{"as_of":"2026-08-06T07:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:07b238866feae423dea4805035a75d699783d91d6275f3f3a7301f680c948350","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T03:50:47.434926Z","state":"measured"},{"denominator":24,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":24,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2602.06886/citation-record","integrity":"/paper/2602.06886/integrity","json":"/paper/2602.06886/citation-record.json","paper":"/paper/2602.06886"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2511.22699","last_updated":"2026-07-06T06:19:03Z","snapshot_observed_at":"2026-08-03T19:47:26.577384Z","submitted_at":"2025-11-27T18:52:07Z","title":"Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.22699","snapshot_observed_at":"2026-08-03T03:50:45.140207Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.140207Z"},"links":{"cited_paper":"/paper/2511.22699","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:88eac16d0a35a38db0c9f042d3bddb1f6c74c06e1c358d3f88f79b254b9a1ff3","observation_id":"61207d22-6a08-47c7-beb3-4a670fc9c49a","resolution":{"observed_at":"2026-08-03T03:50:45.140207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.00426","last_updated":"2023-12-29T16:42:08Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-30T16:18:00Z","title":"PixArt-$\\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.00426","snapshot_observed_at":"2026-08-03T03:50:45.241076Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.241076Z"},"links":{"cited_paper":"/paper/2310.00426","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:402335adf26b212657bd0e071720ce36d14c958be3852ed0094f42041b552333","observation_id":"4af4b611-6ce8-4d49-a031-481ed163eca4","resolution":{"observed_at":"2026-08-03T03:50:45.241076Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09568","last_updated":"2025-05-14T17:11:07Z","snapshot_observed_at":"2026-07-06T21:23:57.084147Z","submitted_at":"2025-05-14T17:11:07Z","title":"BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09568","snapshot_observed_at":"2026-08-03T03:50:45.324738Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.324738Z"},"links":{"cited_paper":"/paper/2505.09568","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:e4a72d42969ace3e6f9fad61d5fc80027081b9f4d8823d5ac0a9c63a2521c4fc","observation_id":"c465b187-478f-4047-b6f4-665b93268e0e","resolution":{"observed_at":"2026-08-03T03:50:45.324738Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.12598","last_updated":"2022-07-26T01:42:07Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-07-26T01:42:07Z","title":"Classifier-Free Diffusion Guidance","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.12598","snapshot_observed_at":"2026-08-03T03:50:45.406955Z","title":"Ho and T","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.406955Z"},"links":{"cited_paper":"/paper/2207.12598","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:a1bb0cd0a674a4b10c623aef580c79a6499b3fc0d1020bec858f8f8f02828641","observation_id":"b30d7a25-386e-4117-8c44-0142af571fe1","resolution":{"observed_at":"2026-08-03T03:50:45.406955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T03:50:47.209248Z","title":"These Prompt Reinjection settings are chosen based on the best-performing combinations identified in our ablation stud- ies","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:47.209248Z"},"links":{"citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:87adfd517374b0626f392dce1391eaa267eaae6974cfaabe06d179b06b0b25c3","observation_id":"ef49485a-c6c6-4505-9ee1-985504817105","resolution":{"observed_at":"2026-08-03T03:50:47.209248Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03048","last_updated":"2025-05-01T09:40:21Z","snapshot_observed_at":"2026-08-02T13:01:06.918463Z","submitted_at":"2024-01-05T19:55:15Z","title":"Latte: Latent Diffusion Transformer for Video Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03048","snapshot_observed_at":"2026-08-03T03:50:45.759009Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.759009Z"},"links":{"cited_paper":"/paper/2401.03048","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:cda50f921214e68c05b82e7a9249c3358761708da24ea6dc5106b4470373f8f7","observation_id":"85d1aed7-3d63-4c12-ab53-ed1e5f83d174","resolution":{"observed_at":"2026-08-03T03:50:45.759009Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.10741","last_updated":"2022-03-08T18:18:49Z","snapshot_observed_at":"2026-08-02T18:14:47.498475Z","submitted_at":"2021-12-20T18:42:55Z","title":"GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.10741","snapshot_observed_at":"2026-08-03T03:50:45.861332Z","title":"Nichol, P","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.861332Z"},"links":{"cited_paper":"/paper/2112.10741","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:621b4718d8e5b6ae82ec6a20ebae03064cc7e7823486fa8949751734de8888f4","observation_id":"07672c85-0219-44fc-a3f9-7d0b30e5acda","resolution":{"observed_at":"2026-08-03T03:50:45.861332Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.01952","last_updated":"2023-07-04T23:04:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-04T23:04:57Z","title":"SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.01952","snapshot_observed_at":"2026-08-03T03:50:45.972063Z","title":"Podell, Z","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.972063Z"},"links":{"cited_paper":"/paper/2307.01952","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:da51f51f18d6033af9568ecc312b14a6db87566f674a3b7763602527948f41fb","observation_id":"87f96f3d-37df-4345-9ae2-056844db962b","resolution":{"observed_at":"2026-08-03T03:50:45.972063Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-07-06T10:01:50.133383Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-03T03:50:46.127262Z","title":null,"venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:46.127262Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:99ece2f48aaa7d9b22935033593be45c1b9f244bba5a4e00dae888dc5177a00e","observation_id":"c6b843f2-2a15-4dfd-8971-32b736baa733","resolution":{"observed_at":"2026-08-03T03:50:46.127262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.20314","last_updated":"2025-04-19T02:22:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-26T08:25:43Z","title":"Wan: Open and Advanced Large-Scale Video Generative Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.20314","snapshot_observed_at":"2026-08-03T03:50:46.244612Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:46.244612Z"},"links":{"cited_paper":"/paper/2503.20314","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:ab178ac95a215af586b9a164ac07cc99da5917f8da567a5495f9827062ffde7c","observation_id":"0e0ecd26-3c0f-475a-bb09-b07fa5eecaf3","resolution":{"observed_at":"2026-08-03T03:50:46.244612Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.16153","last_updated":"2025-03-20T13:55:12Z","snapshot_observed_at":"2026-08-01T22:02:42.705807Z","submitted_at":"2025-03-20T13:55:12Z","title":"FreeFlux: Understanding and Exploiting Layer-Specific Roles in RoPE-Based MMDiT for Versatile Image Editing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.16153","snapshot_observed_at":"2026-08-03T03:50:46.360371Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:46.360371Z"},"links":{"cited_paper":"/paper/2503.16153","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:1a68cfc934daa43eeb0329b24b2647678e87257344ee747f33a10953f01933aa","observation_id":"cd2da8e1-e90b-4b6f-840d-04681d943322","resolution":{"observed_at":"2026-08-03T03:50:46.360371Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.02324","last_updated":"2025-08-04T11:49:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-04T11:49:20Z","title":"Qwen-Image Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.02324","snapshot_observed_at":"2026-08-03T03:50:46.437884Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:46.437884Z"},"links":{"cited_paper":"/paper/2508.02324","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:3576832c954e4d6e403dfb713e91479e7e28e65f7242a3e8da77d41c17e0ee86","observation_id":"802d2e37-b182-422b-9536-7d3ddfce2ecc","resolution":{"observed_at":"2026-08-03T03:50:46.437884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.09341","last_updated":"2023-09-25T08:19:23Z","snapshot_observed_at":"2026-07-06T15:43:07.989730Z","submitted_at":"2023-06-15T17:59:31Z","title":"Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.09341","snapshot_observed_at":"2026-08-03T03:50:46.551257Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:46.551257Z"},"links":{"cited_paper":"/paper/2306.09341","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:7e46762191602a4734b1dd26cddce239b693a19440b012819ea4095bea7123b5","observation_id":"2267f655-40b9-413e-ba18-ddf0684089e0","resolution":{"observed_at":"2026-08-03T03:50:46.551257Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10629","last_updated":"2024-10-20T14:35:31Z","snapshot_observed_at":"2026-07-06T19:33:08.264958Z","submitted_at":"2024-10-14T15:36:42Z","title":"SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.10629","snapshot_observed_at":"2026-08-03T03:50:46.708056Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:46.708056Z"},"links":{"cited_paper":"/paper/2410.10629","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:363a6dc723fd21847c1a14fd3ab98162f5ad6007708bf6b7e3ae4f001af2bbe5","observation_id":"e7cd895d-04b1-4852-872d-2dfdbcc19770","resolution":{"observed_at":"2026-08-03T03:50:46.708056Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.09987","last_updated":"2025-08-13T17:59:28Z","snapshot_observed_at":"2026-08-06T06:04:10.094208Z","submitted_at":"2025-08-13T17:59:28Z","title":"Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.09987","snapshot_observed_at":"2026-08-03T03:50:46.874348Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:46.874348Z"},"links":{"cited_paper":"/paper/2508.09987","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:f9382d1f204a57822aa06e4ceccec1509aadaf6c634d28cd602c846cb93ee8d7","observation_id":"4b0d842f-3bb5-43bd-b628-7734f017fe59","resolution":{"observed_at":"2026-08-03T03:50:46.874348Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.09305","last_updated":"2024-03-05T01:10:18Z","snapshot_observed_at":"2026-08-03T18:21:25.175322Z","submitted_at":"2023-06-15T17:38:48Z","title":"Fast Training of Diffusion Models with Masked Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.09305","snapshot_observed_at":"2026-08-03T03:50:47.050868Z","title":"Zheng, W","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:47.050868Z"},"links":{"cited_paper":"/paper/2306.09305","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:1be34c4ebad5d91562ed94660413aef908bd91d56769f3598ef14ef6abc7b1e4","observation_id":"44f08017-9a0e-4aa1-964f-852df110be70","resolution":{"observed_at":"2026-08-03T03:50:47.050868Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T03:50:47.319081Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:47.319081Z"},"links":{"citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:caabd0e17fc752b4a9f172cf4378706554f62605a09691e449226e8098a0d383","observation_id":"a137796f-de77-420b-af96-6cc3b956bcf9","resolution":{"observed_at":"2026-08-03T03:50:47.319081Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T03:50:47.434926Z","title":"Unlike our training-free Prompt Reinjec- tion, TACA requires LoRA fine-tuning of the model","venue":null,"work_id":null,"year":1950},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:47.434926Z"},"links":{"citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:b5b63dd5ebb644b537b5c15db8bd2eeb2bb27499ad000b896133b49dd71ca46b","observation_id":"4e2bc90d-6625-489e-9e76-e6b09a446371","resolution":{"observed_at":"2026-08-03T03:50:47.434926Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T03:50:47.131010Z","title":"We fix lori=1, Ltgt={l|l > lori}, and w=0.025, and vary the prompt set used to collect text-token pairs for computing the orthogonal mapping","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":1024,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:47.131010Z"},"links":{"citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:085fcd127faf216bd25c64e37b7a97e0ebb3f81fcd1efa7558f96ba71c3fd2bc","observation_id":"f7ca069d-3743-4e45-a8e3-3a0f96c54a5b","resolution":{"observed_at":"2026-08-03T03:50:47.131010Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07986","last_updated":"2025-07-23T03:45:11Z","snapshot_observed_at":"2026-07-06T21:39:13.304260Z","submitted_at":"2025-06-09T17:54:04Z","title":"Rethinking Cross-Modal Interaction in Multimodal Diffusion Transformers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.07986","snapshot_observed_at":"2026-08-03T03:50:45.713158Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.713158Z"},"links":{"cited_paper":"/paper/2506.07986","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:2640955e9e0f252c3c583848a4fc393219497d4bcd6a6e79b1434cbb41998c9d","observation_id":"b45ccc8f-b5a9-4358-8d0b-8fe2a88c3205","resolution":{"observed_at":"2026-08-03T03:50:45.713158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.05135","last_updated":"2024-03-08T08:08:10Z","snapshot_observed_at":"2026-08-04T23:51:18.339338Z","submitted_at":"2024-03-08T08:08:10Z","title":"ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.05135","snapshot_observed_at":"2026-08-03T03:50:45.491098Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.491098Z"},"links":{"cited_paper":"/paper/2403.05135","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:8faf5d1a3dd761b6dcaecfeb94de823273710d4d65884e96f5881764a249103f","observation_id":"a793ebab-2c41-46d2-a3d3-1fa2b9f2d3b9","resolution":{"observed_at":"2026-08-03T03:50:45.491098Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13301","last_updated":"2024-01-04T19:11:25Z","snapshot_observed_at":"2026-08-01T15:43:51.739518Z","submitted_at":"2023-05-22T17:57:41Z","title":"Training Diffusion Models with Reinforcement Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13301","snapshot_observed_at":"2026-08-03T03:50:45.046193Z","title":"Black, M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.046193Z"},"links":{"cited_paper":"/paper/2305.13301","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:89d9aa3b7af74acb479859b9023f297c80fdf16bf5f0267482cdf00f520944cf","observation_id":"a82a82ae-cb7e-4cba-a558-1ec636851bbb","resolution":{"observed_at":"2026-08-03T03:50:45.046193Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.02211","last_updated":"2026-07-06T03:26:05Z","snapshot_observed_at":"2026-08-04T22:25:47.271922Z","submitted_at":"2026-01-05T15:32:53Z","title":"TexTailor: Inference-Time Textual Guidance Tailoring for Multimodal Diffusion Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.02211","snapshot_observed_at":"2026-08-03T03:50:45.652959Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.652959Z"},"links":{"cited_paper":"/paper/2601.02211","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:646cd7b3ebf9d68ec173bef868467e68de8722dc76ed94a10725ea6c9cc34d90","observation_id":"cb1ba7c0-5ec4-4cdc-8fbc-057a32fd6f27","resolution":{"observed_at":"2026-08-03T03:50:45.652959Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07987","last_updated":"2024-07-25T09:33:50Z","snapshot_observed_at":"2026-08-01T15:05:23.324854Z","submitted_at":"2024-05-13T17:58:30Z","title":"The Platonic Representation Hypothesis","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.07987","snapshot_observed_at":"2026-08-03T03:50:45.572290Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation","version":5},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-03T03:50:45.572290Z"},"links":{"cited_paper":"/paper/2405.07987","citing_paper":"/paper/2602.06886"},"observation_digest":"sha256:d9238576e215dde985115e6752cdf1fa9736473a71fc641f1974544211318d72","observation_id":"b3615aaa-0fa3-47d1-9cf3-e65fd594d11c","resolution":{"observed_at":"2026-08-03T03:50:45.572290Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2602.06886","last_updated":"2026-07-31T08:35:56Z","latest_version":5,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T23:10:18.924353Z","submitted_at":"2026-02-06T17:19:53Z","title":"Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":22,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":24},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2602.06886."}