{"as_of":"2026-08-13T23:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4f9beb0a75cbdd91ea4a0da201cf1f07aa700f83b5bffaca44bc5c44a25882c1","coverage":[{"denominator":16,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T14:58:44.224235Z","state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+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/2507.17204/citation-record","integrity":"/paper/2507.17204/integrity","json":"/paper/2507.17204/citation-record.json","paper":"/paper/2507.17204"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-06T14:58:42.953734Z","title":"Preprint, arXiv:2310.06825","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:42.953734Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:669846517e1b342c32a9a7ff7c4121be9d51970f8050a0204f62702a43585b70","observation_id":"988356ee-b128-436c-a8ef-0b97bc76ba13","resolution":{"observed_at":"2026-08-06T14:58:42.953734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15251","last_updated":"2026-05-03T08:23:53Z","snapshot_observed_at":"2026-08-04T21:47:49.059504Z","submitted_at":"2024-12-15T04:58:00Z","title":"IPS: In-Prompt Process Supervision for Short Video Content Moderation","version":3},"cited_work":{"arxiv_id":"2412.15251","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.15251","snapshot_observed_at":"2026-08-06T14:58:45.182956Z","title":"IPS: In-Prompt Process Supervision for Short Video Content Moderation","venue":"cs.CL","work_id":"dd129742-7e52-40a5-863a-03a303c87704","year":2024},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:43.065453Z"},"links":{"cited_paper":"/paper/2412.15251","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:2e0c8e58d310827dfcd2b2a577ba966e6ae2b021ff013119a969c8c8ad4a6a83","observation_id":"e0a3a464-39ed-4780-8357-e9719c8c46eb","resolution":{"observed_at":"2026-08-06T14:58:45.318999Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03400","last_updated":"2024-03-07T12:04:54Z","snapshot_observed_at":"2026-08-13T22:06:07.144949Z","submitted_at":"2023-10-05T09:09:44Z","title":"Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.03400","snapshot_observed_at":"2026-08-06T14:58:43.165069Z","title":"arXiv preprint arXiv:2310.03400","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:43.165069Z"},"links":{"cited_paper":"/paper/2310.03400","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:cd221cc70c7f16272cc972301b1a3f78f8eec99c31469cc319f327f5281235e1","observation_id":"71de29d7-7c0f-430c-8a2d-0990e53459ca","resolution":{"observed_at":"2026-08-06T14:58:43.165069Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.00142","last_updated":"2025-06-09T17:01:06Z","snapshot_observed_at":"2026-08-13T01:49:12.898890Z","submitted_at":"2024-11-28T18:55:41Z","title":"Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.00142","snapshot_observed_at":"2026-08-06T14:58:43.281185Z","title":"Preprint, arXiv:2412.00142","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:43.281185Z"},"links":{"cited_paper":"/paper/2412.00142","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:8ac7fe0da41cf6f9b0623f369d4e95c2217e848409cf23a9b24b1d332c3fdbcb","observation_id":"f39de5d2-e178-4293-996e-9311c4bec4e9","resolution":{"observed_at":"2026-08-06T14:58:43.281185Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T14:58:43.372402Z","title":"Preprint, arXiv:2303.08774","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:43.372402Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:b4150183c58228e54c4b65190a4e7effbd79049a9b722172bc09b6e9f0ebf107","observation_id":"23627c4d-aaaf-44fb-9531-01c815843b04","resolution":{"observed_at":"2026-08-06T14:58:43.372402Z","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":"2026-08-06T14:58:45.667751Z","title":"In Findings of the Association for Computational Linguistics: ACL 2024, pages 5735– 5748, Bangkok, Thailand","venue":null,"work_id":"9ed3e3f8-0fee-453f-92ae-ac2941fd4f2f","year":2024},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:43.401718Z"},"links":{"citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:1895cc529d6328ebc286012dd50fa037c2a9f9206f42e1e00db44b8dfacb33e8","observation_id":"67ba5547-cdf6-48cf-a087-e56304231486","resolution":{"observed_at":"2026-08-06T14:58:45.799257Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.13337","last_updated":"2024-12-17T21:16:59Z","snapshot_observed_at":"2026-08-11T13:11:55.344762Z","submitted_at":"2024-12-17T21:16:59Z","title":"Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13337","snapshot_observed_at":"2026-08-06T14:58:43.493356Z","title":"Preprint, arXiv:2412.13337","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:43.493356Z"},"links":{"cited_paper":"/paper/2412.13337","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:c9e338ea81ec85f80513867d26dd4e98488af64921d9d997239a5cb1725cd042","observation_id":"afba8959-19d8-42b6-9574-00a5845b1a6e","resolution":{"observed_at":"2026-08-06T14:58:43.493356Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18216","last_updated":"2025-01-20T06:04:13Z","snapshot_observed_at":"2026-08-13T20:41:30.147685Z","submitted_at":"2024-12-24T06:45:36Z","title":"ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation","version":2},"cited_work":{"arxiv_id":"2412.18216","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.18216","snapshot_observed_at":"2026-08-06T14:58:44.939381Z","title":"ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation","venue":"cs.CV","work_id":"f35e9300-4232-42f4-ba34-ae8f31c84205","year":2024},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:43.582211Z"},"links":{"cited_paper":"/paper/2412.18216","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:9658ba8394ffd1038b1853f936e01671657fe4ad168a857e8d8c1b7cf7bb82a7","observation_id":"a1087e48-b2b8-41dd-92b6-02c36f16c4de","resolution":{"observed_at":"2026-08-06T14:58:45.040986Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.14717","last_updated":"2025-03-08T13:10:57Z","snapshot_observed_at":"2026-08-12T14:57:01.583683Z","submitted_at":"2024-11-22T04:09:23Z","title":"FedMLLM: Federated Fine-tuning MLLM on Multimodal Heterogeneity Data","version":2},"cited_work":{"arxiv_id":"2411.14717","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.14717","snapshot_observed_at":"2026-08-06T14:58:44.663781Z","title":"FedMLLM: Federated Fine-tuning MLLM on Multimodal Heterogeneity Data","venue":"cs.LG","work_id":"f38dd412-98ed-4a0d-a210-82ff4520a09d","year":2024},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:43.734247Z"},"links":{"cited_paper":"/paper/2411.14717","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:ed340a237bd9423381da51ef4b5e964d2ecee3df16be8a1d675fe2be33591b4a","observation_id":"50e0c0df-1fa7-4c8f-b19f-bb0dcda53901","resolution":{"observed_at":"2026-08-06T14:58:44.850381Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.10674","last_updated":"2025-02-15T08:31:04Z","snapshot_observed_at":"2026-08-11T15:41:24.396483Z","submitted_at":"2024-12-14T04:22:09Z","title":"USM: Unbiased Survey Modeling for Limiting Negative User Experiences in Recommendation Systems","version":3},"cited_work":{"arxiv_id":"2412.10674","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.10674","snapshot_observed_at":"2026-08-06T14:58:44.423351Z","title":"USM: Unbiased Survey Modeling for Limiting Negative User Experiences in Recommendation Systems","venue":"cs.IR","work_id":"85813227-9b59-40d7-95c4-b65177170acb","year":2024},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:43.858080Z"},"links":{"cited_paper":"/paper/2412.10674","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:d95f437ecf6a67824ea0fa3d5b578742c09666eec8cae3a3970947dfc4a3f5c8","observation_id":"962b06d7-7772-4a20-b809-db75de7a2320","resolution":{"observed_at":"2026-08-06T14:58:44.559603Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18415","last_updated":"2024-11-03T18:23:45Z","snapshot_observed_at":"2026-08-12T23:55:53.030179Z","submitted_at":"2024-05-28T17:57:06Z","title":"Why are Visually-Grounded Language Models Bad at Image Classification?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18415","snapshot_observed_at":"2026-08-06T14:58:44.118082Z","title":"Xiongtao Zhou, Jie He, Yuhua Ke, Guangyao Zhu, Vic- tor Gutierrez Basulto, and Jeff Pan","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:44.118082Z"},"links":{"cited_paper":"/paper/2405.18415","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:4ff329b924d3b86be4a07305455f2a0fceac1fe02d9d70d0154ff6dfe904fb33","observation_id":"5b47dfc0-6f42-40af-9456-f23975f858c7","resolution":{"observed_at":"2026-08-06T14:58:44.118082Z","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":"2026-08-06T14:58:45.509582Z","title":"In Findings of the Association for Computational Linguistics: ACL 2024, pages 10057–10084, Bangkok, Thailand","venue":null,"work_id":"78925c3d-d59a-4c7a-aa3f-8bdd8031e6a3","year":2024},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:44.224235Z"},"links":{"citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:af6ef0f10805e65d21d88465c4cca8d2e612108c37c54065c413746adccc45f7","observation_id":"9a19600b-785c-4f81-89fa-571c33ae0777","resolution":{"observed_at":"2026-08-06T14:58:45.567416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.08276","last_updated":"2022-06-01T16:45:09Z","snapshot_observed_at":"2026-08-13T21:23:52.134746Z","submitted_at":"2021-11-16T07:55:26Z","title":"Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.08276","snapshot_observed_at":"2026-08-06T14:58:44.002049Z","title":"Preprint, arXiv:2111.08276","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:44.002049Z"},"links":{"cited_paper":"/paper/2111.08276","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:e9c08e6a23fbdf59f2206dab321a897a131088de6876def567056fb26bf70c25","observation_id":"e4f707dc-4835-4fa4-8c53-b371b38b35ad","resolution":{"observed_at":"2026-08-06T14:58:44.002049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-08-13T15:58:13.809876Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-06T14:58:42.783915Z","title":"In Proceedings of the International AAAI Conference on Web and Social Media , volume 17, pages 1014–1023","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:42.783915Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:20a81dfa0ce05192870bfd957e7580fbb3587cb915e3626d6a2be67d853bff88","observation_id":"37823ac5-a2e9-497d-9586-7e39cc2bea91","resolution":{"observed_at":"2026-08-06T14:58:42.783915Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21439","last_updated":"2024-09-25T06:14:03Z","snapshot_observed_at":"2026-08-12T23:11:23.137709Z","submitted_at":"2024-07-31T08:43:17Z","title":"MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21439","snapshot_observed_at":"2026-08-06T14:58:42.431248Z","title":"arXiv preprint arXiv:2407.21439","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:42.431248Z"},"links":{"cited_paper":"/paper/2407.21439","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:c9ab5402ca6b1dd18855c6daedad82f792211bcb96f9d5bfffa60570241f2dc1","observation_id":"455e2a99-45a1-4abe-8724-6e181a5c3fde","resolution":{"observed_at":"2026-08-06T14:58:42.431248Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.15795","last_updated":"2025-01-27T05:41:10Z","snapshot_observed_at":"2026-08-12T04:51:48.558507Z","submitted_at":"2025-01-27T05:41:10Z","title":"Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.15795","snapshot_observed_at":"2026-08-06T14:58:42.623068Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:42.623068Z"},"links":{"cited_paper":"/paper/2501.15795","citing_paper":"/paper/2507.17204"},"observation_digest":"sha256:a7f4f2e89aa36a7847cbe9b8ee0131fb40a9bda8b76a344561977a69365ef5f0","observation_id":"57437c8c-ddc2-45a8-aa45-aa22c5afefaa","resolution":{"observed_at":"2026-08-06T14:58:42.623068Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.17204","last_updated":"2025-07-23T04:52:58Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-11T08:04:18.265008Z","submitted_at":"2025-07-23T04:52:58Z","title":"Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation"},"reference_resolution":{"displayed":16,"state_counts":{"malformed_identifier":0,"metadata_mismatch":4,"parse_uncertain":0,"unresolved":10,"verified_exact":0,"verified_fuzzy":2},"total_outbound_references":16},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2507.17204."}