{"as_of":"2026-08-17T22:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f70aa3045c44518572189a988d933f40b39c1a227150d26fb2c6553d15c6d5d2","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":51,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":51,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":51,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":51,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:27:05.353547Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":404,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2303.18223","last_updated":"2026-03-18T05:34:39Z","snapshot_observed_at":"2026-08-14T10:40:26.323157Z","submitted_at":"2023-03-31T17:28:46Z","title":"A Survey of Large Language Models","version":19},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-10T22:46:39.268353Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2303.18223"},"observation_digest":"sha256:9b95d3cdf0d1f19ec6226ed65ccda4a6f539460c3cb8cff433ff571f97e0d43d","observation_id":"ef1f6618-09c3-4d83-9b72-8a3e9a64141e","resolution":{"observed_at":"2026-05-10T22:46:40.770736Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2311.05232","last_updated":"2024-11-19T12:42:45Z","snapshot_observed_at":"2026-07-06T16:45:07.733095Z","submitted_at":"2023-11-09T09:25:37Z","title":"A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-13T02:46:26.957539Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2311.05232"},"observation_digest":"sha256:d7bfa2a37d23dcaf8519dacc2eabaae4f26f9e2ca502af43c14b57a079979b73","observation_id":"4e7c9d58-1b5c-4dc6-a53b-c234a591fe48","resolution":{"observed_at":"2026-05-13T02:46:27.333553Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2402.01411","last_updated":"2026-05-19T14:24:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-02T13:42:50Z","title":"CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-24T03:58:32.556725Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2402.01411"},"observation_digest":"sha256:c9c96b015940819896dbb2a314b289e23940853f4095df69fa71788594c541d5","observation_id":"e70f0a54-434d-4363-9588-8a1573dd1880","resolution":{"observed_at":"2026-05-24T03:58:51.410600Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2402.17177","last_updated":"2024-04-17T18:41:39Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-27T03:30:58Z","title":"Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-13T13:43:11.024069Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2402.17177"},"observation_digest":"sha256:a0cb33663f63a1d67dbd7dd2b4eab96024ac003d5a971536a87c2241c496072b","observation_id":"a81e663b-9565-402c-9414-5a9097628057","resolution":{"observed_at":"2026-05-13T13:43:11.080540Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2406.14966","last_updated":"2026-04-08T10:36:46Z","snapshot_observed_at":"2026-08-02T08:24:58.145165Z","submitted_at":"2024-06-21T08:22:39Z","title":"Towards trustworthy management of AIGC copyright: blockchain-enabled full lifecycle recording and multi-party auditing approach","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-24T00:30:19.360716Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2406.14966"},"observation_digest":"sha256:64b791d4415f364d5c851dc8a8b3fee579504d4b3f70a1b485a020fa97386eb3","observation_id":"601c4446-f256-4198-a8c9-1e46b535853b","resolution":{"observed_at":"2026-05-24T00:33:40.064215Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-12T16:53:16.759919Z","title":"A comprehensive survey of ai -generated con- tent (aigc): A history of generative ai from gan to chatgpt,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13118","last_updated":"2024-11-20T08:26:40Z","snapshot_observed_at":"2026-08-13T13:46:22.854800Z","submitted_at":"2024-11-20T08:26:40Z","title":"Using ChatGPT-4 for the Identification of Common UX Factors within a Pool of Measurement Items from Established UX Questionnaires","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T16:53:16.759919Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2411.13118"},"observation_digest":"sha256:07e975a95edc3bee1fec99caa37657885811b8dc93d6d274bd047772804841c0","observation_id":"4634e1e2-09ef-458f-9505-4b3a4d31be10","resolution":{"observed_at":"2026-08-12T16:53:16.759919Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-12T16:52:58.956016Z","title":"A comprehensive survey of ai -generated con - tent (aigc): A history of generative ai from gan to chatgpt,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13616","last_updated":"2024-11-20T08:26:48Z","snapshot_observed_at":"2026-08-17T08:17:17.125475Z","submitted_at":"2024-11-20T08:26:48Z","title":"Identifying Semantic Similarity for UX Items from Established Questionnaires Using ChatGPT-4","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T16:52:58.956016Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2411.13616"},"observation_digest":"sha256:b40fbe7621ae3d2c711eb6bbc4683086f7af9fefcd8da6b201ba772eea96a02e","observation_id":"089af130-8543-4f24-b287-32d885412108","resolution":{"observed_at":"2026-08-12T16:52:58.956016Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-11T19:10:13.531108Z","title":"A compre- hensive survey of ai-generated content (aigc): A history of gen- erative ai from gan to chatgpt,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.07116","last_updated":"2024-12-10T02:06:10Z","snapshot_observed_at":"2026-08-16T04:07:17.817596Z","submitted_at":"2024-12-10T02:06:10Z","title":"A Review of Human Emotion Synthesis Based on Generative Technology","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T19:10:13.531108Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2412.07116"},"observation_digest":"sha256:023a12b2391edf625b1543b0d7999d7d65a6ca423a8e6d28a12a6958ca6186e6","observation_id":"727588f7-bb53-4b9c-af5f-003d597c6f26","resolution":{"observed_at":"2026-08-11T19:10:13.531108Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-11T12:12:18.260081Z","title":"A comprehensive survey of AI -generated content (AIGC) : A history of generative AI from gan to chatgpt","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.14538","last_updated":"2025-02-13T07:40:46Z","snapshot_observed_at":"2026-08-14T23:17:24.723143Z","submitted_at":"2024-12-19T05:36:34Z","title":"Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities","version":4},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-11T12:12:18.260081Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2412.14538"},"observation_digest":"sha256:b696fc06a374b03197680a068cd9c9f5bada1aa4ba774c40564694f107923dd5","observation_id":"cb554875-cb05-4908-9a44-9e94e1f7e746","resolution":{"observed_at":"2026-08-11T12:12:18.260081Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-11T12:10:13.351167Z","title":"Yu, and Lichao Sun","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.14554","last_updated":"2024-12-27T10:17:12Z","snapshot_observed_at":"2026-08-12T22:10:28.716468Z","submitted_at":"2024-12-19T06:10:40Z","title":"The Current Challenges of Software Engineering in the Era of Large Language Models","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T12:10:13.351167Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2412.14554"},"observation_digest":"sha256:64309f6ec3638b9710044b675ac72692ab3f9651c11c1e245a254ea88d1eda62","observation_id":"a776da10-776a-4f8a-8b33-d3c1db85bd2d","resolution":{"observed_at":"2026-08-11T12:10:13.351167Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-11T11:53:08.564445Z","title":"S.; and Sun, L","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.14902","last_updated":"2024-12-19T14:32:11Z","snapshot_observed_at":"2026-08-12T03:10:14.999284Z","submitted_at":"2024-12-19T14:32:11Z","title":"MagicNaming: Consistent Identity Generation by Finding a \"Name Space\" in T2I Diffusion Models","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-11T11:53:08.564445Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2412.14902"},"observation_digest":"sha256:6a13e621623dd8b61413859e1179f8d3acd89c806c2703009c0379a1686ded05","observation_id":"145e3692-f048-4b03-8ee7-76b57496d52d","resolution":{"observed_at":"2026-08-11T11:53:08.564445Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-11T04:59:29.417825Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18212","last_updated":"2024-12-24T06:40:13Z","snapshot_observed_at":"2026-08-17T14:41:38.044340Z","submitted_at":"2024-12-24T06:40:13Z","title":"Accelerating AIGC Services with Latent Action Diffusion Scheduling in Edge Networks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T04:59:29.417825Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2412.18212"},"observation_digest":"sha256:33021090c5e483f4c5666f653afa2cf63cdb48d4a5aff8fb5e8c4d263dc7b093","observation_id":"ff369787-9587-43b3-a230-77eb2966c4f6","resolution":{"observed_at":"2026-08-11T04:59:29.417825Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-10T21:57:16.004324Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.03203","last_updated":"2025-01-06T18:34:20Z","snapshot_observed_at":"2026-08-13T03:25:09.682338Z","submitted_at":"2025-01-06T18:34:20Z","title":"Detecting AI-Generated Text in Educational Content: Leveraging Machine Learning and Explainable AI for Academic Integrity","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T21:57:16.004324Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2501.03203"},"observation_digest":"sha256:017122f6842c70616c5659dbc5353a5c7acac6eeee7564e445dbba7f74c1cb00","observation_id":"7579a15a-325b-4ece-a88c-ece56f847d5e","resolution":{"observed_at":"2026-08-10T21:57:16.004324Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-10T20:52:33.528056Z","title":"S., and Sun, L","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.06929","last_updated":"2025-01-12T20:50:24Z","snapshot_observed_at":"2026-08-12T19:37:50.906030Z","submitted_at":"2025-01-12T20:50:24Z","title":"Why are we living the age of AI applications right now? The long innovation path from AI's birth to a child's bedtime magic","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-10T20:52:33.528056Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2501.06929"},"observation_digest":"sha256:57fbf86afa36b51b737cf0dc48e4d98bd67a9d96d9d5dce05aeb1c9f80a9ff28","observation_id":"905d4829-ca72-4085-a984-950cb2f9db09","resolution":{"observed_at":"2026-08-10T20:52:33.528056Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-10T15:18:21.773771Z","title":"arXiv preprint arXiv:2303.04226 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.14844","last_updated":"2026-08-13T16:11:08Z","snapshot_observed_at":"2026-08-16T23:11:43.554185Z","submitted_at":"2025-01-24T09:10:02Z","title":"Unmasking Conversational Bias in AI Multiagent Systems","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T15:18:21.773771Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2501.14844"},"observation_digest":"sha256:1be9068e5dd56989f96d93905c03211310e28c35e4dac3a8e763b4942ea31839","observation_id":"bee51250-402c-4a62-bfd1-256bdce059f9","resolution":{"observed_at":"2026-08-10T15:18:21.773771Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-10T12:25:31.028025Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16557","last_updated":"2025-01-27T22:57:39Z","snapshot_observed_at":"2026-08-16T05:38:07.148650Z","submitted_at":"2025-01-27T22:57:39Z","title":"CARING-AI: Towards Authoring Context-aware Augmented Reality INstruction through Generative Artificial Intelligence","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T12:25:31.028025Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2501.16557"},"observation_digest":"sha256:c476206dc0ccf2d26db2035e948cd5739e363bcd971b8b5819c448bf46c497a3","observation_id":"fd75cf7e-4b90-4af1-9d81-2bf301e524b9","resolution":{"observed_at":"2026-08-10T12:25:31.028025Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-10T10:58:29.023260Z","title":"A comprehensive survey of ai-generated content (AIGC): A history of generative AI from GAN to chatgpt,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16761","last_updated":"2025-01-28T07:32:07Z","snapshot_observed_at":"2026-08-16T17:49:12.890340Z","submitted_at":"2025-01-28T07:32:07Z","title":"CosyAudio: Improving Audio Generation with Confidence Scores and Synthetic Captions","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T10:58:29.023260Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2501.16761"},"observation_digest":"sha256:0abb3ce4da680e6617cbd96ddc4e662e0228b9375a8d305483f99fef0a50d931","observation_id":"87a576c1-be7e-4587-b609-03a9ddb171e3","resolution":{"observed_at":"2026-08-10T10:58:29.023260Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-10T00:36:46.254508Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18128","last_updated":"2025-01-30T04:20:16Z","snapshot_observed_at":"2026-08-14T08:56:55.129574Z","submitted_at":"2025-01-30T04:20:16Z","title":"Unraveling the Capabilities of Language Models in News Summarization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T00:36:46.254508Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2501.18128"},"observation_digest":"sha256:57b6939f35b30a8fb1e76735875fcd048da4c55b16c34018fa4bac9d06675f05","observation_id":"9cc5c167-b9df-48e6-8e46-efc9042a1bd3","resolution":{"observed_at":"2026-08-10T00:36:46.254508Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-09T00:44:51.891142Z","title":"https://doi.org/10.48550/arXiv.2303.04226 arXiv:2303.04226 [cs]","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.03804","last_updated":"2025-02-07T02:45:17Z","snapshot_observed_at":"2026-08-16T23:00:27.831835Z","submitted_at":"2025-02-06T06:27:09Z","title":"Understanding and Supporting Formal Email Exchange by Answering AI-Generated Questions","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-09T00:44:51.891142Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2502.03804"},"observation_digest":"sha256:66712aa940230b60704db4716a7a193b2d1241693209930f8d640d6403a0409b","observation_id":"05d65b20-ab8c-40d0-9269-dc2dc2e5a56f","resolution":{"observed_at":"2026-08-09T00:44:51.891142Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-09T18:23:40.537053Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.06803","last_updated":"2025-02-02T00:11:19Z","snapshot_observed_at":"2026-08-15T12:03:04.740914Z","submitted_at":"2025-02-02T00:11:19Z","title":"Emotion Recognition and Generation: A Comprehensive Review of Face, Speech, and Text Modalities","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T18:23:40.537053Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2502.06803"},"observation_digest":"sha256:e303e2e8aa4fa55c8684c4f4891720040a1615aefe327cf4ff8a089a2fd67eba","observation_id":"28059e98-a5dc-4817-b3d3-ee7e579d24b9","resolution":{"observed_at":"2026-08-09T18:23:40.537053Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-08T14:06:45.608850Z","title":"A comprehensive survey of ai-generated content (AIGC): A history of generative ai from gan to chatgpt","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.07007","last_updated":"2025-07-01T01:17:14Z","snapshot_observed_at":"2026-08-14T21:02:32.582951Z","submitted_at":"2025-02-10T20:13:16Z","title":"Grounding Creativity in Physics: A Brief Survey of Physical Priors in AIGC","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T14:06:45.608850Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2502.07007"},"observation_digest":"sha256:8e3cea36ca2ee469b9699f09ba8baa724b7bf372ce7d08805ae7e959bbd54fe7","observation_id":"9d7fb639-648c-46f1-8204-2869bf588f81","resolution":{"observed_at":"2026-08-08T14:06:45.608850Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2502.08921","last_updated":"2026-04-29T15:27:26Z","snapshot_observed_at":"2026-07-31T21:45:35.482040Z","submitted_at":"2025-02-13T03:15:18Z","title":"Detecting Malicious Concepts without Image Generation in AI-Generated Content (AIGC)","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-23T03:46:15.019944Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2502.08921"},"observation_digest":"sha256:d74141c75f58efb2a468f4afe35dffb208588d57790ef56246aa2727683c9daa","observation_id":"0865bab6-3b6b-4070-9cb0-01ec5961af41","resolution":{"observed_at":"2026-05-23T03:47:28.596545Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-16T11:27:05.353547Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.15552","last_updated":"2025-04-22T03:14:29Z","snapshot_observed_at":"2026-08-16T11:21:27.917623Z","submitted_at":"2025-04-22T03:14:29Z","title":"A Multi-Agent Framework for Automated Qinqiang Opera Script Generation Using Large Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T11:27:05.353547Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2504.15552"},"observation_digest":"sha256:fb80c9a3a670e077b4a7797e57b454bbd2bd67b231a47219f14a36bdba55955d","observation_id":"d606bea7-9f70-4290-9255-d893ce9034c1","resolution":{"observed_at":"2026-08-16T11:27:05.353547Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-15T21:49:12.809718Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt.arXiv preprint arXiv:2303.04226, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.08854","last_updated":"2025-05-13T17:59:20Z","snapshot_observed_at":"2026-08-16T20:35:49.762883Z","submitted_at":"2025-05-13T17:59:20Z","title":"Generative AI for Autonomous Driving: Frontiers and Opportunities","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-15T21:49:12.809718Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2505.08854"},"observation_digest":"sha256:19ff9bec154e9d57f952fb4a936e30c1ee42d62595e83389e88b16a1af136f1e","observation_id":"c39cc7e5-da1e-446f-86c2-379daf0740ec","resolution":{"observed_at":"2026-08-15T21:49:12.809718Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-15T21:26:43.383652Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.09872","last_updated":"2025-05-15T00:30:15Z","snapshot_observed_at":"2026-08-16T11:02:15.640845Z","submitted_at":"2025-05-15T00:30:15Z","title":"Context-AI Tunes: Context-Aware AI-Generated Music for Stress Reduction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T21:26:43.383652Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2505.09872"},"observation_digest":"sha256:9c70533a75fb2bb9593f9f2edb3ea2261b70acaa6a918fd28dcabaa857d2dad4","observation_id":"1dc880d4-03dc-4c32-a919-b8d83bd58d5f","resolution":{"observed_at":"2026-08-15T21:26:43.383652Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-07T14:46:34.591816Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt.arXiv preprint arXiv:2303.04226, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.17768","last_updated":"2025-07-20T01:08:18Z","snapshot_observed_at":"2026-08-16T17:53:59.588658Z","submitted_at":"2025-05-23T11:41:26Z","title":"R-Genie: Reasoning-Guided Generative Image Editing","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T14:46:34.591816Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2505.17768"},"observation_digest":"sha256:23cb02a47e58d770271cb2d577eaf483caa982c65a11bee33597d58325a616dd","observation_id":"b2158e25-d588-4187-81aa-6ce1386dbc29","resolution":{"observed_at":"2026-08-07T14:46:34.591816Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-07T13:16:58.953669Z","title":"arXiv preprint arXiv:2303.04226 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22306","last_updated":"2025-08-21T03:53:43Z","snapshot_observed_at":"2026-08-14T02:41:08.040759Z","submitted_at":"2025-05-28T12:45:39Z","title":"Versatile Cardiovascular Signal Generation with a Unified Diffusion Transformer","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T13:16:58.953669Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2505.22306"},"observation_digest":"sha256:46896a064661c9a045dd821439de02dc129cec4e0866db8791fcfc414323ff8a","observation_id":"f0d58c5e-6387-4051-b226-979318aa6afd","resolution":{"observed_at":"2026-08-07T13:16:58.953669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-07T11:44:14.885064Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt.arXiv preprint arXiv:2303.04226, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01591","last_updated":"2025-06-02T12:26:46Z","snapshot_observed_at":"2026-08-10T21:20:32.190957Z","submitted_at":"2025-06-02T12:26:46Z","title":"Silence is Golden: Leveraging Adversarial Examples to Nullify Audio Control in LDM-based Talking-Head Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:44:14.885064Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2506.01591"},"observation_digest":"sha256:285dde1687761c952b6366570bb00f2c5ffdb4583d2cbc2b6b60649474ab5d78","observation_id":"c1b45a53-fa21-447c-b667-d26fa4649800","resolution":{"observed_at":"2026-08-07T11:44:14.885064Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-07T11:22:43.210066Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.05384","last_updated":"2025-06-12T16:38:10Z","snapshot_observed_at":"2026-08-13T19:49:04.575670Z","submitted_at":"2025-06-03T10:11:51Z","title":"Q-Ponder: A Unified Training Pipeline for Reasoning-based Visual Quality Assessment","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:22:43.210066Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2506.05384"},"observation_digest":"sha256:063bc7fa052ce40ce76941aebea9d6724f49afef52e353017e71507343f88b16","observation_id":"2245206f-11ef-4b6d-80a0-ec5258b1c28b","resolution":{"observed_at":"2026-08-07T11:22:43.210066Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-07T04:47:18.011925Z","title":"S., and Sun, L","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13790","last_updated":"2025-08-20T13:47:47Z","snapshot_observed_at":"2026-08-10T01:31:14.540393Z","submitted_at":"2025-06-11T11:40:11Z","title":"The NordDRG AI Benchmark for Large Language Models","version":3},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T04:47:18.011925Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2506.13790"},"observation_digest":"sha256:2556623d118f29d0255132bc74791fb0d4baf2462e19b70eff6a160989fa758d","observation_id":"f0a069d9-389c-4f9c-bfc5-ef28c79e0ca8","resolution":{"observed_at":"2026-08-07T04:47:18.011925Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-07T00:27:19.498285Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14018","last_updated":"2025-06-16T21:30:42Z","snapshot_observed_at":"2026-08-14T19:11:08.060711Z","submitted_at":"2025-06-16T21:30:42Z","title":"\"I Cannot Write This Because It Violates Our Content Policy\": Understanding Content Moderation Policies and User Experiences in Generative AI Products","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T00:27:19.498285Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2506.14018"},"observation_digest":"sha256:b6772b6263fa381182f9e6929c5effcf33284cac22d3e20c3dd9b0c990f9387a","observation_id":"52649e71-ecd9-43ee-a15c-8ff09a3bc47d","resolution":{"observed_at":"2026-08-07T00:27:19.498285Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2506.17185","last_updated":"2026-04-06T21:18:48Z","snapshot_observed_at":"2026-07-06T21:45:20.732169Z","submitted_at":"2025-06-20T17:40:05Z","title":"A Common Pool of Privacy Problems: Legal and Technical Lessons from a Large-Scale Web-Scraped Machine Learning Dataset","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-19T08:18:48.936867Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2506.17185"},"observation_digest":"sha256:f9498c8e2255a95c509aaae76b1d8f9a24340a56197ced149c8cb3e758be8010","observation_id":"58f397d7-80ed-4ef8-8bf3-6691114e3d39","resolution":{"observed_at":"2026-05-19T08:22:11.140646Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-06T21:06:01.443843Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01154","last_updated":"2025-07-01T19:28:37Z","snapshot_observed_at":"2026-08-14T20:29:38.731467Z","submitted_at":"2025-07-01T19:28:37Z","title":"FlashDP: Private Training Large Language Models with Efficient DP-SGD","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T21:06:01.443843Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2507.01154"},"observation_digest":"sha256:5a34dfee971d49e18099f11439019b8f44651d05bb922840c7b91359e77de902","observation_id":"6af9995e-9755-4618-a8b3-e758743e2009","resolution":{"observed_at":"2026-08-06T21:06:01.443843Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-06T19:45:58.438153Z","title":"Yu, and Lichao Sun","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.05302","last_updated":"2025-07-07T06:29:57Z","snapshot_observed_at":"2026-08-14T21:34:50.636001Z","submitted_at":"2025-07-07T06:29:57Z","title":"CorrDetail: Visual Detail Enhanced Self-Correction for Face Forgery Detection","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T19:45:58.438153Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2507.05302"},"observation_digest":"sha256:104aea3fcfad62305d9ebb1539ceee4958e074e089936a737c643dc21d3c11dd","observation_id":"9d47626f-6f6e-4e3e-96b3-f897c1265385","resolution":{"observed_at":"2026-08-06T19:45:58.438153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-06T18:19:58.870967Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.08648","last_updated":"2025-07-11T14:51:33Z","snapshot_observed_at":"2026-08-16T16:20:47.419321Z","submitted_at":"2025-07-11T14:51:33Z","title":"DatasetAgent: A Novel Multi-Agent System for Auto-Constructing Datasets from Real-World Images","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T18:19:58.870967Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2507.08648"},"observation_digest":"sha256:8e67e2151ddb623cfcdbdb895f479a919b9cefe100773f253e3ba2fa28d0bd92","observation_id":"d8e23581-8848-41a1-a1f5-70cdf87dd3fa","resolution":{"observed_at":"2026-08-06T18:19:58.870967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-06T14:58:05.273006Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.17259","last_updated":"2025-07-23T06:56:34Z","snapshot_observed_at":"2026-08-14T05:10:17.092965Z","submitted_at":"2025-07-23T06:56:34Z","title":"Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:05.273006Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2507.17259"},"observation_digest":"sha256:7ca5c9f04390ccfa25875c1867fb3c1c19252aec7cbaa33c9d9bfe506d6bd059","observation_id":"2a1ea3ea-af9d-4eae-8cf8-6db15e4fc20b","resolution":{"observed_at":"2026-08-06T14:58:05.273006Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-06T14:45:20.585569Z","title":"Yu, and Lichao Sun","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.18006","last_updated":"2025-07-24T00:49:48Z","snapshot_observed_at":"2026-08-16T22:55:19.760355Z","submitted_at":"2025-07-24T00:49:48Z","title":"Unlock the Potential of Fine-grained LLM Serving via Dynamic Module Scaling","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T14:45:20.585569Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2507.18006"},"observation_digest":"sha256:eda30a61fa9210064fd0b6ef3743ccc1115d79f7716488f4dab65ebeb17b5350","observation_id":"55b91946-2e24-42ce-8a21-b0f42ff41d2e","resolution":{"observed_at":"2026-08-06T14:45:20.585569Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-06T14:07:28.790739Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt.arXiv preprint arXiv:2303.04226, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.19771","last_updated":"2025-07-26T03:47:12Z","snapshot_observed_at":"2026-08-09T08:28:14.343286Z","submitted_at":"2025-07-26T03:47:12Z","title":"Large Language Model Agent for Structural Drawing Generation Using ReAct Prompt Engineering and Retrieval Augmented Generation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T14:07:28.790739Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2507.19771"},"observation_digest":"sha256:415419853b2d1b9081c1b1cd32156181f86616da473d0332796ebfaffac72895","observation_id":"f33b25ff-311c-4f42-919a-1a89e8d6eeed","resolution":{"observed_at":"2026-08-06T14:07:28.790739Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-06T14:34:10.484346Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.21157","last_updated":"2025-07-24T22:05:52Z","snapshot_observed_at":"2026-08-14T02:53:48.252152Z","submitted_at":"2025-07-24T22:05:52Z","title":"Unmasking Synthetic Realities in Generative AI: A Comprehensive Review of Adversarially Robust Deepfake Detection Systems","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T14:34:10.484346Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2507.21157"},"observation_digest":"sha256:da5780f6de84adf479291c19e8af4a5b80206dc03ea0c1b6c41f6cf668ea4902","observation_id":"ed1c77d5-8447-4ff0-89e4-1b56446d4bf8","resolution":{"observed_at":"2026-08-06T14:34:10.484346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T20:20:12.168845Z","title":"S.; and Sun, L","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.10769","last_updated":"2025-08-14T15:55:19Z","snapshot_observed_at":"2026-08-17T13:55:44.574771Z","submitted_at":"2025-08-14T15:55:19Z","title":"Modeling Human Responses to Multimodal AI Content","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-05T20:20:12.168845Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2508.10769"},"observation_digest":"sha256:b2b1c82e17ff9f9a1392335a23231748b8c83a35d8a1341887fb330d216d573e","observation_id":"6c18a36c-c448-4e8d-b985-4c8f438bb7f1","resolution":{"observed_at":"2026-08-05T20:20:12.168845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-15T17:24:35.810701Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.16643","last_updated":"2025-08-18T11:02:32Z","snapshot_observed_at":"2026-08-17T00:27:29.928186Z","submitted_at":"2025-08-18T11:02:32Z","title":"From Classical Probabilistic Latent Variable Models to Modern Generative AI: A Unified Perspective","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T17:24:35.810701Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2508.16643"},"observation_digest":"sha256:5bb04f92ece1ba025c8e32e60876a152ca9d6c58b2f678b5f0bf893580085be1","observation_id":"3397e076-44ed-4b17-8ea4-950da318a90a","resolution":{"observed_at":"2026-08-15T17:24:35.810701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T15:24:11.648915Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.19882","last_updated":"2025-08-27T13:40:14Z","snapshot_observed_at":"2026-08-09T07:23:21.879760Z","submitted_at":"2025-08-27T13:40:14Z","title":"Generative AI for Testing of Autonomous Driving Systems: A Survey","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T15:24:11.648915Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2508.19882"},"observation_digest":"sha256:b099a493120b5e3bb512469e4d569fda9f6deee41ff0ec58971d65d9312656fa","observation_id":"d87ec4b4-ae20-4f70-b1e2-2354752a7b89","resolution":{"observed_at":"2026-08-05T15:24:11.648915Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T12:43:42.316384Z","title":"Yu, and Lichao Sun","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01314","last_updated":"2025-09-01T09:58:52Z","snapshot_observed_at":"2026-08-10T03:14:21.052478Z","submitted_at":"2025-09-01T09:58:52Z","title":"Can Smaller LLMs do better? Unlocking Cross-Domain Potential through Parameter-Efficient Fine-Tuning for Text Summarization","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-05T12:43:42.316384Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2509.01314"},"observation_digest":"sha256:fad304873f8d2940e5565fdaffade59109d36148ebc8eb502459cde476f8ca1f","observation_id":"2927ee4d-00a1-4704-9ef2-df545acd6fac","resolution":{"observed_at":"2026-08-05T12:43:42.316384Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T05:50:37.618103Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.04923","last_updated":"2025-09-05T08:41:24Z","snapshot_observed_at":"2026-08-17T20:24:40.929545Z","submitted_at":"2025-09-05T08:41:24Z","title":"Artificial intelligence for representing and characterizing quantum systems","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T05:50:37.618103Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2509.04923"},"observation_digest":"sha256:fb7a373a92838a8236fbc189f9af2554367abedc371b36aa342f7b187ffdbe4c","observation_id":"22f31255-b2e3-410f-8133-b14fa367cb11","resolution":{"observed_at":"2026-08-05T05:50:37.618103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2509.06027","last_updated":"2026-04-27T10:03:51Z","snapshot_observed_at":"2026-08-12T13:13:57.375681Z","submitted_at":"2025-09-07T12:06:21Z","title":"DreamAudio: Customized Text-to-Audio Generation with Diffusion Models","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-18T18:26:51.583145Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2509.06027"},"observation_digest":"sha256:f4551c0f7e264a6efa6f97f81c065491ed0485f52b5fcb84c33bf49781564a57","observation_id":"7642b494-c035-44cc-ac4a-b05c2e9aefa6","resolution":{"observed_at":"2026-05-18T18:31:44.735534Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2604.07486","last_updated":"2026-07-13T04:54:35Z","snapshot_observed_at":"2026-08-14T22:18:34.166494Z","submitted_at":"2026-04-08T18:26:34Z","title":"Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T17:31:30.510866Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2604.07486"},"observation_digest":"sha256:4da2b27d4c7a4ad3a8830f1e43f034ac89b8c10e74d5ce2a8266f692c1692499","observation_id":"ea51eeae-e5a5-450e-b288-9b9d6cd168fc","resolution":{"observed_at":"2026-05-11T06:41:10.516202Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-07-14T19:49:46.135987Z","title":"In NeurIPS 2019 Machine Learning with Guarantees Workshop","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2604.07486","last_updated":"2026-07-13T04:54:35Z","snapshot_observed_at":"2026-08-14T22:18:34.166494Z","submitted_at":"2026-04-08T18:26:34Z","title":"Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-14T19:49:46.135987Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2604.07486"},"observation_digest":"sha256:fe388a54db555c984f18076c61283555c044d7153b1d05312d7354b8560c965a","observation_id":"4b597498-9aea-4f3c-8829-6619f1989d05","resolution":{"observed_at":"2026-07-14T19:49:46.135987Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2604.08197","last_updated":"2026-04-09T12:55:19Z","snapshot_observed_at":"2026-08-11T12:25:31.490963Z","submitted_at":"2026-04-09T12:55:19Z","title":"Discrete Diffusion for Codebook-Based Beam Candidate Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T17:48:37.951942Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2604.08197"},"observation_digest":"sha256:d11e1a7d6ee0853fbe117b67d0a1db734f2a7a58b1a2c553fc726e9e00a0bd8c","observation_id":"014c4446-957c-490b-aae1-6cc143470ede","resolution":{"observed_at":"2026-05-11T06:05:57.907922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2606.02606","last_updated":"2026-05-23T15:56:16Z","snapshot_observed_at":"2026-08-13T13:09:03.610770Z","submitted_at":"2026-05-23T15:56:16Z","title":"ReLoRA: Knowledge-Reusing Adaptation for Fast Rollout of Evolving LLM Services","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-30T15:06:08.515588Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2606.02606"},"observation_digest":"sha256:7d0fa7706b0e69ebd1b5a561ffef5e1a0ba4499ef8f7fd70dc3f9ed898818fc1","observation_id":"d4e24df3-1016-46ed-9160-a9fcb611d0b9","resolution":{"observed_at":"2026-06-30T15:44:48.865449Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":"2303.04226","doi":"10.48550/arxiv.2303.04226","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt","venue":"arXiv (Cornell University)","work_id":"7eda166a-6bc6-48c3-be6c-f302e8014f50","year":2023},"citing_paper":{"arxiv_id":"2606.20173","last_updated":"2026-06-18T12:40:43Z","snapshot_observed_at":"2026-08-16T09:41:41.677616Z","submitted_at":"2026-06-18T12:40:43Z","title":"Qiskit Code Migration with LLMs","version":1},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-06-26T16:24:25.357338Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2606.20173"},"observation_digest":"sha256:b1d2dd0ee59111e2d2d93f41b18660736a6df6a2f511f3e05c1ad50982abee4b","observation_id":"1476c24f-f568-4db4-822a-e4bd4eb8b386","resolution":{"observed_at":"2026-06-26T16:29:35.705863Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04226","snapshot_observed_at":"2026-07-11T13:32:25.037160Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04786","last_updated":"2026-07-06T08:20:04Z","snapshot_observed_at":"2026-08-07T04:06:58.858273Z","submitted_at":"2026-07-06T08:20:04Z","title":"An Exploration of Agentic Information Fusion for Test Maintenance Prediction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-11T13:32:25.037160Z"},"links":{"cited_paper":"/paper/2303.04226","citing_paper":"/paper/2607.04786"},"observation_digest":"sha256:e7a0e1eafa74f1b0c426f63e00992309c62eceaaac79d584efd539dc14321a12","observation_id":"eacdcb20-857b-4fe6-a9e8-6a30f3b0f0b3","resolution":{"observed_at":"2026-07-11T13:32:25.037160Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2303.04226/citation-record","integrity":"/paper/2303.04226/integrity","json":"/paper/2303.04226/citation-record.json","paper":"/paper/2303.04226"},"outbound":[],"paper":{"arxiv_id":"2303.04226","last_updated":"2023-03-07T20:36:13Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-16T15:50:00.319562Z","submitted_at":"2023-03-07T20:36:13Z","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 51 inbound Pith citation observations for arXiv:2303.04226."}