{"as_of":"2026-08-07T15:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5d88f667d7f8597f436becdb8b95559b8f02d8dcd7149f233055e5f58f7879ae","coverage":[{"denominator":64,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":64,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-17T04:39:59.601872Z","state":"measured"},{"denominator":67,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":67,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T04:54:12.975689Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-05-13T07:47:32.654801Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2511.20211","doi":null,"metadata_source":"pith","pith_arxiv_id":"2511.20211","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","venue":"cs.CV","work_id":"d0052b04-1fd5-4c29-a8a7-3f446b8ab96a","year":2025},"citing_paper":{"arxiv_id":"2605.00658","last_updated":"2026-05-01T13:40:56Z","snapshot_observed_at":"2026-07-06T23:14:01.852096Z","submitted_at":"2026-05-01T13:40:56Z","title":"UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-05-09T20:05:21.723724Z"},"links":{"cited_paper":"/paper/2511.20211","citing_paper":"/paper/2605.00658"},"observation_digest":"sha256:593ef00571553c8da873bfcbb18b24927e773a7ec53e8f6dbe5ade43bfb4584e","observation_id":"6f829126-1dea-44b4-9650-9dcb2cf20a98","resolution":{"observed_at":"2026-05-11T15:26:07.681619Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2511.20211","doi":null,"metadata_source":"pith","pith_arxiv_id":"2511.20211","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","venue":"cs.CV","work_id":"d0052b04-1fd5-4c29-a8a7-3f446b8ab96a","year":2025},"citing_paper":{"arxiv_id":"2605.11818","last_updated":"2026-05-12T09:09:01Z","snapshot_observed_at":"2026-08-02T21:46:06.216835Z","submitted_at":"2026-05-12T09:09:01Z","title":"RevealLayer: Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-05-13T07:46:50.540528Z"},"links":{"cited_paper":"/paper/2511.20211","citing_paper":"/paper/2605.11818"},"observation_digest":"sha256:21acca4d90459fa9dc94fafebd8aadb2315f5cff298e67cd2b9b988484a506ae","observation_id":"3422b8dd-b557-42f6-9929-6deee96900a8","resolution":{"observed_at":"2026-05-13T07:47:32.657564Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.20211","snapshot_observed_at":"2026-08-05T04:54:12.975689Z","title":"Omnialpha: Aligning transparency-aware generation via multi-task unified reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.03971","last_updated":"2026-08-04T17:39:37Z","snapshot_observed_at":"2026-08-07T14:34:37.855418Z","submitted_at":"2026-08-04T17:39:37Z","title":"UniWorld-Design: From Pixel Generation to Layer-Native Design","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T04:54:12.975689Z"},"links":{"cited_paper":"/paper/2511.20211","citing_paper":"/paper/2608.03971"},"observation_digest":"sha256:33386586b319b0de3400b2ffe8b963863993c1a8431d73a8dff6d6179e181c82","observation_id":"e7d9d0e7-1eb4-468c-9a20-922e84e9b1d3","resolution":{"observed_at":"2026-08-05T04:54:12.975689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2511.20211/citation-record","integrity":"/paper/2511.20211/integrity","json":"/paper/2511.20211/citation-record.json","paper":"/paper/2511.20211"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Transmat- ting: Enhancing transparent objects matting with transform- ers","venue":null,"work_id":"4acadbd0-52f0-4d68-ae93-218bfe14d680","year":2022},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:e77f41b949107c84e4e29ec9fb9784032e0421e4bff0f2548bcabe8bcc51c866","observation_id":"d506e95d-0026-4691-9ae4-a0c34929fa0e","resolution":{"observed_at":"2026-05-17T04:41:31.798669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Prismlayers: Open data for high-quality multi-layer transpar- ent image generative models","venue":null,"work_id":"ed957808-0b62-4cb5-a708-c9b9921231d0","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:e53bee2128d8d91d585f122de9f2417c86efc53488608bf24dddd42044e6171b","observation_id":"fb0138c3-d464-4e8c-a79b-3601b1fffebd","resolution":{"observed_at":"2026-05-17T04:41:31.805117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Layerfusion: Harmo- nized multi-layer text-to-image generation with generative priors","venue":null,"work_id":"e5b34465-43a4-45bd-b23c-06eb546e49ea","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:c8a67ce57b0fd5fc850525349caf990bf1344e2e83e07a1e19bbd1aafb29b6f4","observation_id":"29fe988f-fefd-4799-a6fc-a17d574f9a0d","resolution":{"observed_at":"2026-05-17T04:41:31.799891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Puma: Empowering unified mllm with multi-granular visual generation","venue":null,"work_id":"dd1c918c-492b-4ffe-b08d-a117a2896fbf","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:4a639b140d59e91cae36b50c3939ba5915f9506cee69615fb83b4b02b73612be","observation_id":"08b15eda-5de8-4e04-86f7-100c8f4a0dde","resolution":{"observed_at":"2026-05-17T04:41:31.807783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Haralick, Stanley R","venue":null,"work_id":"fca7fd0e-1f84-4859-be77-1be11a583dbb","year":1987},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:8994d4642bece567d3c40e0b663d312b1903fc6cfa88c0b91824603aba40d718","observation_id":"ad161aea-3345-46c2-9332-e4eec8923c86","resolution":{"observed_at":"2026-05-17T04:41:31.810505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T07:06:04.158752Z","title":"Denoising diffu- sion probabilistic models","venue":null,"work_id":"e2b19783-b26f-40e8-ad60-dbe8f7ca807e","year":2020},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:11af453bcc0fd17662f1c2c185e6621bdcc28f92faba862bd6a16fc14e315798","observation_id":"f947a4e6-012c-4230-840d-c6db810efd0d","resolution":{"observed_at":"2026-05-17T04:41:31.795693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen","venue":null,"work_id":"30ce698a-e400-4464-a70f-6d773ea5f7b4","year":2021},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:6232e7d8de77e8a7b40c605afdd51b685e34b9ba8166ed5e350c174be6a7bcef","observation_id":"844d0b33-b707-4384-99a5-fb0bca3d1578","resolution":{"observed_at":"2026-05-17T04:41:31.793343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Diffusion for natural image matting","venue":null,"work_id":"b180a0a3-e546-4d71-ac1a-3ea2534e79ec","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:f1a2a68d334926702b1535ea51a23b9b7de93e905672af04d9ef2cda74b22e5f","observation_id":"ae720cfb-f8fb-47a5-9055-34666b7cc4ce","resolution":{"observed_at":"2026-05-17T04:41:31.795480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Psdiffusion: Harmonized multi-layer image generation via layout and appearance alignment","venue":null,"work_id":"015f2fe4-544d-4472-bfb1-989db6038eed","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:7865f0736fe53dd7c04e00a6a042766bf69db7a98f9bd4c58dec218b2968ad70","observation_id":"3ad08d95-7383-49d9-a49a-ebab546e13bf","resolution":{"observed_at":"2026-05-17T04:41:31.792978Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dream- layer: Simultaneous multi-layer generation via diffusion mode","venue":null,"work_id":"42980a83-9dfa-4e05-ba8b-d3a50d02a78d","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:59208cd4bd2f093b8ff8935a9a3c75fb3fbf813ac2c0244706a2093f9dc5c75c","observation_id":"06fc696e-95a1-4658-8bcc-0bb994258113","resolution":{"observed_at":"2026-05-17T04:41:31.783395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Designedit: Multi-layered latent decomposition and fusion for unified & accurate image editing","venue":null,"work_id":"fec0058e-1eb2-4cbf-89e3-954112714522","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:65ea6b80ad0528f9c21f86c7fa3feb4703e8786a1f89009921b1171cacca3a00","observation_id":"84982090-1ac3-4953-8488-fc3fd21a2bc7","resolution":{"observed_at":"2026-05-17T04:41:31.801896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Auto-encoding varia- tional bayes","venue":null,"work_id":"8dd84326-b935-4f5b-8539-60b35be469b6","year":2022},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:98af1a9736f61635f2c8d3d8573729ba15213c06973ef81e1add828297f626f9","observation_id":"fccfc506-aad6-42dc-94cf-64f5ffc5ecad","resolution":{"observed_at":"2026-05-17T04:41:31.773646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Flux.1 kontext: Flow matching for in-context image generation and editing in latent space","venue":null,"work_id":"092aed36-c711-4997-9f18-5033448a2dd1","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:6c778ec5b7c7fb6d14b89327ce55879279170d36a185a0718554f686e3a6c4b1","observation_id":"33bcdaed-d321-4906-8439-e891bf21a6ee","resolution":{"observed_at":"2026-05-17T04:41:31.749953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Privacy- preserving portrait matting","venue":null,"work_id":"0eb184cc-ec0f-4570-83f2-e0013591680b","year":2021},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:9cf1a3742a760aef11e75b219dae16b5118948521120cc80a455ff777da38959","observation_id":"f5c3b344-1c6b-4056-83ae-20d69a3eb181","resolution":{"observed_at":"2026-05-17T04:41:31.768657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Maybank, and Dacheng Tao","venue":null,"work_id":"a1b8377c-edf9-4852-8c8e-fc137d17db61","year":2021},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:ab02cd5215635cfb44d2a75f4803358033821da85623a2e3d9c3006280edfd19","observation_id":"10119069-4981-4f66-9214-976457dd7db6","resolution":{"observed_at":"2026-05-17T04:41:31.732930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep automatic natural image matting","venue":null,"work_id":"2f086253-c0bc-41b4-acf7-e7d88ee20dbd","year":2021},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:14fd0e2bd28d357cfb39cbd072f82ed76ea3b7d846112558bda398aa161a5468","observation_id":"dbf2328b-27c2-4034-8027-53fb3b165400","resolution":{"observed_at":"2026-05-17T04:41:31.730436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Matting anything","venue":null,"work_id":"a3bc75b0-ba0d-4ede-ab2e-afdb06c6add1","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:a6143c3e70e2a4aabc73a2cd8f1982540ae4b82470b775fb04aa116298ea118f","observation_id":"bd534404-51ca-4aa2-8d78-66d6255bbeef","resolution":{"observed_at":"2026-05-17T04:41:31.711318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Referring image matting","venue":null,"work_id":"d827ae74-7a05-49ff-877b-9df30adba944","year":2023},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:4b9aa8f814d3b80148339b2b87f7eec21a739ad7c8b67f82394a7873f21c6e63","observation_id":"ea29a692-69ab-4acb-a7d3-fe9e3895abae","resolution":{"observed_at":"2026-05-17T04:41:31.673854Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Drip: Unleashing diffusion priors for joint foreground and alpha prediction in image matting.Advances in Neural Information Processing Systems 37","venue":null,"work_id":"0bf0fe75-1681-4687-bf78-85d116be0ea8","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:03aa6a7301938dac14463beb4db98ebb0cd02c03d9e55aba95aefa0591c37fc3","observation_id":"26861af9-de85-43c5-89fb-0b312e198f5c","resolution":{"observed_at":"2026-05-17T04:41:31.747503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Visualcloze: A universal image generation framework via visual in-context learning","venue":null,"work_id":"16faf125-00a7-421d-a63b-bbd3dea37a3d","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:139260c70e788d3d15387808211502bf590626f9e443db10b1306d26685b7f7f","observation_id":"d2c286c9-8093-4923-8ade-2c1f9eed013b","resolution":{"observed_at":"2026-05-17T04:41:31.758768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Real-time high-resolution background matting","venue":null,"work_id":"d5768e94-d12d-4fc3-aa13-0cfb214b6af7","year":2020},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:942a70f134c51c6e5bbb6e9e4adbc181c9dede706a52fbef86426cb6f7a625b8","observation_id":"5ed4f575-eb2f-442b-b584-2b5213c3934f","resolution":{"observed_at":"2026-05-17T04:41:31.763417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tripartite information mining and inte- gration for image matting","venue":null,"work_id":"09739292-ae78-43cb-8fca-b0acd572455f","year":2021},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:2cd8d7aac85b615476995ee493b3ac2dee4a2765fee0439fc7a8f0b10efd8f47","observation_id":"64cde491-c943-4142-b877-afa190d50333","resolution":{"observed_at":"2026-05-17T04:41:31.686700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":"1711.05101","doi":"10.1137/1.9781611972825.47","metadata_source":"pith","pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Decoupled Weight Decay Regularization","venue":"cs.LG","work_id":"07ef7360-d385-4033-83f7-8384a6325204","year":2017},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:9245cd815e799895602f5a140a12125314a8d935baead931ac15344a4ad9e1a7","observation_id":"dd6d489a-b226-497b-ab1e-c8e7711134b6","resolution":{"observed_at":"2026-05-17T04:41:31.457968Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Gpt-4 technical report","venue":null,"work_id":"e2ff7f2c-b03c-4f52-ab03-5fc244262efb","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:b9c886f97948badf7edf9376ff5a14ff1f72dfb1e14de9c0d720989651bba076","observation_id":"b7128ef2-6939-4aec-82e2-a0f164bad484","resolution":{"observed_at":"2026-05-17T04:41:31.694128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scalable diffusion models with transformers","venue":null,"work_id":"bb7f8403-839f-40c9-a83b-f2f8d796aece","year":2023},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:b1657aa6ff2f519e3df42958847040bd3a7ef1cffdc13a3f07f64e054b25fb8b","observation_id":"a726868e-6315-4928-86e2-14a8271cfa55","resolution":{"observed_at":"2026-05-17T04:41:31.762934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Art: Anonymous re- gion transformer for variable multi-layer transparent image generation","venue":null,"work_id":"c2b9d65c-e183-4620-8d65-d74edb5f3961","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:6caaec94e634fe0181a3e6786f370d1d9e37731735fffa510254d3893318e9ed","observation_id":"b88e4eda-79c2-40b6-971e-80e3b8bb3c4a","resolution":{"observed_at":"2026-05-17T04:41:31.661144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Attention-guided hi- erarchical structure aggregation for image matting","venue":null,"work_id":"17a829f0-595f-4b80-a381-d14e1cffd802","year":2020},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:8fc9eb121d2bb13c5c374e1167abac6cbb0e9712f2dedf6984981dfab7302dc0","observation_id":"7b0d2d53-13cd-428c-87e6-e4bcd2b6374e","resolution":{"observed_at":"2026-05-17T04:41:31.760007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Alfie: Democratising rgba image generation with no $$$","venue":null,"work_id":"3795c14b-3b7e-4edb-8610-fb38c9419e50","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:ad00b9672a2d2ac93b6d5d24277f2485e81a9ae40df35864eefad1d6286889ed","observation_id":"b3c17d4e-72d8-43e4-9b72-58ac882dd5ac","resolution":{"observed_at":"2026-05-17T04:41:31.737645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"bee674db-bdb8-480a-a4a1-e3a8da761d5b","year":2022},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:7af3164dd1fa2a27646da784b5d5c85e6874b13a5a5bcad2a2751162bcb00d9c","observation_id":"6eca63dc-88bd-4dbd-99c4-6d2fcb79feef","resolution":{"observed_at":"2026-05-17T04:41:31.743184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Rord: A real-world object removal dataset","venue":null,"work_id":"33f448a0-856c-4413-b457-c93902cd3d0f","year":2022},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:8d2d94097632664bfe968b9deeeec48d991b95249d649c7d92a95e1dbe0564cc","observation_id":"275a0b30-8dcd-4ec8-bc5a-4a7adbc10d93","resolution":{"observed_at":"2026-05-17T04:41:31.745150Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063","venue":null,"work_id":"d1af47bd-dd90-4dff-826b-302fd98831d3","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:a78a2bfdfd7b43de8fa0054099fbd5d336ff56872bd36b318f28d3a23052a0fa","observation_id":"34b78ed5-e619-45a5-990b-b3af408fe6ac","resolution":{"observed_at":"2026-05-17T04:41:31.752262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Semantic image matting","venue":null,"work_id":"9c9d5e7b-8d75-4b6e-ac1b-6296cdbf2c8b","year":2021},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:20f78ce3a49c8b15a6b9441ad0ba2f36c82e71d4c650984800e62b85e0df1462","observation_id":"7dd719bb-7727-49be-8c44-67b21260121c","resolution":{"observed_at":"2026-05-17T04:41:31.756633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ultrahigh resolution image/video matting with spatio-temporal sparsity","venue":null,"work_id":"0d4e6de6-3081-4f20-9e98-0714d33b4d96","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:33c3946f59de23283f700a29ad4eb5cabefbb195ad12a8a7401da42423e6f1e8","observation_id":"a13fa32b-03c7-4d1e-8fd8-104611d009d4","resolution":{"observed_at":"2026-05-17T04:41:31.735421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Qwen3 technical report","venue":null,"work_id":"b3488ffb-cea8-4729-8826-2f847232936f","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:7c8a5a1084bed706cd98674ceb7820752d0661e019736e8b3ccc2148792854fb","observation_id":"2deedf0d-fec8-4cf2-833d-fd780278584c","resolution":{"observed_at":"2026-05-17T04:41:31.767182Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.09308","last_updated":"2025-07-12T14:53:42Z","snapshot_observed_at":"2026-08-06T17:56:34.980177Z","submitted_at":"2025-07-12T14:53:42Z","title":"AlphaVAE: Unified End-to-End RGBA Image Reconstruction and Generation with Alpha-Aware Representation Learning","version":1},"cited_work":{"arxiv_id":"2507.09308","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.09308","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Alphavae: Unified end-to-end rgba image reconstruction and generation with alpha-aware representation learning.arXiv preprint arXiv: 2507.09308","venue":null,"work_id":"abf59af8-15e6-4dfc-8114-b06e3e37b43c","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"cited_paper":"/paper/2507.09308","citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:befd543be2135d4db3e17b679d3f6a91512e22245ff4ed8be2ea18288f0b7885","observation_id":"94afaf5c-ba71-4292-9f72-a596a9c5d8b4","resolution":{"observed_at":"2026-05-17T04:41:31.454322Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Objectdrop: Bootstrap- ping counterfactuals for photorealistic object removal and insertion","venue":null,"work_id":"585948cb-f975-4ed8-89bd-37ccda265955","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:a999a3bd3cf307f5c3164b01f5366bacf0a71adae6a96e0aafb8642fa432c296","observation_id":"b07d63cf-48a1-45dd-9847-4e77bc812150","resolution":{"observed_at":"2026-05-17T04:41:31.727498Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Qwen-image technical report","venue":null,"work_id":"27961bac-752c-4ca3-a7bf-70c5d3e10e00","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:61d0e24501878780538d91c386b4d9108c5cb365f41070803f065a9fece2c91d","observation_id":"46268575-6365-4447-a157-ea51085eb10c","resolution":{"observed_at":"2026-05-17T04:41:31.696440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Omnigen2: Exploration to advanced multimodal generation","venue":null,"work_id":"5140f45c-4fbb-49cb-8f7b-bbd608ab3b74","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:1f26eec788cdc06c059c773d99a9092d182a2217c9df4e525875f7264844bf00","observation_id":"a8b621c8-1cfe-44c6-87c0-c7c0c8ad28b3","resolution":{"observed_at":"2026-05-17T04:41:31.701073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dreamomni: Unified image generation and editing","venue":null,"work_id":"7b058ea6-b8c3-4829-a240-8f9570a39841","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:ca3a57b1623120605c8c167bc2c7e675baf296e0468bb6633558ac5b2607d3e1","observation_id":"26c72cbf-1519-4239-97c1-154a6212a9f8","resolution":{"observed_at":"2026-05-17T04:41:31.669866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Teaching diffu- sion models to ground alpha matte.Transactions on Machine Learning Research","venue":null,"work_id":"79ab63b0-47d5-49a5-b60c-f19f0a5d093d","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:231f11cf324c3e2802fff5288614cdcbcaeeeaafb34a480a570582fb4980534d","observation_id":"22896c0a-5d13-497d-aaae-244a1269f3a7","resolution":{"observed_at":"2026-05-17T04:41:31.773374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Omnigen: Unified image generation","venue":null,"work_id":"5eb3c760-785b-4d12-a0cb-4d6cc0a5e6a5","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:a79d555e4d5679b0143d1f6a3aeb3dd2377ff1c078ffe64f7ed42b603bece9f7","observation_id":"caf737cc-5d9a-4f37-be0e-9c5635ec75db","resolution":{"observed_at":"2026-05-17T04:41:31.752769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep image matting","venue":null,"work_id":"7592db7f-ea9f-4259-8c15-f993b718eb13","year":2017},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:477c24eb371ac8268c3c9615790be99a7763c5099e8e3b30f949034224765e91","observation_id":"3ebba45d-2543-4d04-95b2-8f63ac6ceab6","resolution":{"observed_at":"2026-05-17T04:41:31.744798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Generative image layer decomposition with visual effects","venue":null,"work_id":"2370031c-17d9-4381-9834-cab663521fdb","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:cfc11431ff7f1630bbf6291edae7c8644750d682f93dfbca8a9e7f29e2ff6a80","observation_id":"6d1e9652-dd6c-4a0e-8e6e-daeff7248cbc","resolution":{"observed_at":"2026-05-17T04:41:31.755078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vitmatte: Boosting image matting with pretrained plain vision transformers","venue":null,"work_id":"a8c4916e-2b5c-462c-a9b5-3a533ecd8a8d","year":2023},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:5525d27ba0ee48f1d5ea55f2f55ea21cea142baae5fbe3e46bc211b228dee767","observation_id":"a5b1d9e1-c0cf-4f28-94b4-5499c1d77a2c","resolution":{"observed_at":"2026-05-17T04:41:31.724289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Matte anything: Interactive natural image matting with seg- ment anything models","venue":null,"work_id":"ea55524c-6c36-4849-8aeb-41bece9b5543","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:13cd02700d42d859e6c52c7430c587a8f1f0ea73e52ada0294e21abd2b5f35c3","observation_id":"e9d29d81-99a9-4435-ae09-f3c4e4904cfd","resolution":{"observed_at":"2026-05-17T04:41:31.742191Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mask guided matting via progressive refinement network","venue":null,"work_id":"ec129448-72a8-434b-b007-3b105c511f5f","year":2021},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:7d63a7a9705a7736e6bf2e9a3790b741ca0a4f3414d097cba405937dbdaf80b8","observation_id":"854d7313-1527-4fff-bee1-c570ceca2e5e","resolution":{"observed_at":"2026-05-17T04:41:31.739119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Transparent image layer diffusion using latent transparency","venue":null,"work_id":"ffaa56a8-bfe4-49a0-87b2-9691563c2789","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:b1cdbb31b4cf3f412005ce01de3f915a66483cb74e3ffa3f7a9fdff92783370e","observation_id":"0e3b579c-282d-4d2a-9666-f926ab00a44b","resolution":{"observed_at":"2026-05-17T04:41:31.732708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Objectclear: Complete object removal via object-effect attention","venue":null,"work_id":"f72b17a6-ddc0-463d-ab9b-4e6b3c6171f9","year":2025},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:7d8b70fc9d01a18cb817298721f75827b2c9f6d6e33fdd45d1c62166f9e1d190","observation_id":"8f1fe71b-a64e-497a-9e34-ba16be80b48c","resolution":{"observed_at":"2026-05-17T04:41:31.693499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"gray →white","venue":null,"work_id":"9ca84a79-8890-4eea-90d3-675644b874e1","year":2024},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:9a4047cd06899b53615970fd9c49288c871e05cb17053aa06530a1f99999fb81","observation_id":"39f8c0bf-80d1-4863-b205-692cc6aa41b1","resolution":{"observed_at":"2026-05-17T04:41:31.776660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"minimalist","venue":null,"work_id":"fe9de6d2-c57d-4957-b15b-4fab731b7831","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:3becc725a5312ee2716502d5c40f5263dee834486e9eb3dc2161eb102f5bda0e","observation_id":"ab623ec5-ee9f-44b4-b045-63e833a7ce69","resolution":{"observed_at":"2026-05-17T04:41:31.754473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"in a lab","venue":null,"work_id":"b49c41d9-57fc-4eb5-928b-1349a81a3549","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:50aa21404bbde3c256890f1e1c2e7e4d1c4c4168d0328f5183bb292b23e8be48","observation_id":"3d42afd4-f554-431c-b46a-6f30f566f44b","resolution":{"observed_at":"2026-05-17T04:41:31.761188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"black”, “purple","venue":null,"work_id":"290de6b3-7c7b-4c9f-9a4d-eccf8907a616","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:a56e0903a4803a0886d20ac65c77823b01bd24335257f8cd81b5115e087835ed","observation_id":"b761f2e7-bd25-49d5-9525-1e8ca2f1198b","resolution":{"observed_at":"2026-05-17T04:41:31.691224Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"ec2a4aa3-6194-412a-8ebe-e154f7784715","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:c930d892db8ad1519fd5aad9e86012092f4bc49803f524d97458a6b0018d81ae","observation_id":"07b9a70f-9cae-4e8b-9886-b4475428b734","resolution":{"observed_at":"2026-05-17T04:41:31.765556Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"8c2981e8-1d35-44c7-b99b-4ab3be0246de","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:a77dc1855a4900d900be8c74b337bd0bcdb637044843cfc76dec49abba901b5e","observation_id":"8e549d7f-ba74-4e44-b176-7e6b5c5d71bd","resolution":{"observed_at":"2026-05-17T04:41:31.708974Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"4 Compare the two generated images according to the following three aspects","venue":null,"work_id":"92d82c17-41e2-4327-b279-fed2ebebc58c","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:42783da9dad4dd90b21a83d481256e69cd10d843eeed3ee068bddc172444dcfc","observation_id":"f52a5720-01e3-49b1-a3b3-b872a0fe85bb","resolution":{"observed_at":"2026-05-17T04:41:31.701653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"better\"","venue":null,"work_id":"5c4f9324-0c00-4aca-8170-3192009fd286","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:293f806a3035e0815458bdd0adcd7fabf86fc8f0a18d48d9b252aa6d3c406343","observation_id":"4a291a40-bb26-4876-89fa-677ceccbee64","resolution":{"observed_at":"2026-05-17T04:41:31.706092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"better\"","venue":null,"work_id":"3b1c0bb0-eb97-426d-abf2-5c7f27f256e5","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:b81d8cc2be06876b959aca2fb54d7d5f4dc07fa55910bcfeb80b15d65d568d82","observation_id":"30198a25-9d33-40d7-a61e-43b3bce1c8e7","resolution":{"observed_at":"2026-05-17T04:41:31.715470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"031d5676-94d7-4ea7-8f70-5835a6cd13a6","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:19762a23c49cd6695112e0344769e94d39db6c5ff235bad9998e9ed83090ab65","observation_id":"3aedd204-6e68-4a53-9f45-a219709a9af4","resolution":{"observed_at":"2026-05-17T04:41:31.735769Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"5f981dc9-fa98-4059-b273-0a3cbb30d0d2","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:f8fc3d9c0a87f9e28ca85a0519e4b6461ba9dd08a95ad5929c673f44fcac558b","observation_id":"3b312f9d-2b2d-48a0-8e22-2937017d082e","resolution":{"observed_at":"2026-05-17T04:41:31.750324Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"a9db33f4-1bac-421c-9060-a444f59603b8","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:aa07014b1f70d0d587a6e8f9f83a1c3bfb61147f6da403b2c212462bd3adcf28","observation_id":"b9c16d5d-774c-446a-b955-4bab78a527ba","resolution":{"observed_at":"2026-05-17T04:41:31.718562Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Compare the two generated images according to the following three aspects","venue":null,"work_id":"b0d74bef-d563-4422-8205-6e2fe2e1dcb2","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:162269c8697003bfaa9b17111642603199a512648a9b942d41e9ddc3a50a3234","observation_id":"6a0a0db5-9aba-419f-924d-0afd53b1f174","resolution":{"observed_at":"2026-05-17T04:41:31.721077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"c8fc8da3-a2fd-448a-a0ea-9b181e37a871","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:d9158352d66eb70049b098b6c336574d8ea3ac6ceca7f8aec3fdfc30bc14e23c","observation_id":"6c7f1e65-4363-4aac-b11f-542b245188d0","resolution":{"observed_at":"2026-05-17T04:41:31.713353Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"6affbe94-5e67-4d07-87e1-b72398d10a06","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:44631fa5d73ca2934a71befbc50cba430c77999a4ae2bf304140c596cea8dd58","observation_id":"2aca6a5c-2050-4997-b5c3-9dec32a51edc","resolution":{"observed_at":"2026-05-17T04:41:31.721289Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"better\"","venue":null,"work_id":"fa899a92-d35c-4d70-9a1f-dba1936d7a68","year":null},"citing_paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-17T04:39:59.601872Z"},"links":{"citing_paper":"/paper/2511.20211"},"observation_digest":"sha256:d9dab1373bb0d4a73e09aae23609fe87658f44d522d284c4351d30d62d19a9ba","observation_id":"d47ccbdd-b8d1-4b0e-870c-1bbaa59c2811","resolution":{"observed_at":"2026-05-17T04:41:31.771650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2511.20211","last_updated":"2026-04-28T13:58:26Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T22:36:53.831174Z","submitted_at":"2025-11-25T11:34:51Z","title":"OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning"},"reference_resolution":{"displayed":64,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":2,"verified_fuzzy":55},"total_outbound_references":64},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 3 inbound Pith citation observations for arXiv:2511.20211."}