resolution":{"observed_at":"2026-08-07T04:29:35.557881Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.21059","last_updated":"2026-01-05T02:39:01Z","snapshot_observed_at":"2026-08-03T02:30:08.318253Z","submitted_at":"2024-12-30T16:24:09Z","title":"VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.21059","snapshot_observed_at":"2026-08-07T04:29:35.673428Z","title":"Visionreward: Fine-grained multi-dimensional human preference learning for image and video generation.arXiv preprint arXiv:2412.21059, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:35.673428Z"},"links":{"cited_paper":"/paper/2412.21059","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:203cc16a93190ef70bfe09958a95d754ba7a0d1ad5da5e4bff50dcbe7aeb438a","observation_id":"01fcccbf-f24b-4a32-81c2-f44da00ed37e","resolution":{"observed_at":"2026-08-07T04:29:35.673428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15127","last_updated":"2023-11-25T22:28:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-11-25T22:28:38Z","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15127","snapshot_observed_at":"2026-08-07T04:29:35.783078Z","title":"Stable video diffusion: Scaling latent video diffusion models to large datasets.arXiv preprint arXiv:2311.15127, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:35.783078Z"},"links":{"cited_paper":"/paper/2311.15127","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:c05280616322c69be8cefc8a5f9e441f94f1cd3e7ff7d8871b4ee565e82fa3ae","observation_id":"2f457a2f-0147-49f8-9192-12bba4d1b7f8","resolution":{"observed_at":"2026-08-07T04:29:35.783078Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.19512","last_updated":"2023-10-30T13:12:40Z","snapshot_observed_at":"2026-08-07T10:15:15.859263Z","submitted_at":"2023-10-30T13:12:40Z","title":"VideoCrafter1: Open Diffusion Models for High-Quality Video Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.19512","snapshot_observed_at":"2026-08-07T04:29:35.918527Z","title":"Videocrafter1: Open diffusion models for high-quality video generation.arXiv preprint arXiv:2310.19512, 2023","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:35.918527Z"},"links":{"cited_paper":"/paper/2310.19512","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:2f5c638977f39a5d3ff26f8d00e7bc4926af7723d1fa9a6d2da3b9a5c9a518f4","observation_id":"c82352ea-09b6-430a-810b-e87296faf42d","resolution":{"observed_at":"2026-08-07T04:29:35.918527Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:29:41.292504Z","title":"Flexible diffusion modeling of long videos.Advances in Neural Information Processing Systems, 35:27953–27965, 2022","venue":null,"work_id":"042fee3c-f4a0-42fa-99e7-9fde5c403259","year":2022},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:36.012341Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:ae3e03bab01b7bf43241348e8f80dd36f511268f54e8db104d02ab5e4a3d2bda","observation_id":"8f7beaeb-07e6-409a-b314-67ff6692abd5","resolution":{"observed_at":"2026-08-07T04:29:41.422461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03048","last_updated":"2025-05-01T09:40:21Z","snapshot_observed_at":"2026-08-02T13:01:06.918463Z","submitted_at":"2024-01-05T19:55:15Z","title":"Latte: Latent Diffusion Transformer for Video Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03048","snapshot_observed_at":"2026-08-07T04:29:36.113916Z","title":"Latte: Latent diffusion transformer for video generation.arXiv preprint arXiv:2401.03048, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:36.113916Z"},"links":{"cited_paper":"/paper/2401.03048","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:cb64e27b8a6eadefc25ed9e4a752d7cb6ff5a3bd7e74cfb4f32c111711165841","observation_id":"02ec4496-333c-4358-8659-b1e21813a7f7","resolution":{"observed_at":"2026-08-07T04:29:36.113916Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.20404","last_updated":"2024-12-29T08:52:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-29T08:52:49Z","title":"Open-Sora: Democratizing Efficient Video Production for All","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.20404","snapshot_observed_at":"2026-08-07T04:29:36.205019Z","title":"Open-sora: Democratizing efficient video production for all","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:36.205019Z"},"links":{"cited_paper":"/paper/2412.20404","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:c068adfff64c681b56088ec39d38220d82eb29d1d289b802381d242dee44bda9","observation_id":"646db30b-0295-441b-bbe5-cc9f92d1ea79","resolution":{"observed_at":"2026-08-07T04:29:36.205019Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:29:41.073437Z","title":"Vidm: Video implicit diffusion models","venue":null,"work_id":"1775c19b-9143-4707-bff7-b6f93d12589f","year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:36.363308Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:998f579e75c2f3c185d041ff4e07bcd47d04788fd3d6a3f69aa5680317748c22","observation_id":"d6d7c495-716f-4ad0-a45e-60a43486762a","resolution":{"observed_at":"2026-08-07T04:29:41.191534Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14792","last_updated":"2022-09-29T13:59:46Z","snapshot_observed_at":"2026-07-06T13:57:47.051387Z","submitted_at":"2022-09-29T13:59:46Z","title":"Make-A-Video: Text-to-Video Generation without Text-Video Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.14792","snapshot_observed_at":"2026-08-07T04:29:36.463830Z","title":"Make-a-video: Text-to-video generation without text-video data.arXiv preprint arXiv:2209.14792, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:36.463830Z"},"links":{"cited_paper":"/paper/2209.14792","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:9529a716a9f3884d70631642f19d6fb12952127a1374006230f3ee33a773f468","observation_id":"15ee06df-264b-4605-9721-94e82cb64c0e","resolution":{"observed_at":"2026-08-07T04:29:36.463830Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:29:40.877271Z","title":"Show-1: Marrying pixel and latent diffusion models for text-to-video generation.International Journal of Computer Vision, pages 1–15, 2024","venue":null,"work_id":"dc05425a-1ba3-4757-b16d-532600cc216b","year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:36.611929Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:c75abc5f4c00e3f06807e70efcf380ca1df430116e27f0263b56276db000c7f6","observation_id":"42f65169-a2fb-4f95-8349-ff02e0bbf80b","resolution":{"observed_at":"2026-08-07T04:29:40.957619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.15458","last_updated":"2024-10-20T17:51:35Z","snapshot_observed_at":"2026-07-06T19:36:41.445591Z","submitted_at":"2024-10-20T17:51:35Z","title":"Allegro: Open the Black Box of Commercial-Level Video Generation Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.15458","snapshot_observed_at":"2026-08-07T04:29:36.769463Z","title":"Allegro: Open the black box of commercial-level video generation model.arXiv preprint arXiv:2410.15458, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:36.769463Z"},"links":{"cited_paper":"/paper/2410.15458","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:387ecdf1ab004b09de4c1d86bbf088c9836f4d411a1a4083c959a1e8294fcc46","observation_id":"3b9c747b-fcd6-4b46-99e3-3dd3ab03be97","resolution":{"observed_at":"2026-08-07T04:29:36.769463Z","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":"2026-08-07T04:29:36.858137Z","title":"Scalable diffusion models with transformers","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:36.858137Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:e5d66537e252bc90c3d5aa78d83a7d8e2144453133a3eb58f2589f2b53193b58","observation_id":"5f4ac0bd-6c98-4bf0-81ba-564eb4ca4945","resolution":{"observed_at":"2026-08-07T04:29:36.858137Z","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":"2026-08-07T04:29:36.936888Z","title":"Elucidating the design space of diffusion-based generative models.Advances in neural information processing systems, 35:26565–26577, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:36.936888Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:9cf600f0794f14f528ba0fd35eb5f77353bab1ad0a4cc3cc6d0f1298898aa7f7","observation_id":"b354a7ef-9b20-40eb-917b-c3b8cc792555","resolution":{"observed_at":"2026-08-07T04:29:36.936888Z","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":"2026-08-07T04:29:37.047405Z","title":"Scaling rectified flow trans- formers for high-resolution image synthesis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:37.047405Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:2a37efb84d2eb92956ce7343c06fe2bc4135b61378ca41b7d4e8825e4f15be38","observation_id":"ca030abf-da3c-4abc-b9c7-c5165272cde5","resolution":{"observed_at":"2026-08-07T04:29:37.047405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.21755","last_updated":"2025-08-20T15:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-27T17:57:01Z","title":"VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.21755","snapshot_observed_at":"2026-08-07T04:29:37.188560Z","title":"Vbench-2.0: Advancing video generation benchmark suite for intrinsic faithfulness.arXiv preprint arXiv:2503.21755, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:37.188560Z"},"links":{"cited_paper":"/paper/2503.21755","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:c545103f4c374cba59c37323b74bb1121bb9e6f269979f356e6f11d46f7a8c66","observation_id":"25f6955b-fcf0-426c-976e-59c15c8e099f","resolution":{"observed_at":"2026-08-07T04:29:37.188560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.20694","last_updated":"2025-02-28T03:58:23Z","snapshot_observed_at":"2026-08-07T17:41:02.221324Z","submitted_at":"2025-02-28T03:58:23Z","title":"WorldModelBench: Judging Video Generation Models As World Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.20694","snapshot_observed_at":"2026-08-07T04:29:37.277478Z","title":"Worldmodelbench: Judging video generation models as world models.arXiv preprint arXiv:2502.20694, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:37.277478Z"},"links":{"cited_paper":"/paper/2502.20694","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:b504a57e9d1e6bfcc20ff2b33abeb7b37de757a5990a84752a6b936607d18b6d","observation_id":"2bf2fd3b-c7b2-448f-b47f-37f961e3d7f8","resolution":{"observed_at":"2026-08-07T04:29:37.277478Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:29:40.679349Z","title":"Advantage-weighted regression: Simple and scalable off-policy reinforcement learning, 2019","venue":null,"work_id":"3f528f60-a3eb-476e-8e40-8fa2f008d6ab","year":2019},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:37.415979Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:053fa4856cf47eb084d906926f61924d30790f38f79f2fbeb96a9b14250fdf6a","observation_id":"98a0a420-08a3-4f6c-919e-0bf4d2afc50f","resolution":{"observed_at":"2026-08-07T04:29:40.739996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12192","last_updated":"2023-02-23T17:34:53Z","snapshot_observed_at":"2026-07-06T14:55:12.100148Z","submitted_at":"2023-02-23T17:34:53Z","title":"Aligning Text-to-Image Models using Human Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12192","snapshot_observed_at":"2026-08-07T04:29:37.530489Z","title":"Aligning text-to-image models using human feedback.arXiv preprint arXiv:2302.12192, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:37.530489Z"},"links":{"cited_paper":"/paper/2302.12192","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:383047590bef5e288bb5ac708edf6dd79ef0e9617a059964dcbfb1a728652413","observation_id":"c503522c-07ea-432d-b02c-7c13facee579","resolution":{"observed_at":"2026-08-07T04:29:37.530489Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.02617","last_updated":"2026-04-17T21:00:45Z","snapshot_observed_at":"2026-07-30T10:05:05.279382Z","submitted_at":"2024-12-03T17:44:23Z","title":"Improving Dynamic Object Interactions in Text-to-Video Generation with AI Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.02617","snapshot_observed_at":"2026-08-07T04:29:37.670705Z","title":"Improving dynamic object interactions in text-to-video generation with ai feedback.arXiv preprint arXiv:2412.02617, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:37.670705Z"},"links":{"cited_paper":"/paper/2412.02617","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:d5aaf35d445093784d4f61e235f7c2797dfab16bdd24ee2365f0c473bff9e984","observation_id":"df2d7333-c8cc-4b69-90b2-6e06dc04ab51","resolution":{"observed_at":"2026-08-07T04:29:37.670705Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.13221","last_updated":"2023-03-20T17:29:45Z","snapshot_observed_at":"2026-07-06T14:22:24.004857Z","submitted_at":"2022-11-23T18:58:39Z","title":"Latent Video Diffusion Models for High-Fidelity Long Video Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.13221","snapshot_observed_at":"2026-08-07T04:29:37.767663Z","title":"Latent video diffusion models for high-fidelity long video generation.arXiv preprint arXiv:2211.13221, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:37.767663Z"},"links":{"cited_paper":"/paper/2211.13221","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:522eae59f41058b8013227f7b52222b3283c15b4bea8e0bc24f299cd1bf93345","observation_id":"0ae9246b-95e5-4b64-8af1-497f8d50859c","resolution":{"observed_at":"2026-08-07T04:29:37.767663Z","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":"2026-08-07T04:29:37.880698Z","title":"Direct preference optimization: Your language model is secretly a reward model","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:37.880698Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:74e2342ee8d76bbc4400523691dc990a3e3378d68b028b926dfc23e01ab5650e","observation_id":"51e41cf4-c842-4f87-92c1-65ee836e1363","resolution":{"observed_at":"2026-08-07T04:29:37.880698Z","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":"2026-08-07T04:29:37.991042Z","title":"Diffusion model alignment using direct preference optimization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:37.991042Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:22ae15ff7055222637e3dddf78afc8c7eee0ba56ac6b9d4dadbb8f7ff986b84b","observation_id":"f85c2159-b5f2-4342-9289-d78fc463aa0b","resolution":{"observed_at":"2026-08-07T04:29:37.991042Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06767","last_updated":"2023-12-01T14:28:06Z","snapshot_observed_at":"2026-08-07T04:02:54.504761Z","submitted_at":"2023-04-13T18:22:40Z","title":"RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06767","snapshot_observed_at":"2026-08-07T04:29:38.135404Z","title":"Raft: Reward ranked finetuning for generative foundation model alignment.arXiv preprint arXiv:2304.06767, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.135404Z"},"links":{"cited_paper":"/paper/2304.06767","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:f1106163ad9d37801f843264752978045d11dbb662af7bed7c224aae1279f7e4","observation_id":"dccc29e0-216f-4101-955f-9675bc0c0288","resolution":{"observed_at":"2026-08-07T04:29:38.135404Z","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":"2026-08-07T04:29:38.313805Z","title":"Using human feedback to fine-tune diffusion models without any reward model","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.313805Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:c23d358e7a4c4003d3ad83297252c9fd9a6358669b6556e081b68c6ae9b14c11","observation_id":"f1120756-8f57-4e87-87d8-26b565c7a88d","resolution":{"observed_at":"2026-08-07T04:29:38.313805Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04314","last_updated":"2025-03-25T17:06:27Z","snapshot_observed_at":"2026-08-06T20:07:18.681767Z","submitted_at":"2024-06-06T17:57:09Z","title":"Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.04314","snapshot_observed_at":"2026-08-07T04:29:38.396893Z","title":"Step-aware preference optimization: Aligning preference with denoising performance at each step.arXiv preprint arXiv:2406.04314, 2(3), 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.396893Z"},"links":{"cited_paper":"/paper/2406.04314","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:22b3a9d145c38bc3c0c0bf7149afe77358af1b8f8ab084ab75469a59ebd038d4","observation_id":"7b4eefa4-3d83-4a02-bd26-529ca2228b3a","resolution":{"observed_at":"2026-08-07T04:29:38.396893Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22304","last_updated":"2024-10-29T17:50:31Z","snapshot_observed_at":"2026-08-04T05:43:52.536455Z","submitted_at":"2024-10-29T17:50:31Z","title":"Flow-DPO: Improving LLM Mathematical Reasoning through Online Multi-Agent Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22304","snapshot_observed_at":"2026-08-07T04:29:38.509910Z","title":"Flow-dpo: Improving llm mathematical reasoning through online multi-agent learning.arXiv preprint arXiv:2410.22304, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.509910Z"},"links":{"cited_paper":"/paper/2410.22304","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:fa852bacc2e157589a9200ff8035c6f7f4a072f289a0032700d1277e73465ffc","observation_id":"3c3b4cdf-c412-446d-8908-961cc6afba05","resolution":{"observed_at":"2026-08-07T04:29:38.509910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.20194","last_updated":"2025-03-26T03:37:52Z","snapshot_observed_at":"2026-08-07T16:36:46.066394Z","submitted_at":"2025-03-26T03:37:52Z","title":"GAPO: Learning Preferential Prompt through Generative Adversarial Policy Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.20194","snapshot_observed_at":"2026-08-07T04:29:38.537856Z","title":"Gapo: Learning preferential prompt through generative adversarial policy optimization.arXiv preprint arXiv:2503.20194, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.537856Z"},"links":{"cited_paper":"/paper/2503.20194","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:380c0ce72c90b146032d08b737a100b1e03a276e8e2215135898ecf26af56830","observation_id":"02ad75a6-c0ce-472d-bfb6-7746a0a3eab8","resolution":{"observed_at":"2026-08-07T04:29:38.537856Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-07T04:29:38.585815Z","title":"Proximal policy optimization algorithms","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.585815Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:a68a28889c62c55af091b1a14948c5e25e2c3dacce463219f91920a75eee3c22","observation_id":"8ec20fa5-d281-453b-a4d9-ae0d45104786","resolution":{"observed_at":"2026-08-07T04:29:38.585815Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13301","last_updated":"2024-01-04T19:11:25Z","snapshot_observed_at":"2026-08-01T15:43:51.739518Z","submitted_at":"2023-05-22T17:57:41Z","title":"Training Diffusion Models with Reinforcement Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13301","snapshot_observed_at":"2026-08-07T04:29:38.635088Z","title":"Training diffusion models with reinforcement learning.arXiv preprint arXiv:2305.13301, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.635088Z"},"links":{"cited_paper":"/paper/2305.13301","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:6b2ae21573c538922ad78c14c100df1fafb79f479a1c5b7cf0a543fd360fc524","observation_id":"d04ec081-92e6-4d52-94e4-50207e25cac3","resolution":{"observed_at":"2026-08-07T04:29:38.635088Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:29:40.462901Z","title":"Reinforcement learning for fine- tuning text-to-image diffusion models","venue":null,"work_id":"b02eccbd-8731-4c87-bb8a-0c514fa75597","year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.722553Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:47a2c7fcf7481c6f10bc75138da3ed7f2c803859a817094be6000d5167094acd","observation_id":"3a51d4ba-008c-4158-a518-bddc22a7c095","resolution":{"observed_at":"2026-08-07T04:29:40.534519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:29:38.809581Z","title":"Structure and content-guided video synthesis with diffusion models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.809581Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:1f1901cde40b0bc35767a1d65d7a90a290f97dcdc6acbbe84554fbecef1e853d","observation_id":"43407ae1-ff48-4df2-ac02-5355ae1e2834","resolution":{"observed_at":"2026-08-07T04:29:38.809581Z","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":"2026-08-07T04:29:38.937918Z","title":"Video generation models as world simulators","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:38.937918Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:0d2392b98ac09ae4146a7a07d89a5ea268050c5fe6e546aea6a5920b5efadb75","observation_id":"677b00e3-e171-4d88-b6b8-1faa3eb467ad","resolution":{"observed_at":"2026-08-07T04:29:38.937918Z","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":"2026-08-07T04:29:39.045278Z","title":"Cotracker: It is better to track together","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:39.045278Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:afd846ab3793851b0ec1ad69b87f9746d683f2a663774479162205bdae7ce289","observation_id":"502f77ae-30b4-4e8d-bb6f-98d28247526f","resolution":{"observed_at":"2026-08-07T04:29:39.045278Z","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":"2026-08-07T04:29:39.144940Z","title":"Video generation models as world simulators, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:39.144940Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:47adc7a42c6ac43a9fdda073e4ccc10552dbf63ab38e0ce25a94dc99967619b9","observation_id":"4965863d-13f6-46cf-b683-aba510ec6ae5","resolution":{"observed_at":"2026-08-07T04:29:39.144940Z","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":"2026-08-07T04:29:39.266036Z","title":"Kling ai.https://klingai.kuaishou.com/, 2024.06","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:39.266036Z"},"links":{"citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:de230f596c9bebe4e805957c517171850c86a3000024f99fe03a8fa829ea29fb","observation_id":"3684ae8c-c882-4b4f-9e96-83db357a0df9","resolution":{"observed_at":"2026-08-07T04:29:39.266036Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08260","last_updated":"2025-04-26T17:58:24Z","snapshot_observed_at":"2026-08-01T11:16:30.883699Z","submitted_at":"2024-10-10T17:57:49Z","title":"Koala-36M: A Large-scale Video Dataset Improving Consistency between Fine-grained Conditions and Video Content","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.08260","snapshot_observed_at":"2026-08-07T04:29:39.411751Z","title":"Koala-36m: A large-scale video dataset improving con- sistency between fine-grained conditions and video content.arXiv preprint arXiv:2410.08260, 2024","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:39.411751Z"},"links":{"cited_paper":"/paper/2410.08260","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:c2ba9d1a8f561215232a76c5ff69e6060a3d7d8db61f67f4f5f1a31f32168871","observation_id":"ac7eec90-e1c1-429f-9411-f21d674beb6f","resolution":{"observed_at":"2026-08-07T04:29:39.411751Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.15252","last_updated":"2024-10-14T04:08:53Z","snapshot_observed_at":"2026-07-06T18:34:56.008706Z","submitted_at":"2024-06-21T15:43:46Z","title":"VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.15252","snapshot_observed_at":"2026-08-07T04:29:39.531704Z","title":"Videoscore: Building automatic metrics to simulate fine-grained human feedback for video generation.arXiv preprint arXiv:2406.15252, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:39.531704Z"},"links":{"cited_paper":"/paper/2406.15252","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:7b15372065711d209b8dd559a024a7278af47fb5cc0994843f39d52660d5db3d","observation_id":"be29dfc3-72d3-426d-bcdf-c9f4e5149870","resolution":{"observed_at":"2026-08-07T04:29:39.531704Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-07T04:29:39.658035Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:39.658035Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:ef9f36408e673c3d13e7c5f8e2a9e60b5108a5f3585dd8660cc6faf83f61f7a5","observation_id":"0b02af15-157f-4dd9-aae1-4c1d4d0dc9f4","resolution":{"observed_at":"2026-08-07T04:29:39.658035Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02713","last_updated":"2025-08-01T16:40:14Z","snapshot_observed_at":"2026-08-02T12:24:31.329178Z","submitted_at":"2024-10-03T17:36:49Z","title":"LLaVA-Video: Video Instruction Tuning With Synthetic Data","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02713","snapshot_observed_at":"2026-08-07T04:29:39.770200Z","title":"Camera zoom in, Disneyland","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T04:29:39.770200Z"},"links":{"cited_paper":"/paper/2410.02713","citing_paper":"/paper/2506.10639"},"observation_digest":"sha256:03ba45fd6ece569a8aef04f0298b776821b7ddd6b54ed4db485a2f818f4e0f18","observation_id":"28c45976-fa18-49ff-ad2e-50198112175c","resolution":{"observed_at":"2026-08-07T04:29:39.770200Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.10639","last_updated":"2025-06-12T12:25:37Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T04:18:45.003587Z","submitted_at":"2025-06-12T12:25:37Z","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":41,"verified_exact":0,"verified_fuzzy":5},"total_outbound_references":48},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2506.10639."}