{"as_of":"2026-08-13T23:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a2e486ea36a187e12cad6f018e575f6015dc5c1eae034492a98457a85931c91c","coverage":[{"denominator":58,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":58,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T04:38:02.315863Z","state":"measured"},{"denominator":58,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":58,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.01223/citation-record","integrity":"/paper/2412.01223/integrity","json":"/paper/2412.01223/citation-record.json","paper":"/paper/2412.01223"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:03.201861Z","title":"Blended diffusion for text-driven editing of natural images","venue":null,"work_id":"7180be61-0e67-43d0-8e53-790493548d94","year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.012781Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:c63f3a1fc97204cb89093cc0718393efc50138f8bd94227941f110db2e95d139","observation_id":"5f05aef1-a993-4694-9018-ccfb5477c9db","resolution":{"observed_at":"2026-08-12T04:38:03.207516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:03.180857Z","title":"Blended latent diffusion","venue":null,"work_id":"5c30077b-395d-4edd-a8e7-8d9fee670d3d","year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.018143Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:c591a15822322fe76cc9ba19d9b09f607333e934bc921f6f87f7931d0f8cd027","observation_id":"4624540a-00a8-45ed-8fbe-3ff6ee0f3808","resolution":{"observed_at":"2026-08-12T04:38:03.189654Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.022984Z","title":"In- structpix2pix: Learning to follow image editing instructions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.022984Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:b8fe4175c307d487e7a9d7bccc44e716c00c44256264a8a65156faa3d78e90e4","observation_id":"4848f318-6f1b-4f8b-b1c4-30890d19eb30","resolution":{"observed_at":"2026-08-12T04:38:02.022984Z","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":"2026-08-12T04:38:02.028337Z","title":"Pixart- α: Fast training of diffusion transformer for photorealistic text-to-image synthesis","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.028337Z"},"links":{"cited_paper":"/paper/2310.00426","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:a0beabeb6070cbcc6d217cca4acb1b4e389ab6615d86988d311a8cf3193351d4","observation_id":"ddc2e7d1-d955-410d-b73e-fa640e208613","resolution":{"observed_at":"2026-08-12T04:38:02.028337Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12793","last_updated":"2023-11-28T08:52:50Z","snapshot_observed_at":"2026-08-04T08:17:54.774738Z","submitted_at":"2023-11-21T18:58:11Z","title":"ShareGPT4V: Improving Large Multi-Modal Models with Better Captions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12793","snapshot_observed_at":"2026-08-12T04:38:02.033710Z","title":"Sharegpt4v: Improving large multi-modal models with better captions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.033710Z"},"links":{"cited_paper":"/paper/2311.12793","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:3ac000b256679d213583743e9ebfad5692110bd2b4a831d3d5fdcb5e73d3309b","observation_id":"220b7bba-95cc-4f0f-bc84-1baf7a9da7c4","resolution":{"observed_at":"2026-08-12T04:38:02.033710Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:03.151520Z","title":"Latentpaint: Image inpainting in latent space with diffusion models","venue":null,"work_id":"c7cbc250-480b-4d3a-9bbf-1c759e5bfe21","year":2024},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.038909Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:ccb96721332be08af3eead222d7525f4ec9b2e4e45c0c547e116fd5336c27bb4","observation_id":"7dafb205-ca3a-427b-b1b9-958d3d1704f4","resolution":{"observed_at":"2026-08-12T04:38:03.156947Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:03.135813Z","title":"Van Gogh Diffusion Model","venue":null,"work_id":"745e5e21-7e0f-4f4f-831a-0049a3776791","year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.055965Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:5a740214cecba309e4c82e156497b15be3329a4dc4df836243ed5906c13d8e18","observation_id":"1bd21f8c-a976-49f2-a8a7-8e590d5a12c2","resolution":{"observed_at":"2026-08-12T04:38:03.140971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.061632Z","title":"Imagenet: A large-scale hierarchical image database","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.061632Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:b53ec8e69bcb6a183380b2d266c3e0154a0b4c1c7dadb9cebf80bdddd1a81da0","observation_id":"0e9df746-6387-4d09-95f0-2a3e80315212","resolution":{"observed_at":"2026-08-12T04:38:02.061632Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.01618","last_updated":"2022-08-02T17:50:36Z","snapshot_observed_at":"2026-08-02T23:40:32.342515Z","submitted_at":"2022-08-02T17:50:36Z","title":"An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.01618","snapshot_observed_at":"2026-08-12T04:38:02.066901Z","title":"An image is worth one word: Personalizing text-to- image generation using textual inversion","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.066901Z"},"links":{"cited_paper":"/paper/2208.01618","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:58474b1947a04c3d5d7938d4aec60d6ad2f8e5293061f7e09faa18dcb6525f4b","observation_id":"d6decae3-c276-41c9-9de7-98e690c09beb","resolution":{"observed_at":"2026-08-12T04:38:02.066901Z","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":"2026-08-12T04:38:02.072185Z","title":"Generative adversarial networks","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.072185Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:97c13f18ff9aa8f9c6f36f2cdfe99cab71fad729f0cd5d0a6919c470530c1019","observation_id":"4bf3130a-526f-4993-8061-7b28d77d2e6c","resolution":{"observed_at":"2026-08-12T04:38:02.072185Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:03.097931Z","title":"Counterfeit-v3.0","venue":null,"work_id":"d0e2e194-9178-44e2-b05b-511672f9fe2a","year":2024},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.077092Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:230b37f5ddc9eeb63737b732608352c84f0a546408469311b32fa58c2f995386","observation_id":"338d881f-cbbc-4c78-99e1-2dbd3aa682b3","resolution":{"observed_at":"2026-08-12T04:38:03.104038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.01626","last_updated":"2022-08-02T17:55:41Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-08-02T17:55:41Z","title":"Prompt-to-Prompt Image Editing with Cross Attention Control","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.01626","snapshot_observed_at":"2026-08-12T04:38:02.082036Z","title":"Prompt-to-prompt image editing with cross attention control.(2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.082036Z"},"links":{"cited_paper":"/paper/2208.01626","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:d9e8fd187f5e6e5633d1cb941fb18495f28022454ca4a6b1ea206b42a2c08cc2","observation_id":"67d376c2-9bcd-4f28-92ab-c97b5208e1c6","resolution":{"observed_at":"2026-08-12T04:38:02.082036Z","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":"2026-08-12T19:28:23.372660Z","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":"2026-08-12T04:38:02.087533Z","title":"Classifier-free diffusion guidance","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.087533Z"},"links":{"cited_paper":"/paper/2207.12598","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:e0761f71815282b1687bb4da7fe1ada6e1722c83e462f1657f5a62b4f7da6d25","observation_id":"5080f77e-1a6b-4a62-bbbf-ab7c61740938","resolution":{"observed_at":"2026-08-12T04:38:02.087533Z","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":"2026-08-12T04:38:02.093046Z","title":"Denoising dif- fusion probabilistic models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.093046Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:5250de499fa2c89145f9d5fb656b885fa77a7644d6d53658dc366242b4a3f407","observation_id":"ae7d3960-88d6-4f14-bb8f-6b9ea9e79a88","resolution":{"observed_at":"2026-08-12T04:38:02.093046Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:03.070604Z","title":"Introvae: Introspective variational autoencoders for photo- graphic image synthesis","venue":null,"work_id":"755c77f2-f3c2-4b5a-92c9-a66020015606","year":2018},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.098137Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:6d105d3f094328ddfd107a9934d85de27c4ae8acd10e9373a79a176b5fb25eb5","observation_id":"bb06ac7a-6134-48c0-b923-b1699421b51d","resolution":{"observed_at":"2026-08-12T04:38:03.075736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.06976","last_updated":"2024-03-11T17:59:31Z","snapshot_observed_at":"2026-08-13T00:57:21.525577Z","submitted_at":"2024-03-11T17:59:31Z","title":"BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.06976","snapshot_observed_at":"2026-08-12T04:38:02.102930Z","title":"Brushnet: A plug-and-play image inpaint- ing model with decomposed dual-branch diffusion","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.102930Z"},"links":{"cited_paper":"/paper/2403.06976","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:ede0a9bb52354d4a3d3016417e97239d190f23ea35376af2a3e9582d83acc30e","observation_id":"f027f0f6-bdc2-4ce6-a208-668ee89b2f1a","resolution":{"observed_at":"2026-08-12T04:38:02.102930Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10196","last_updated":"2018-02-26T15:33:34Z","snapshot_observed_at":"2026-07-06T06:06:26.276752Z","submitted_at":"2017-10-27T15:28:35Z","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10196","snapshot_observed_at":"2026-08-12T04:38:02.108722Z","title":"Progressive growing of gans for improved qual- ity, stability, and variation.arXiv preprint arXiv:1710.10196,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.108722Z"},"links":{"cited_paper":"/paper/1710.10196","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:bbfb3423387b2d8c804af19706a328840fd8443e282a6ee431cf3996bd60dddd","observation_id":"44e79534-fc81-412a-8287-1eed21168981","resolution":{"observed_at":"2026-08-12T04:38:02.108722Z","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":"2026-08-12T04:38:02.113825Z","title":"A style-based generator architecture for generative adversarial networks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.113825Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:3ccb517fd32b0a5d40fb946981be90ecf661c3b1d7c67d67aa451bf3be8ee815","observation_id":"c3e37608-c1f3-495f-96be-d6b939c770da","resolution":{"observed_at":"2026-08-12T04:38:02.113825Z","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":"2026-08-12T04:38:02.118488Z","title":"The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale","venue":null,"work_id":null,"year":1956},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.118488Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:11acea2fa5f2bfacd3b7464b95e9abd068363d9b8ab6367e48f798a472b3208b","observation_id":"1831a27f-70d6-4059-a430-0e3ffae1f274","resolution":{"observed_at":"2026-08-12T04:38:02.118488Z","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":"2026-08-12T04:38:02.123137Z","title":"Blip-diffusion: Pre- trained subject representation for controllable text-to-image generation and editing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.123137Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:337b5eaa1cdf916f6de0b6ab1b40eab333b8bb493f4448226dd5b604b3aee51d","observation_id":"e46eaf5e-9563-408a-ae6e-3dd2ad176540","resolution":{"observed_at":"2026-08-12T04:38:02.123137Z","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":"2026-08-12T04:38:02.127606Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.127606Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:db4797b86c203ceff2f381a39cd4f0a127cc8ca9524a78af5bc71009c81c1783","observation_id":"5e2d2eb4-83c3-4b47-a261-3993e2615695","resolution":{"observed_at":"2026-08-12T04:38:02.127606Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.05499","last_updated":"2024-07-19T06:00:41Z","snapshot_observed_at":"2026-07-06T15:00:58.804337Z","submitted_at":"2023-03-09T18:52:16Z","title":"Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.05499","snapshot_observed_at":"2026-08-12T04:38:02.132017Z","title":"Grounding dino: Marrying dino with grounded pre-training for open-set object detection","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.132017Z"},"links":{"cited_paper":"/paper/2303.05499","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:9345d4879d163a427f8867ca463a1e2a9da6163543c59ba3c1576237aa3da9dc","observation_id":"9608787f-f3d9-4a1c-9d13-185746bf4711","resolution":{"observed_at":"2026-08-12T04:38:02.132017Z","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":"2026-08-12T04:38:02.136569Z","title":"Deep learning face attributes in the wild","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.136569Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:1ae73ca16d966bd4154bc2db0b681fe407b9de7c93f70b54c508cd4e246d8a50","observation_id":"5bd25526-f49a-49fe-b264-cd3d4ec2f417","resolution":{"observed_at":"2026-08-12T04:38:02.136569Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:03.001846Z","title":"Spe- cialist diffusion: Plug-and-play sample-efficient fine-tuning of text-to-image diffusion models to learn any unseen style","venue":null,"work_id":"1167bd4d-a71c-43e1-a137-6cc4ef0ef5fe","year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.140877Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:332006a453d786ec2a26dd6c343b615cb8a16bd27eb15c92dd120076549267cb","observation_id":"29f94f3d-5545-42c8-9bbb-ee9d3ce5e4f7","resolution":{"observed_at":"2026-08-12T04:38:03.007198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.145307Z","title":"Repaint: Inpainting using denoising diffusion probabilistic models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.145307Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:ff56802644fcff0810ee33cc41acbb36e15946f2c7f486bc1bfbf814179c33a5","observation_id":"91ee503a-dfaa-477d-b9a5-3bb69e6b13d7","resolution":{"observed_at":"2026-08-12T04:38:02.145307Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14091","last_updated":"2024-03-18T16:48:13Z","snapshot_observed_at":"2026-08-13T04:55:54.883202Z","submitted_at":"2023-12-21T18:09:30Z","title":"HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.14091","snapshot_observed_at":"2026-08-12T04:38:02.150262Z","title":"Hd-painter: high-resolution and prompt-faithful text-guided image inpainting with diffusion models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.150262Z"},"links":{"cited_paper":"/paper/2312.14091","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:aca2ca93d2359b5e3d39fd39392f207a6e603151c280c21c6bf77996e78ec2d8","observation_id":"195eab47-b378-4ac6-848a-9e2c120db411","resolution":{"observed_at":"2026-08-12T04:38:02.150262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.973608Z","title":"9 On distillation of guided diffusion models","venue":null,"work_id":"150da876-3a8d-43c1-92c8-0008eae36bd2","year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.154949Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:5047feea43678ef4901b92fca3c913a95f2814586db7780439f870443969b8d4","observation_id":"97b9a741-4258-4870-b88d-e994c42db0bd","resolution":{"observed_at":"2026-08-12T04:38:02.978959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.160072Z","title":"T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.160072Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:affbc847578b065cd57ce7c07f1e1eabdece1d62055634406e9f10618fece9ba","observation_id":"b9c9adfa-c601-4064-80ed-dd51ccc4ae86","resolution":{"observed_at":"2026-08-12T04:38:02.160072Z","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":"2026-08-12T04:38:02.164824Z","title":"Gen- erating diverse structure for image inpainting with hierar- chical vq-vae","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.164824Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:237a9d1c1f07b87c2dd5ace30680fb5b5a9198bb91c890c9f8b4673116237b51","observation_id":"664f6b88-6f46-4cbb-8559-79c2c381d4ed","resolution":{"observed_at":"2026-08-12T04:38:02.164824Z","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":"2026-08-12T04:38:02.169245Z","title":"Sdxl: Improving latent diffusion mod- els for high-resolution image synthesis","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.169245Z"},"links":{"cited_paper":"/paper/2307.01952","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:a0ea98849636bc1b847259d6ae3670b075906dab156c7b8cce776738c21001ec","observation_id":"605f0573-b13f-4314-86e8-0700cfa1ab60","resolution":{"observed_at":"2026-08-12T04:38:02.169245Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.936663Z","title":"Deep learning-based image and video inpainting: A survey","venue":null,"work_id":"5cd234e2-e453-4736-9073-20ce110cddef","year":2024},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.173902Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:292b16c62a025860afdd3969d3fb824a4a7c4f8589cdc132c98d1eaa1c71c256","observation_id":"65cebef8-8b80-4b15-a427-d292352aa56a","resolution":{"observed_at":"2026-08-12T04:38:02.941700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.919853Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":"9ea7bf42-c163-474b-bc21-968da1fdb27d","year":2021},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.178465Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:f39066a3eb8e070c9049a82f9c66f12cdf441dccd4ae11109aaf062a5d6c37d9","observation_id":"0fbdadc0-c71d-46ae-8f08-62e8530bf03a","resolution":{"observed_at":"2026-08-12T04:38:02.925373Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.183352Z","title":"Exploring the limits of transfer learning with a unified text-to-text transformer","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.183352Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:29525eb4ccb94e252e399602beefe794b20375be1b6975cb64f8ff3c007c959f","observation_id":"162ebc24-fa95-44f9-b5aa-0dd63af9adf6","resolution":{"observed_at":"2026-08-12T04:38:02.183352Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.06125","last_updated":"2022-04-13T01:10:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-13T01:10:33Z","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.06125","snapshot_observed_at":"2026-08-12T04:38:02.188077Z","title":"Hierarchical text-conditional image gener- ation with clip latents","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.188077Z"},"links":{"cited_paper":"/paper/2204.06125","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:ff48d8efbe78355442dddd32461096b5cad31a47f47e2dbf418a78397e010ffb","observation_id":"e00b82db-9c9a-48d9-adc5-f207385ae29b","resolution":{"observed_at":"2026-08-12T04:38:02.188077Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.891675Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"3f06ac5b-22a6-490c-8bd8-d741c315b2d5","year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.193159Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:d7542feb2330237393673be4d869d550dcd88bab018a8e86f963104bb480802d","observation_id":"6f1b02ec-ae0e-4c18-9de6-08e24b74d8af","resolution":{"observed_at":"2026-08-12T04:38:02.896933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.198113Z","title":"Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.198113Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:fb02e06167a7d422bcd236c5ec0ce70accbea14f0012b6c62d5984c9c8514feb","observation_id":"4add31f2-50d3-4509-978e-597eade4be58","resolution":{"observed_at":"2026-08-12T04:38:02.198113Z","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":"2026-08-12T04:38:02.202734Z","title":"Photorealistic text-to-image diffusion models with deep language understanding","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.202734Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:493c9077dfc7ce45c1bf3914b7d84178f67d8efd8637a1fefbceb47164c8451e","observation_id":"274dec7e-a332-46d5-8412-9c2f05e14da6","resolution":{"observed_at":"2026-08-12T04:38:02.202734Z","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":"2026-08-12T04:38:02.207225Z","title":"Mi-gan: A simple baseline for image in- painting on mobile devices","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.207225Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:d8325eae5cd162c5cc6a469f2204594c92fe7d69595e9f47407adddf6d08c5f6","observation_id":"90ef4f30-8f25-4d56-b0c1-44894d9b6e82","resolution":{"observed_at":"2026-08-12T04:38:02.207225Z","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":"2026-08-12T04:38:02.211782Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.211782Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:e8ba37991291a9c174459ead99b73c471a408bb1238678996f2f1ebc02f74ce1","observation_id":"75fe57bf-3dc4-49e6-bdad-bf701a884e6b","resolution":{"observed_at":"2026-08-12T04:38:02.211782Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.828717Z","title":null,"venue":null,"work_id":"ecd421ab-a4f6-4491-a972-5777ac068fb5","year":2024},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.216278Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:04e83bf0b1863c30b314725c346802e70f979ca4555b6ee18543a57f60c19151","observation_id":"942a54fd-e32d-4207-8c33-0ed2a5339c26","resolution":{"observed_at":"2026-08-12T04:38:02.833858Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.812756Z","title":"Chatglm: A family of large language mod- els from glm-130b to glm-4 all tools","venue":null,"work_id":"acfb9fb9-477a-4f53-878c-e6d3caec5491","year":2024},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.220822Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:75e48e6deac2d788de8be73e6bd658e8c3a59b164d3dd7e2246fefece984a9a0","observation_id":"106bb60e-25f4-4047-b4c5-5cffb3f71b11","resolution":{"observed_at":"2026-08-12T04:38:02.817770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.796252Z","title":"High-fidelity pluralistic image completion with transform- ers","venue":null,"work_id":"4509ee9a-bd51-4af1-8832-955f404a874c","year":2021},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.225115Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:9e2b5609d6870092bae23aff23ced66dc246c277877caceea2f21382862b4319","observation_id":"08a11d1c-1ca7-4d59-96fc-fddcc29df6e9","resolution":{"observed_at":"2026-08-12T04:38:02.801600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.780658Z","title":"Imagen editor and editbench: Advancing and evaluating text-guided im- age inpainting","venue":null,"work_id":"6c1b61af-f836-4303-94bf-b9dd2e21684d","year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.229528Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:8630c69f54173d9d8d68d3ca139ded676be51993a154c1d6a32a3c1ce7b52a1f","observation_id":"0d9b42e2-439e-47b0-8527-fd429371549c","resolution":{"observed_at":"2026-08-12T04:38:02.785516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14806","last_updated":"2021-04-30T07:40:35Z","snapshot_observed_at":"2026-08-12T04:22:15.303374Z","submitted_at":"2021-04-30T07:40:35Z","title":"GODIVA: Generating Open-DomaIn Videos from nAtural Descriptions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.14806","snapshot_observed_at":"2026-08-12T04:38:02.234358Z","title":"Godiva: Gen- erating open-domain videos from natural descriptions","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.234358Z"},"links":{"cited_paper":"/paper/2104.14806","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:aa8feb2876153c7abf2621e75e866ccaf5baae5192fb85df01fbacc98461136a","observation_id":"a945daad-0538-4d4f-89f3-35acf74e3936","resolution":{"observed_at":"2026-08-12T04:38:02.234358Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.764573Z","title":"Smartbrush: Text and shape guided object inpainting with diffusion model","venue":null,"work_id":"2321031a-5f66-4297-99f0-5ccf3852f8e0","year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.239204Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:f4c5873428f3d26b8a16d9d1a4c339acb6000188c1a8fad67888d3c31b165db5","observation_id":"b1513de4-90e6-48d0-8cc0-2e187417b97e","resolution":{"observed_at":"2026-08-12T04:38:02.769958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.03771","last_updated":"2023-12-05T22:23:19Z","snapshot_observed_at":"2026-08-13T05:09:09.098874Z","submitted_at":"2023-12-05T22:23:19Z","title":"DreamInpainter: Text-Guided Subject-Driven Image Inpainting with Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.03771","snapshot_observed_at":"2026-08-12T04:38:02.244064Z","title":"Dreaminpainter: Text-guided subject-driven image inpaint- ing with diffusion models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.244064Z"},"links":{"cited_paper":"/paper/2312.03771","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:19ab4de029a184461993669e2c1804382b16939d0fc2f7aef262f975e70fa7b1","observation_id":"dc88320c-9062-4835-8f85-6a69ec9fe707","resolution":{"observed_at":"2026-08-12T04:38:02.244064Z","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":"2026-08-12T04:38:02.250520Z","title":"Imagere- ward: Learning and evaluating human preferences for text- to-image generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.250520Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:266945d7ab4e8edc8cb2d683b4b1dd171bd6b0746c228bf012abfb0458f13eaa","observation_id":"bc4e570b-5e0f-43c9-940e-7f3bb4c799c6","resolution":{"observed_at":"2026-08-12T04:38:02.250520Z","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":"2026-08-12T04:38:02.256127Z","title":"Image completion with heterogeneously filtered spectral hints","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.256127Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:2c6b1b289a3f534ef43e6f9ff8d1f02a6100d3067a8843bb7041344d2cc55aee","observation_id":"bcc258ab-3954-489f-9f6b-c1382ee0a8fc","resolution":{"observed_at":"2026-08-12T04:38:02.256127Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.728526Z","title":"A review of image in- painting methods based on deep learning","venue":null,"work_id":"c8c40610-c689-45e7-b294-ec96f29b8320","year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.261871Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:1bb947f4b22aa161c58cb0bea447338ab6601ce89f9167e38c651e3370e9055a","observation_id":"e8f6f98b-7ed0-405d-8377-17033d58ad34","resolution":{"observed_at":"2026-08-12T04:38:02.733696Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.712573Z","title":"Uni-paint: A unified framework for multimodal image inpainting with pretrained diffusion model","venue":null,"work_id":"841d61b6-9440-4a45-a368-a49ee1e5a51e","year":null},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.268835Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:d5a30aaab11e83982d330b7856a24c87c604ad05ddef8d19d64ac11f6f13ab97","observation_id":"d99c2d05-c783-4a7e-b08c-050e6929347e","resolution":{"observed_at":"2026-08-12T04:38:02.717653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.695777Z","title":"Towards coherent image in- painting using denoising diffusion implicit models","venue":null,"work_id":"2feadf96-f4b4-4f70-ae37-9a40bf8d2125","year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.275905Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:9f194982da3d705fdbbfd087e7828a70ea5e2f469771502874e20046f08c868d","observation_id":"dfe5428e-6a8b-445a-9757-0fe97cfc1f04","resolution":{"observed_at":"2026-08-12T04:38:02.701316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.678386Z","title":"Adding conditional control to text-to-image diffusion models","venue":null,"work_id":"7028c96a-bc06-4a91-b5bc-9a06b3b8789c","year":2023},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.282522Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:6bfc57fb3ceff2440b464e224ae7aa3197cef109e0c5232dc29e6fcd47e461bb","observation_id":"67167e36-4b0a-4bce-9009-2c93cbece0e2","resolution":{"observed_at":"2026-08-12T04:38:02.683317Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.10428","last_updated":"2021-03-18T17:59:11Z","snapshot_observed_at":"2026-08-13T19:55:33.904329Z","submitted_at":"2021-03-18T17:59:11Z","title":"Large Scale Image Completion via Co-Modulated Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.10428","snapshot_observed_at":"2026-08-12T04:38:02.288176Z","title":"Large scale image comple- tion via co-modulated generative adversarial networks.arXiv preprint arXiv:2103.10428, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.288176Z"},"links":{"cited_paper":"/paper/2103.10428","citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:b7b6355de195c5881f5bc4130d3baf03c09bb2729580e393c788e8c05e7355a3","observation_id":"ef3560c7-f4ed-4fce-8abc-b80c37b63855","resolution":{"observed_at":"2026-08-12T04:38:02.288176Z","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":"2026-08-12T04:38:02.294160Z","title":"Pluralistic image completion","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.294160Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:63327544f0a0a523ae7c03466ba34ad741a9190281be79a07e65e464bc571683","observation_id":"e185bfba-95e8-457e-a282-03296a4954ea","resolution":{"observed_at":"2026-08-12T04:38:02.294160Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.651770Z","title":"Image inpainting with cascaded modulation gan and object-aware training","venue":null,"work_id":"ced66428-34aa-42d9-8c7d-f14976f77b1b","year":2022},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.299692Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:9bb0f0d0b4bc81dec8056fdbbd1cc4718635d916303d89cd52370a846aafcfa6","observation_id":"8ae1702d-2fb9-426f-8f4e-9df092f1317a","resolution":{"observed_at":"2026-08-12T04:38:02.656575Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.635519Z","title":null,"venue":null,"work_id":"4361a781-cf10-4b1b-918f-a05b76519590","year":null},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.304968Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:fa464f119463720bb35b64e563635d7b3f6b72f4a838739f085b4580d8e39261","observation_id":"c484a0c9-237f-428c-af1d-9232d884b024","resolution":{"observed_at":"2026-08-12T04:38:02.640377Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.619482Z","title":null,"venue":null,"work_id":"6260e7af-b1e6-47a7-a9e2-5aae54b48776","year":null},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.310075Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:5ada0e355f4ccbf4376c820f131c1b8712444997b3b50b511fbf2b10aa0f7e3b","observation_id":"9646e536-038b-4f3c-94d8-46dbd49dc2fb","resolution":{"observed_at":"2026-08-12T04:38:02.624367Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:38:02.600955Z","title":"8, our PainterBench ensures a uniform distribution among various categories, including humans, animals, cartoons, as well as indoor and outdoor scenes","venue":null,"work_id":"1734a78a-d5ff-484b-b522-edb4b7015a3b","year":null},"citing_paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-12T04:38:02.315863Z"},"links":{"citing_paper":"/paper/2412.01223"},"observation_digest":"sha256:b53e3bca28a8d1ff4d28b99a5c448da8824d40d0a8186ab43a7f2d0533a4c5c9","observation_id":"788d3a88-bdb8-4da8-bf87-ef5ffc1b847c","resolution":{"observed_at":"2026-08-12T04:38:02.608340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.01223","last_updated":"2024-12-02T07:40:47Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T07:14:57.148802Z","submitted_at":"2024-12-02T07:40:47Z","title":"PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control"},"reference_resolution":{"displayed":58,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":37,"verified_exact":0,"verified_fuzzy":21},"total_outbound_references":58},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2412.01223."}