{"as_of":"2026-08-07T11:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:58bcd1b2f937586777d4fbcadc0f714a8fcdfa1c68f4df370875762d0c80a2cc","coverage":[{"denominator":18,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T09:17:20.585749Z","state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"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/2607.00867/citation-record","integrity":"/paper/2607.00867/integrity","json":"/paper/2607.00867/citation-record.json","paper":"/paper/2607.00867"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T09:17:20.543774Z","title":"arXiv preprint arXiv:2512.22315","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.543774Z"},"links":{"citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:a2d76aee26e8362d8123bf1dd0c36d4630443c0bf527e8564bfb91c89274e9f4","observation_id":"0b2eb096-a4a6-454a-9a89-162a48a64938","resolution":{"observed_at":"2026-08-02T09:17:20.543774Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.21776","last_updated":"2025-10-22T16:42:24Z","snapshot_observed_at":"2026-08-05T07:15:29.998948Z","submitted_at":"2025-03-27T17:59:51Z","title":"Video-R1: Reinforcing Video Reasoning in MLLMs","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.21776","snapshot_observed_at":"2026-08-02T09:17:20.546688Z","title":"Kairui Hu, Penghao Wu, Fanyi Pu, Wang Xiao, Yuan- han Zhang, Xiang Yue, Bo Li, and Ziwei Liu","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.546688Z"},"links":{"cited_paper":"/paper/2503.21776","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:062c4a7fdf3fa8ca0633c0b37a609145c6ff399023820a7dea432ef0e6223f12","observation_id":"16ba4161-da79-4b33-a995-72a69267d47d","resolution":{"observed_at":"2026-08-02T09:17:20.546688Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.13826","last_updated":"2025-01-23T16:51:47Z","snapshot_observed_at":"2026-07-06T20:25:03.950783Z","submitted_at":"2025-01-23T16:51:47Z","title":"Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.13826","snapshot_observed_at":"2026-08-02T09:17:20.550240Z","title":"Hongbo Jin, Qingyuan Wang, Wenhao Zhang, Yang Liu, and Sijie Cheng","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.550240Z"},"links":{"cited_paper":"/paper/2501.13826","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:1afe2d850def6965a49154613f3f1be50e18919df4748cc2164f0e50fc25bc48","observation_id":"f704073d-3c4e-4b54-8fc9-4a3843aa86e1","resolution":{"observed_at":"2026-08-02T09:17:20.550240Z","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":"2026-08-02T09:17:20.553197Z","title":"Peng Jin, Jinfa Ryu, Yuan Huang, Bin Lin, and 1 others","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.553197Z"},"links":{"citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:f73b59896816762fc96dbbcd446e11cff0fa60f8357dda8315818a44e5cbfb3e","observation_id":"3d6ddcfa-8949-4219-bcc9-7db125894016","resolution":{"observed_at":"2026-08-02T09:17:20.553197Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03326","last_updated":"2024-10-26T16:35:13Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-06T17:59:44Z","title":"LLaVA-OneVision: Easy Visual Task Transfer","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03326","snapshot_observed_at":"2026-08-02T09:17:20.559211Z","title":"Hongyu Li, Songhao Han, Yue Liao, Junfeng Luo, Jialin Gao, Shuicheng Yan, and Si Liu","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.559211Z"},"links":{"cited_paper":"/paper/2408.03326","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:1242d0095ade8e20cc1cd6a097ec1855ac74cee45201ca321541b4d9108c1e41","observation_id":"28aa8a9c-dd8f-43fe-92bc-6cffd1ffcd17","resolution":{"observed_at":"2026-08-02T09:17:20.559211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05424","last_updated":"2024-06-10T01:36:53Z","snapshot_observed_at":"2026-07-06T15:40:24.127663Z","submitted_at":"2023-06-08T17:59:56Z","title":"Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05424","snapshot_observed_at":"2026-08-02T09:17:20.564288Z","title":"Kun Ouyang, Yuanxin Liu, Linli Yao, Yishuo Cai, Hao Zhou, Fandong Meng, Jie Zhou, and Xu Sun","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.564288Z"},"links":{"cited_paper":"/paper/2306.05424","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:7ba3fea9a612890af1a15365a7a031cf3daa77bdd748c21bf931a6673288d80d","observation_id":"f31da8e7-c1cc-4d07-b2fb-d46b9b6c6ee8","resolution":{"observed_at":"2026-08-02T09:17:20.564288Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.02051","last_updated":"2024-03-28T12:41:14Z","snapshot_observed_at":"2026-07-06T16:56:42.232555Z","submitted_at":"2023-12-04T17:09:52Z","title":"TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.02051","snapshot_observed_at":"2026-08-02T09:17:20.566842Z","title":"Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.566842Z"},"links":{"cited_paper":"/paper/2312.02051","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:7e22d19e099cf14b7ee0cb5cd5283047674b41c318cf5097b95c58cbdb9d4236","observation_id":"66d9599d-a935-4146-8499-6ec150eea4e5","resolution":{"observed_at":"2026-08-02T09:17:20.566842Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-08-06T14:58:42.911363Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-02T09:17:20.569529Z","title":"9 Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, and Yueting Zhuang","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.569529Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:7dcdb2fe42bc88f8b9fd2c7718d3f7a4fe270e9b591762d5aa09276851486e5b","observation_id":"0843d77b-7031-4c79-9c0f-725a0a38c07b","resolution":{"observed_at":"2026-08-02T09:17:20.569529Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.01694","last_updated":"2025-02-13T07:42:33Z","snapshot_observed_at":"2026-07-06T20:00:18.828829Z","submitted_at":"2024-12-02T16:37:50Z","title":"Enhancing Video-LLM Reasoning via Agent-of-Thoughts Distillation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.01694","snapshot_observed_at":"2026-08-02T09:17:20.572219Z","title":"Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.572219Z"},"links":{"cited_paper":"/paper/2412.01694","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:aca38942cf6b4c73dcd970cce333bf06d749837d3b2edeffa5b454164814729f","observation_id":"b9a6b450-b810-4ca2-9fe6-07625edae2ba","resolution":{"observed_at":"2026-08-02T09:17:20.572219Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-08-02T09:17:20.574790Z","title":"Qi Wang, Yanrui Yu, Ye Yuan, Rui Mao, and Tianfei Zhou","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.574790Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:43757c8b8fbd520d7d5031d0bfe51769d7d2efa050a0436219b0c291e33e13d6","observation_id":"9d2825c2-a603-43f1-b7db-49ac1f769f87","resolution":{"observed_at":"2026-08-02T09:17:20.574790Z","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":"2026-08-02T09:17:20.577428Z","title":"thinking with videos","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.577428Z"},"links":{"citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:65d076152370844d6345348f0728a90bcc880722ada713473e4b06a090a7ea30","observation_id":"6de5743c-281c-447c-9d2d-e8b6ddf43e93","resolution":{"observed_at":"2026-08-02T09:17:20.577428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15754","last_updated":"2024-07-22T16:00:55Z","snapshot_observed_at":"2026-08-06T14:12:05.548569Z","submitted_at":"2024-07-22T16:00:55Z","title":"LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15754","snapshot_observed_at":"2026-08-02T09:17:20.580137Z","title":"Jihan Yang, Shusheng Yang, Anjali W","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.580137Z"},"links":{"cited_paper":"/paper/2407.15754","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:6932f4eae2d3fc5d1707d1fc05bf46cbb40e92d67bbd02da8e538e0262f019e3","observation_id":"58b91602-6fc8-424f-a71e-b6fe58998e8a","resolution":{"observed_at":"2026-08-02T09:17:20.580137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14171","last_updated":"2025-07-02T21:00:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-18T18:59:54Z","title":"Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14171","snapshot_observed_at":"2026-08-02T09:17:20.583170Z","title":"Zuhao Yang, Sudong Wang, Kaichen Zhang, Keming Wu, Sicong Leng, Yifan Zhang, Bo Li, Chengwei Qin, Shijian Lu, Xingxuan Li, and 1 others","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.583170Z"},"links":{"cited_paper":"/paper/2412.14171","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:2e3d58d2dbbebbb9b92d2e212b4aca2e2aaefde30b73cbc4647fd2dc9060bdf3","observation_id":"44d82397-828d-4507-91a3-dd56f3cb842a","resolution":{"observed_at":"2026-08-02T09:17:20.583170Z","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":"2026-08-02T09:17:20.585749Z","title":"InInternational Conference on Learning Representations","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.585749Z"},"links":{"citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:7f468dc452e8aceae457efe88d287b9581eb7e1311e6147e9b4e01a3323fece0","observation_id":"41ba027a-2781-4444-9a53-89fb205355d6","resolution":{"observed_at":"2026-08-02T09:17:20.585749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.08046","last_updated":"2024-04-05T15:21:09Z","snapshot_observed_at":"2026-07-06T16:47:17.136168Z","submitted_at":"2023-11-14T10:11:36Z","title":"Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.08046","snapshot_observed_at":"2026-08-02T09:17:20.556107Z","title":"Bo Li, Yuanhan Zhang, Dong Guo, Renrui Zhang, Feng Li, Hao Zhang, Kaichen Zhang, Yanwei Li, Ziwei Liu, and Chunyuan Li","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.556107Z"},"links":{"cited_paper":"/paper/2311.08046","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:013f77c19e593b7293b4fa8c6794dae19328e3b83e40e3006080fe5459af408c","observation_id":"9d517c64-2dc3-45cd-b0fb-993feec28c5c","resolution":{"observed_at":"2026-08-02T09:17:20.556107Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19437","last_updated":"2025-02-18T17:26:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-27T04:03:16Z","title":"DeepSeek-V3 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19437","snapshot_observed_at":"2026-08-02T09:17:20.540520Z","title":"arXiv preprint arXiv:2412.19437","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.540520Z"},"links":{"cited_paper":"/paper/2412.19437","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:813f1150ad084a4c8ddf785a6574da3b35ef34b5d2cd9068688112adcbe80458","observation_id":"df43f777-192b-4c77-8a21-16155985acb3","resolution":{"observed_at":"2026-08-02T09:17:20.540520Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13923","last_updated":"2025-02-19T18:00:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-19T18:00:14Z","title":"Qwen2.5-VL Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13923","snapshot_observed_at":"2026-08-02T09:17:20.536090Z","title":"DeepSeek-AI","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.536090Z"},"links":{"cited_paper":"/paper/2502.13923","citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:684782780a8f521147696cac4a7dc2cfbcb682f136125bce16fbe32b1c7fc80d","observation_id":"2412de57-12de-49c4-9cd4-78431b3bf4d7","resolution":{"observed_at":"2026-08-02T09:17:20.536090Z","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":"2026-08-02T09:17:20.561868Z","title":"Muhammad Maaz, Hanoona Rasheed, Salman Khan, and Fahad Shahbaz Khan","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection","version":3},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-02T09:17:20.561868Z"},"links":{"citing_paper":"/paper/2607.00867"},"observation_digest":"sha256:c78362098bae157e149119bb71f410dfca17b4db120776d1c20be25be58ec930","observation_id":"3b4c5655-1e23-497d-ac8f-f69fd35904c1","resolution":{"observed_at":"2026-08-02T09:17:20.561868Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.00867","last_updated":"2026-07-15T08:03:34Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-02T09:17:20.227144Z","submitted_at":"2026-07-01T12:32:29Z","title":"EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection"},"reference_resolution":{"displayed":18,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":18},"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 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.00867."}