{"as_of":"2026-08-08T12:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f74132270c0ba4f143225540b0e2166f0c48a70afbfaaa03538b6fd2154fe4bb","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T04:23:09.771186Z","state":"measured"},{"denominator":87,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":87,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":27,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":27,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T00:41:15.247986Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T13:29:50.921149Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-08-04T22:58:08.819616Z","title":"Hpsv3: Towards wide-spectrum human preference score","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.06942","last_updated":"2025-09-11T17:14:11Z","snapshot_observed_at":"2026-08-08T03:23:05.134967Z","submitted_at":"2025-09-08T17:54:08Z","title":"Directly Aligning the Full Diffusion Trajectory with Fine-Grained Human Preference","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T22:58:08.819616Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2509.06942"},"observation_digest":"sha256:4f9966d1dd31a2aca6aec33ab2dd12e5a96bf7c94a9e440aeae80f03c991b59c","observation_id":"5134029c-8262-4629-9416-3e3bcc9275c4","resolution":{"observed_at":"2026-08-04T22:58:08.819616Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-08-04T20:08:58.995776Z","title":"Hpsv3: Towards wide-spectrum human preference score","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.08826","last_updated":"2025-09-10T17:59:31Z","snapshot_observed_at":"2026-08-07T13:58:40.131270Z","submitted_at":"2025-09-10T17:59:31Z","title":"RewardDance: Reward Scaling in Visual Generation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-04T20:08:58.995776Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2509.08826"},"observation_digest":"sha256:9d9c7691831fa2370a11f960bbf30f666d6e4495122e77fc042fe214d0ac54d6","observation_id":"3930fdb3-dd8b-4d9a-abf8-1030b39d043a","resolution":{"observed_at":"2026-08-04T20:08:58.995776Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2510.21583","last_updated":"2026-05-20T09:16:04Z","snapshot_observed_at":"2026-07-06T22:33:58.663508Z","submitted_at":"2025-10-24T15:50:36Z","title":"Principled RL for Flow Matching Emerges from the Chunk-level Policy Optimization","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-21T19:47:48.545820Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2510.21583"},"observation_digest":"sha256:01ebb45dcf17f078a60840c5ed759a76f35d3d6b0e6bccff3d8a0a673ca51d75","observation_id":"2677e3f0-2f34-4f8a-ba04-f4c16eed30f8","resolution":{"observed_at":"2026-05-21T19:50:33.819081Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2512.01236","last_updated":"2026-04-09T08:04:17Z","snapshot_observed_at":"2026-08-02T07:28:05.240599Z","submitted_at":"2025-12-01T03:25:49Z","title":"PSR: Scaling Multi-Subject Personalized Image Generation with Pairwise Subject-Consistency Rewards","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-17T03:49:05.489626Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2512.01236"},"observation_digest":"sha256:5f310e8767e8fa28ba708c66f90b307bdedd844a09205c2866a67707ee7fbaa6","observation_id":"cb8f2f66-0882-4ee5-9276-91f461e3dbe4","resolution":{"observed_at":"2026-05-17T03:51:29.476948Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-08-02T23:59:15.904880Z","title":"10 FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Mao, W., Chen, H., Yang, Z., and Shou, M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.12155","last_updated":"2026-06-29T06:08:55Z","snapshot_observed_at":"2026-08-07T09:48:03.626010Z","submitted_at":"2026-02-12T16:36:33Z","title":"FAIL: Flow Matching Adversarial Imitation Learning for Image Generation","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T23:59:15.904880Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2602.12155"},"observation_digest":"sha256:63ddd1101e6e4f1f1780643bd5a9a7b3f7dc4295ffdf50b1b39213aadd334bcb","observation_id":"71aaac17-d079-4327-a4b9-f971fe9f3c99","resolution":{"observed_at":"2026-08-02T23:59:15.904880Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2604.09850","last_updated":"2026-04-10T19:25:24Z","snapshot_observed_at":"2026-07-06T22:58:38.807460Z","submitted_at":"2026-04-10T19:25:24Z","title":"Training-Free Object-Background Compositional T2I via Dynamic Spatial Guidance and Multi-Path Pruning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-10T17:56:06.693585Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2604.09850"},"observation_digest":"sha256:b1ceb67e53df618d6104a564748e1a9fda52764db89328d702127ea238d77755","observation_id":"19182bdb-4dc4-4a5b-bcaa-dd6fdf17c652","resolution":{"observed_at":"2026-05-11T05:51:02.036761Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2604.18258","last_updated":"2026-04-20T13:31:36Z","snapshot_observed_at":"2026-07-06T23:05:08.728446Z","submitted_at":"2026-04-20T13:31:36Z","title":"Long-Text-to-Image Generation via Compositional Prompt Decomposition","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-05-10T04:22:19.645747Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2604.18258"},"observation_digest":"sha256:5792d368986fe74dab7be0e1c9a6824489340efb4a4d6d5d266e09cf06294516","observation_id":"90638b16-0944-4b42-a39a-398e937b0e1f","resolution":{"observed_at":"2026-05-11T12:01:03.725601Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2604.24953","last_updated":"2026-04-29T03:07:25Z","snapshot_observed_at":"2026-07-06T23:10:52.763251Z","submitted_at":"2026-04-27T19:49:06Z","title":"ViPO: Visual Preference Optimization at Scale","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-08T04:12:47.226661Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2604.24953"},"observation_digest":"sha256:84c94283cdeeef834669dfb3e01dee1d4e7baddaa7f55f2af04cb7780622c540","observation_id":"4bddcaa1-22fd-42ad-a4d8-a0aa7fdc6c26","resolution":{"observed_at":"2026-05-11T21:51:12.351712Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2604.27505","last_updated":"2026-05-20T07:08:10Z","snapshot_observed_at":"2026-07-06T23:12:57.730833Z","submitted_at":"2026-04-30T06:54:39Z","title":"Leveraging Verifier-Based Reinforcement Learning in Image Editing","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-07T08:00:33.307429Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2604.27505"},"observation_digest":"sha256:98f3d87730004cd16c70ccd8a0bd6233bccfec1a234b4be148e81209d3585ed3","observation_id":"9f83125f-809a-40d1-ae43-75bb23ff2a85","resolution":{"observed_at":"2026-05-12T10:06:27.626523Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2604.27505","last_updated":"2026-05-20T07:08:10Z","snapshot_observed_at":"2026-07-06T23:12:57.730833Z","submitted_at":"2026-04-30T06:54:39Z","title":"Leveraging Verifier-Based Reinforcement Learning in Image Editing","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-21T09:11:02.183133Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2604.27505"},"observation_digest":"sha256:0ea5f593a265db522fd8d15d193b7afd4d6d8b145c62876f3746830a101cb429","observation_id":"eab95291-766e-46bc-b26e-afd6f4a50baf","resolution":{"observed_at":"2026-05-21T09:14:05.939576Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2605.14278","last_updated":"2026-05-14T02:24:46Z","snapshot_observed_at":"2026-07-06T23:25:44.508166Z","submitted_at":"2026-05-14T02:24:46Z","title":"KVPO: ODE-Native GRPO for Autoregressive Video Alignment via KV Semantic Exploration","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-15T02:38:14.180433Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2605.14278"},"observation_digest":"sha256:2fc73ffdc53d010d53a476c08b2479e0783bf1a0400554acb6961d15fc7ad974","observation_id":"24b9a4fa-b64f-4d89-a34d-843a79e7ca7b","resolution":{"observed_at":"2026-05-15T02:38:34.512044Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2605.16842","last_updated":"2026-05-16T06:59:54Z","snapshot_observed_at":"2026-07-06T23:27:57.805018Z","submitted_at":"2026-05-16T06:59:54Z","title":"Sketch Then Paint: Hierarchical Reinforcement Learning for Diffusion Multi-Modal Large Language Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-19T21:18:03.005508Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2605.16842"},"observation_digest":"sha256:e92cac85ab7bf7714e356f947ea6ab3ad444df8a1bccbaa49ef757acad7d9dbe","observation_id":"65ca208e-e063-481a-9b88-fbb1c8e4aceb","resolution":{"observed_at":"2026-05-19T21:22:48.489020Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2605.19320","last_updated":"2026-06-02T07:39:57Z","snapshot_observed_at":"2026-08-02T16:37:25.437984Z","submitted_at":"2026-05-19T03:55:59Z","title":"TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-20T06:59:27.578911Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2605.19320"},"observation_digest":"sha256:4b69db8de313e2ba5c54cff58df432a746dd7498fc7b5fc6505cf30bba6ea0db","observation_id":"22011102-de29-441e-b296-66b1dd86d3e4","resolution":{"observed_at":"2026-05-20T07:03:06.372500Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2605.19320","last_updated":"2026-06-02T07:39:57Z","snapshot_observed_at":"2026-08-02T16:37:25.437984Z","submitted_at":"2026-05-19T03:55:59Z","title":"TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-30T18:51:00.698045Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2605.19320"},"observation_digest":"sha256:9fb77ccdb853e22f87c9e5b75a42e7a977c173226e93108656bc3d1592a98e70","observation_id":"e215f9fc-ada4-4829-912b-4a14739d3538","resolution":{"observed_at":"2026-06-30T18:55:00.419877Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2605.25759","last_updated":"2026-05-25T12:10:23Z","snapshot_observed_at":"2026-07-06T23:35:41.527169Z","submitted_at":"2026-05-25T12:10:23Z","title":"Towards Anatomically Plausible Human Image Generation via Synthetic Localized Preferences","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-29T22:55:02.514189Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2605.25759"},"observation_digest":"sha256:6ae781a03008f29ecdd1073a98f848e2bef4f574aa2592b53233ba39e87fa5e2","observation_id":"5a27f2a6-1ab9-4bfb-80b3-d4370a62de2f","resolution":{"observed_at":"2026-06-30T00:14:04.754528Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2605.25874","last_updated":"2026-05-25T14:01:31Z","snapshot_observed_at":"2026-07-06T23:35:46.157653Z","submitted_at":"2026-05-25T14:01:31Z","title":"WBench: A Comprehensive Multi-turn Benchmark for Interactive Video World Model Evaluation","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-06-29T22:57:08.381846Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2605.25874"},"observation_digest":"sha256:de96660ce647890cca5f810bfc45264864c31e32dce6d8369dedb1f79cc66061","observation_id":"a8a1252e-30a1-464b-95e1-0cb3ff3ac615","resolution":{"observed_at":"2026-06-29T23:14:02.285755Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2606.01985","last_updated":"2026-06-01T09:46:10Z","snapshot_observed_at":"2026-08-05T13:43:57.622962Z","submitted_at":"2026-06-01T09:46:10Z","title":"MT-EditFlow: Reinforcement Learning for Multi-Turn Image Editing with Flow Matching","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-28T15:07:29.897089Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2606.01985"},"observation_digest":"sha256:4b44edf6f7de4331e60ab5ad4e8c3359f02a7d5c0eb50bd153e55b7f6294246d","observation_id":"abad0b26-a2e5-4adb-8205-98dd4a37352b","resolution":{"observed_at":"2026-07-01T22:46:18.535951Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2606.03216","last_updated":"2026-06-02T06:22:07Z","snapshot_observed_at":"2026-08-02T20:47:25.605127Z","submitted_at":"2026-06-02T06:22:07Z","title":"Follow-Your-Preference++: Rethinking Preference Alignment for Image Inpainting","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-28T10:51:40.605583Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2606.03216"},"observation_digest":"sha256:012d9b02fef72326db36afa99609aa12b9f79a6afbc101379ae65d67d2adc1ef","observation_id":"dbe8e974-237e-4907-9c4b-8cefdf710cba","resolution":{"observed_at":"2026-07-02T02:36:26.419667Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2606.09076","last_updated":"2026-07-14T12:46:55Z","snapshot_observed_at":"2026-07-17T23:19:03.633221Z","submitted_at":"2026-06-08T06:20:12Z","title":"Z-Reward: Beyond Scalar Rewards by Internalizing Reasoning into Score Distributions","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-27T17:30:57.001021Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2606.09076"},"observation_digest":"sha256:6cbfc02313bd8d22faafb10410f3cded0181cfe4574374abd789116410f6b8c7","observation_id":"7e312084-ae6f-4e50-889d-d613f20716ed","resolution":{"observed_at":"2026-07-03T00:07:27.955173Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-15T10:53:37.186361Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.09076","last_updated":"2026-07-14T12:46:55Z","snapshot_observed_at":"2026-07-17T23:19:03.633221Z","submitted_at":"2026-06-08T06:20:12Z","title":"Z-Reward: Beyond Scalar Rewards by Internalizing Reasoning into Score Distributions","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-15T10:53:37.186361Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2606.09076"},"observation_digest":"sha256:6d95cfcabd38e78fdc1332e9112c5b24fc10c97b6c3bb6f94205846ae0e8c0dd","observation_id":"0605ba11-0405-4dd2-af52-88bb38c116f2","resolution":{"observed_at":"2026-07-15T10:53:37.186361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2606.26930","last_updated":"2026-06-25T12:05:40Z","snapshot_observed_at":"2026-08-02T23:20:42.422710Z","submitted_at":"2026-06-25T12:05:40Z","title":"PortraitGen: Exemplar-Driven GRPO with Dual-Reward Guidance for Photorealistic Portrait Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-26T05:14:14.053344Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2606.26930"},"observation_digest":"sha256:8ea0e5c7cdf747c04e53f8510d11f3d805c64a26e6de427cedecd454edcb9116","observation_id":"e590b6e3-c7e9-4594-ab44-8bbc38786dae","resolution":{"observed_at":"2026-07-04T13:29:50.922769Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2606.32020","last_updated":"2026-06-30T17:51:26Z","snapshot_observed_at":"2026-08-03T10:16:58.559510Z","submitted_at":"2026-06-30T17:51:26Z","title":"Cross-Space Distillation: Teaching One-Step Students with Modern Diffusion Teachers","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-01T05:35:48.896721Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2606.32020"},"observation_digest":"sha256:db7deb6e3e39b5cfc2662a5aeef44dddea7eff0a15aa2e0f985073ce14e17f51","observation_id":"d0f7a228-40f6-453f-9fde-4d2f876f7949","resolution":{"observed_at":"2026-07-01T10:25:41.130895Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":"2508.03789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-04T13:29:50.921149Z","title":"Hpsv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789","venue":null,"work_id":"07750820-6650-4ada-bb72-56cbca3871f6","year":2025},"citing_paper":{"arxiv_id":"2607.02220","last_updated":"2026-07-02T14:26:47Z","snapshot_observed_at":"2026-08-01T18:29:16.831004Z","submitted_at":"2026-07-02T14:26:47Z","title":"DetailAnywhere: Fashion Detail Generation via Cross-Modal Feature Alignment Distillation","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-07-03T15:56:38.037304Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2607.02220"},"observation_digest":"sha256:2c344edbcb64344b94625a6a436b50afb9672aace6ea952d23a9de7f8d08ccc6","observation_id":"97fe4345-8912-4985-b68d-2b92e4dbf097","resolution":{"observed_at":"2026-07-03T15:58:37.254282Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-30T21:02:13.315381Z","title":"Hpsv3: Towards wide-spectrum human preference score, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23488","last_updated":"2026-07-26T06:29:48Z","snapshot_observed_at":"2026-08-08T07:35:57.574796Z","submitted_at":"2026-07-26T06:29:48Z","title":"Learning Sampling Parameters for Diffusion Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-30T21:02:13.315381Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2607.23488"},"observation_digest":"sha256:565a30be58c1ae3f244df1730925f3211b8d98e98b5865e3f1889627a41df17a","observation_id":"414e59cd-b9be-4d6e-9ceb-89539c5f78ee","resolution":{"observed_at":"2026-07-30T21:02:13.315381Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-07-30T23:47:57.932110Z","title":"HPSv3: Towards wide-spectrum human preference score,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.26694","last_updated":"2026-07-29T09:40:23Z","snapshot_observed_at":"2026-08-07T09:33:33.406786Z","submitted_at":"2026-07-29T09:40:23Z","title":"Visko Orbis 1.0: A Live Model for Real-Time Interactive Long Video Generation","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-07-30T23:47:57.932110Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2607.26694"},"observation_digest":"sha256:6c3fa558a3340c05f915dccbc0de43c2283fa141217c7175316a9fb863497edc","observation_id":"ad202311-8bf3-486e-bc24-2de653302391","resolution":{"observed_at":"2026-07-30T23:47:57.932110Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-08-05T05:39:05.785791Z","title":"HPSv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.03929","last_updated":"2026-08-05T03:09:27Z","snapshot_observed_at":"2026-08-08T12:11:19.155122Z","submitted_at":"2026-08-04T17:00:52Z","title":"Latent Reward Registers for Diffusion Preference Alignment","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-05T05:39:05.785791Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2608.03929"},"observation_digest":"sha256:ada51e9b89ae0cf24ad3bdd69b952fb6f5ad54008e9107ece9ee7f2212ba9c31","observation_id":"81f63623-db3f-4dd1-8688-662ffb68d2cf","resolution":{"observed_at":"2026-08-05T05:39:05.785791Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.03789","snapshot_observed_at":"2026-08-08T00:41:15.247986Z","title":"HPSv3: Towards wide-spectrum human preference score.arXiv preprint arXiv:2508.03789,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.03929","last_updated":"2026-08-05T03:09:27Z","snapshot_observed_at":"2026-08-08T12:11:19.155122Z","submitted_at":"2026-08-04T17:00:52Z","title":"Latent Reward Registers for Diffusion Preference Alignment","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-08T00:41:15.247986Z"},"links":{"cited_paper":"/paper/2508.03789","citing_paper":"/paper/2608.03929"},"observation_digest":"sha256:ba88ca734927feeebb66d7e1ea2c10eada576c49a6e630ac0cbf1be3333063a8","observation_id":"99d4c96a-3ee5-46f2-a405-0b03b7ab838b","resolution":{"observed_at":"2026-08-08T00:41:15.247986Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2508.03789/citation-record","integrity":"/paper/2508.03789/integrity","json":"/paper/2508.03789/citation-record.json","paper":"/paper/2508.03789"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T04:23:18.610894Z","title":"Flux.1 [dev]: 12b-parameter open-source text-to-image diffusion model, 2024","venue":null,"work_id":"66d943ad-8fe6-440a-9bed-df83f8fee9df","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:04.631083Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:5d6a3d242eaee41bfc74150d457cde338d905a7416b7b48f4778dcd38f276ca7","observation_id":"5bb28ef2-a586-472a-813b-6cd6542a7dfc","resolution":{"observed_at":"2026-08-06T04:23:18.669319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:18.345219Z","title":"Rank analysis of incomplete block designs: I","venue":null,"work_id":"ed7017ff-6ce6-460e-afb3-f7f450461101","year":1952},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:04.717142Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:b49ac4e26be7cd53b02a70582320a7781a34a44dabc5836098ecb7c42b6f7be1","observation_id":"6cab7da5-c153-4c0f-9f1e-24a56cc9bb3e","resolution":{"observed_at":"2026-08-06T04:23:18.474749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-06T04:23:04.802017Z","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":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:04.802017Z"},"links":{"cited_paper":"/paper/2310.00426","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:d75694d6d724b5b997d8f8ac0f1353b2e9a28b74dd1b7e552e7f31de3a9bb228","observation_id":"0a2fddd8-8fd2-4960-8c26-1da23dacd150","resolution":{"observed_at":"2026-08-06T04:23:04.802017Z","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":"2026-08-06T04:23:18.113599Z","title":"Pixart- σ: Weak-to-strong training of dif- fusion transformer for 4k text-to-image generation, 2024","venue":null,"work_id":"f7cf6a05-6b6d-4684-9c25-58deb2ace83e","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:04.885964Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:93115027ee81c992dfdd9df7609557eaa8462d6f1745db9730acc719039a9624","observation_id":"25682877-7ae6-4c76-b739-203be115c6a1","resolution":{"observed_at":"2026-08-06T04:23:18.184948Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:17.834831Z","title":"Lawrence Zitnick","venue":null,"work_id":"59974ee6-6418-4560-aeca-6084dab46185","year":2015},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:04.949594Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:30ff094b4affeaa0476e7e49a52f0e099924a816fce5144c9723b9620d8a13cd","observation_id":"48701548-30be-4cce-a6dc-0ac2239416e9","resolution":{"observed_at":"2026-08-06T04:23:17.955880Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:17.562626Z","title":"Cogview2: Faster and better text-to-image generation via hi- erarchical transformers","venue":null,"work_id":"b18f75d7-f084-473c-baa1-0f818a23d503","year":2022},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.055307Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:17b372ae815f63f287587231d57c15be039630c7489e4ddda262990061bb8395","observation_id":"a2eed7e2-8651-4e5a-be13-e97157fd8a2e","resolution":{"observed_at":"2026-08-06T04:23:17.664872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:17.248643Z","title":"Taming transformers for high-resolution image synthesis","venue":null,"work_id":"82ce7e73-f082-4644-8556-e2c02c61a7ab","year":2021},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.106231Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:abfa9c0842348d4b77af6d8a40d3372a4cb8003d8ed5f5b5063d1975a82d5bb9","observation_id":"ab60297a-bbe9-4466-a3a1-ddc70af26c29","resolution":{"observed_at":"2026-08-06T04:23:17.362684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:16.904386Z","title":"Scaling rectified flow trans- formers for high-resolution image synthesis, 2024","venue":null,"work_id":"33fddbb9-1c34-4d7c-ba34-c3eb86cf2dd1","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.196385Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:4dce547ee79b63b4e7833f214cdc39e8045a61f32d40cd72f8aa2a1dc896bfc8","observation_id":"da5236b1-73fd-46b6-a4c2-49d0e303b91b","resolution":{"observed_at":"2026-08-06T04:23:16.985745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13863","last_updated":"2024-10-17T17:59:59Z","snapshot_observed_at":"2026-08-07T22:15:46.490983Z","submitted_at":"2024-10-17T17:59:59Z","title":"Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13863","snapshot_observed_at":"2026-08-06T04:23:05.274006Z","title":"Fluid: Scaling autoregressive text-to-image generative models with continuous tokens","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.274006Z"},"links":{"cited_paper":"/paper/2410.13863","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:99a434ae833a46efbde74da1eba1c223184ab8670b8d16b9737679d8eb5fe3f7","observation_id":"851a5af6-4b4e-4604-a561-73280dab8e37","resolution":{"observed_at":"2026-08-06T04:23:05.274006Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04431","last_updated":"2025-06-17T15:32:20Z","snapshot_observed_at":"2026-08-07T20:34:58.400387Z","submitted_at":"2024-12-05T18:53:02Z","title":"Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04431","snapshot_observed_at":"2026-08-06T04:23:05.334022Z","title":"Infinity: Scaling bit- wise autoregressive modeling for high-resolution image syn- thesis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.334022Z"},"links":{"cited_paper":"/paper/2412.04431","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:5c2bbab50d2702a92e5a0cbc3de2c4a16ec95aa51425790cee3b993b821149c3","observation_id":"155d910e-423d-4de4-bec8-5cceba7a1d5e","resolution":{"observed_at":"2026-08-06T04:23:05.334022Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.01569","last_updated":"2023-11-23T17:07:58Z","snapshot_observed_at":"2026-08-05T16:14:24.029428Z","submitted_at":"2023-05-02T16:18:11Z","title":"Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.01569","snapshot_observed_at":"2026-08-06T04:23:05.410969Z","title":"Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.410969Z"},"links":{"cited_paper":"/paper/2305.01569","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:f476fd67891f4196d1b834378ef8e42d6e36d2f5a42b164c4290cf86baf166a7","observation_id":"236c6bc6-1aa2-4253-82bd-b5db1bd5bdb2","resolution":{"observed_at":"2026-08-06T04:23:05.410969Z","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":"2026-08-06T04:23:16.676691Z","title":"Instantportrait: One-step portrait editing via diffusion multi-objective distillation","venue":null,"work_id":"213813a3-3313-41d7-a7be-6803afeb0756","year":2025},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.482879Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:a19775d77a92e768650ac8b45f39b29503d788f598d1bc8f2369b1d66e233fd6","observation_id":"03db1d7d-2e80-477a-8030-2472ffac2cd1","resolution":{"observed_at":"2026-08-06T04:23:16.773158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:16.472277Z","title":"Playground v2.5: Three insights towards enhancing aesthetic quality in text-to-image genera- tion, 2024","venue":null,"work_id":"d1f5aeca-e0bb-4614-b2d5-f5ae25ded604","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.599740Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:2a2abd1d7e713b71827cafbbd9eea0d8a06f9c215165d52620fb31f0172e3620","observation_id":"56cfa6c1-6e67-407a-83fc-bbebc1463d93","resolution":{"observed_at":"2026-08-06T04:23:16.560413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:16.340788Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation","venue":null,"work_id":"e323cfbd-6865-4e36-884c-9696a2f30f44","year":2022},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.694744Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:29a14143dbc59a7a9417ec4d92b37eaea9360a816a1ca56a5fbd3f7a657cd153","observation_id":"6f4de011-cc54-4683-aab3-e9556467a60d","resolution":{"observed_at":"2026-08-06T04:23:16.403022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:05.815816Z","title":"Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.815816Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:7677aec78f40189f3c47f4053a228858bf645b1a4f43955591f8fd517ccd0dff","observation_id":"fa25e727-ed0e-4042-86b1-c860f7c08f28","resolution":{"observed_at":"2026-08-06T04:23:05.815816Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.18417","last_updated":"2024-03-27T10:09:38Z","snapshot_observed_at":"2026-07-06T17:51:48.378864Z","submitted_at":"2024-03-27T10:09:38Z","title":"ECNet: Effective Controllable Text-to-Image Diffusion Models","version":1},"cited_work":{"arxiv_id":"2403.18417","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.18417","snapshot_observed_at":"2026-08-06T04:23:10.342375Z","title":"ECNet: Effective Controllable Text-to-Image Diffusion Models","venue":"cs.CV","work_id":"bff57559-616a-44eb-8260-c12152d03a98","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:05.934979Z"},"links":{"cited_paper":"/paper/2403.18417","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:5ebbdfb7d15c46d297d1a6c15006f463d9a0ca5cfd299e3d5121d777a07be143","observation_id":"0f04dd37-7b46-4ab8-93f7-ac42404430b4","resolution":{"observed_at":"2026-08-06T04:23:10.431809Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:16.166594Z","title":"Hunyuan-dit: A powerful multi-resolution diffusion trans- former with fine-grained chinese understanding, 2024","venue":null,"work_id":"2a4a4ad8-832a-4fbb-a80c-79bd043ed8c3","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.042120Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:636fbf7fed7b9534a9e6e5ded1e7b7af9aca0fcd2222c89366725667e6173e74","observation_id":"284becdd-475e-46ab-aa44-a6e8676e3032","resolution":{"observed_at":"2026-08-06T04:23:16.251926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:15.904423Z","title":"Llm4gen: Leveraging semantic representation of llms for text-to-image generation, 2024","venue":null,"work_id":"840e5c09-fa34-4159-8e3d-3dcbd3629b6e","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.159142Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:3ab9bc5960e6bc6628d255d18364af9b104b3f15d95c21d51c180a4bae20cb2d","observation_id":"b6ec330c-0bd6-4359-94b9-406bf1776006","resolution":{"observed_at":"2026-08-06T04:23:16.075556Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.01573","last_updated":"2021-12-02T19:27:27Z","snapshot_observed_at":"2026-08-06T14:23:50.362039Z","submitted_at":"2021-12-02T19:27:27Z","title":"FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.01573","snapshot_observed_at":"2026-08-06T04:23:06.191380Z","title":"Fusedream: Training-free text-to-image generation with improved clip+ gan space op- timization","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.191380Z"},"links":{"cited_paper":"/paper/2112.01573","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:0d3792b077dcd71f845838f3aa6cc47a38a2aba0866681b9ccca91b4044f91b7","observation_id":"b1b25ea2-9a45-43ff-92a3-f9aa07cc823a","resolution":{"observed_at":"2026-08-06T04:23:06.191380Z","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":"2026-08-06T04:23:15.730864Z","title":"New theory about light and colours","venue":null,"work_id":"91f8580e-6408-40d8-935d-62ecabf9c9d9","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.257226Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:3c5814bc8750cdb7f6e2061a0e50a575c078e1ea940dbb7ab4e26cc39a712352","observation_id":"18d4a51e-256c-4555-a4b8-d9faa933ba71","resolution":{"observed_at":"2026-08-06T04:23:15.818247Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:15.505126Z","title":"GLIDE: Towards Photorealistic Image Gener- ation and Editing with Text-Guided Diffusion Models","venue":null,"work_id":"935d903d-9475-44cb-9908-049446e7bfa0","year":2021},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.349820Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:3a866204cd3cc8e2caf4971f21b6e83f9e3ebf500312b3224ed0db36639fc3d5","observation_id":"17b939ec-9118-4952-8c33-887bab4fe1fe","resolution":{"observed_at":"2026-08-06T04:23:15.620629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:15.319074Z","title":"Inverting generative adversarial renderer for face reconstruction","venue":null,"work_id":"c3db8f46-dac7-4c44-a18b-b6b41cdb6e3c","year":2021},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.412450Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:f862ccf7f5b5093b2766877da0d9118934f56f902343e7c322d33acb3072f43e","observation_id":"1f4ba282-7a05-4844-8a32-2dff8a319f40","resolution":{"observed_at":"2026-08-06T04:23:15.406330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-06T04:23:06.513482Z","title":"Sdxl: Improving latent diffusion mod- els for high-resolution image synthesis","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.513482Z"},"links":{"cited_paper":"/paper/2307.01952","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:380811ba44cf7d9b369221432e9676469b2bb1949f4a5a5a03bafada5ce24cf5","observation_id":"fdc15740-1081-4d77-9a0f-21c0a67c0985","resolution":{"observed_at":"2026-08-06T04:23:06.513482Z","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":"2026-08-06T04:23:06.598871Z","title":"Learning Transferable Visual Models From Natural Language Supervision","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.598871Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:1bcffd68f10c48a1f085bd371983fae49a5de00a0838e9e723bc7834a02d070a","observation_id":"a226d6fc-77f4-4ed8-8492-0a989a22e98a","resolution":{"observed_at":"2026-08-06T04:23:06.598871Z","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":"2026-08-06T04:23:06.646564Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.646564Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:5f0fe30410cae5b9f51c135654a84a85c5985ef32ac12638573a5da5c7046ef6","observation_id":"24b8a2d4-d677-41d1-9c6e-94f70fb67e13","resolution":{"observed_at":"2026-08-06T04:23:06.646564Z","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":"2026-08-06T04:23:06.699832Z","title":"Hierarchical Text-Conditional Image Gen- eration with CLIP Latents","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.699832Z"},"links":{"cited_paper":"/paper/2204.06125","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:bd6401019526a42d718eae35c1d97ebb0986df70ff699b6ccb4d9cc57e77b8b4","observation_id":"40d21a16-13bd-4079-aae2-d91178e5030b","resolution":{"observed_at":"2026-08-06T04:23:06.699832Z","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":"2026-08-06T04:23:15.049696Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"82c20d49-9376-4830-a513-a4a0b74c056c","year":2022},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.757024Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:8fdee4d2537738dc0e7ebdeda9c7c6a2a6dfcf6b925dc16df3aeebc421c4b4a7","observation_id":"6e6cbb4b-e7a0-424e-a5ed-c18a3ed0e0e2","resolution":{"observed_at":"2026-08-06T04:23:15.148647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:14.793732Z","title":"Blattmann, Dominik Lorenz, Patrick Esser, and Bj¨orn Ommer","venue":null,"work_id":"ecf0b7b9-d4a1-413e-bc4e-da3e377eca9b","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.848934Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:95d0a22f9002d5e24e898daf5fd2715f261954bf7bf75d4326e7d9d9bc6ec215","observation_id":"495baa4b-295b-4b79-a0ba-e868d80816ce","resolution":{"observed_at":"2026-08-06T04:23:14.906448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:06.921723Z","title":"Photorealistic text-to-image diffusion models with deep language understanding","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:06.921723Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:ca4f5ce224f282d5e49b855c78d422d9221c793cfe3b8bc39af07b4e67c76550","observation_id":"8909900f-ff18-49db-94eb-a64f75be4796","resolution":{"observed_at":"2026-08-06T04:23:06.921723Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.09515","last_updated":"2023-01-23T16:05:45Z","snapshot_observed_at":"2026-07-06T14:43:50.324853Z","submitted_at":"2023-01-23T16:05:45Z","title":"StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.09515","snapshot_observed_at":"2026-08-06T04:23:07.025510Z","title":"StyleGAN-T: Unlocking the power of gans for fast large-scale text-to-image synthesis","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.025510Z"},"links":{"cited_paper":"/paper/2301.09515","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:868010fb5ea8c38be2d1a23c9456a7bdcbe5499a98b0365ecf9e92681e2e66d4","observation_id":"9d382e1a-6d3c-44fe-b09d-0f78938d98f1","resolution":{"observed_at":"2026-08-06T04:23:07.025510Z","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":"2026-08-06T04:23:14.549994Z","title":"Clip+mlp aesthetic score pre- dictor","venue":null,"work_id":"4447293d-a6c8-4e81-8f8c-319db3c1d80f","year":2022},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.114573Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:5fbb1eb117697efd756136c98ccf73a7fba406f8d8c22257e561d8555857753c","observation_id":"3d2fd977-070a-4db4-9d14-0e5577ae4157","resolution":{"observed_at":"2026-08-06T04:23:14.680327Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-07-29T21:51:47.064287Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-06T04:23:07.177967Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.177967Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:3a85dd54356bc0135d8db1cd96cafc73d354b036eb71ea79b053ee534282ade4","observation_id":"f9f1caf8-e4a0-4114-9dda-3b9ea13e0c0c","resolution":{"observed_at":"2026-08-06T04:23:07.177967Z","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":"2026-08-06T04:23:14.235192Z","title":"Controllable 3d face syn- thesis with conditional generative occupancy fields","venue":null,"work_id":"a8414362-8f87-4fd4-b4f4-1e6975019898","year":2022},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.247710Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:cadbedf293ced1d7ed2b82833fc041465a594d5f6dd0eb5338c7218df54432cc","observation_id":"ede2ba73-b317-4435-9349-e46324056e31","resolution":{"observed_at":"2026-08-06T04:23:14.345906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:14.059206Z","title":"Journeydb: A benchmark for generative image under- standing, 2023","venue":null,"work_id":"d09e2bc1-a3f2-4fd8-a1c4-7bcd50a0630b","year":2023},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.342992Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:f5a79dd3b509f1aee5351f9caea82aa877c3e1f2564e58d3de92fc555bb01370","observation_id":"1e88ac19-7dee-4620-93f0-25ed9dc82a2b","resolution":{"observed_at":"2026-08-06T04:23:14.109571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:13.965832Z","title":"Cgof++: Controllable 3d face synthesis with conditional generative occupancy fields","venue":null,"work_id":"156e6819-9902-4fb3-a9b1-c40a710fd57e","year":2023},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.414960Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:5d489750a5602738fff44d32ad5f54d3e7dafb06520a961ce5e861b153a47b49","observation_id":"34c09bec-4d6c-42b1-95d0-486a3abd6abf","resolution":{"observed_at":"2026-08-06T04:23:14.047473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.13674","last_updated":"2024-08-24T21:25:22Z","snapshot_observed_at":"2026-07-06T19:05:31.646924Z","submitted_at":"2024-08-24T21:25:22Z","title":"GenCA: A Text-conditioned Generative Model for Realistic and Drivable Codec Avatars","version":1},"cited_work":{"arxiv_id":"2408.13674","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.13674","snapshot_observed_at":"2026-08-06T04:23:10.101968Z","title":"GenCA: A Text-conditioned Generative Model for Realistic and Drivable Codec Avatars","venue":"cs.CV","work_id":"ff274a6e-c329-4a41-93a2-b3adf3876e03","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.496508Z"},"links":{"cited_paper":"/paper/2408.13674","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:05fb37e555ec3551606833304586e74182dd4d42ec649d6bed55703d3a267e54","observation_id":"f56ed9bb-b3e7-4da6-ab8d-9c4eee0ed46a","resolution":{"observed_at":"2026-08-06T04:23:10.161876Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:13.829642Z","title":"Probabilistic uncertain reward model, 2025","venue":null,"work_id":"fc2f40cf-0acf-4e1f-9705-c55d44a052cd","year":2025},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.569939Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:ef536ecb00b7768beaac3fb1d9acd20a28df6fecbb217a4e85db382d4bc5a626","observation_id":"172bb0a1-b6f6-4302-87c7-9e218b5471b8","resolution":{"observed_at":"2026-08-06T04:23:13.894322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:07.606219Z","title":"Kolors: Effective training of diffusion model for photorealistic text-to-image synthesis","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.606219Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:3992c86bcca2a5de087149f7d9d1a7b2a47451f0ad58f5af358d3e20f7e1b05d","observation_id":"cf8f1e09-78bb-4084-9b0f-d7583caaca4a","resolution":{"observed_at":"2026-08-06T04:23:07.606219Z","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":"2026-08-06T04:23:13.660880Z","title":"Visual autoregressive modeling: Scalable image generation via next-scale prediction","venue":null,"work_id":"f786c834-fe1b-4304-807f-4b282ddc8922","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.674924Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:b8e596b479c066a332f53eb5fdf3bb2914942a5d6587be26bfd3ddbc0425c992","observation_id":"58307222-e8e3-401a-a38a-fc5a9f2a293e","resolution":{"observed_at":"2026-08-06T04:23:13.716502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:13.515795Z","title":"Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution, 2024","venue":null,"work_id":"2b6ebb45-606e-4d1f-b5a0-0d875aa8ebf7","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.738857Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:2866ce9d5ce96d800b356ad40a7ac1c97cd310f3946c64b6088a3e7889fff319","observation_id":"4146c215-2049-44b0-9000-afdf2808e3ef","resolution":{"observed_at":"2026-08-06T04:23:13.590463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:13.372700Z","title":"Human preference score v2: A solid benchmark for evaluating human preferences of text-to-image synthesis, 2023","venue":null,"work_id":"008c3988-b282-4c93-bf28-b36da9b9c69a","year":2023},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.807906Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:ae561ae979a4f90e2d189789f1e811fbf0520f2588ba4f19b43e0aefc5c8ba1b","observation_id":"9e9736aa-067c-40be-9efe-b4ebd13a4257","resolution":{"observed_at":"2026-08-06T04:23:13.441335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:13.232763Z","title":"Better Aligning Text-to-Image Models with Hu- man Preference, 2023","venue":null,"work_id":"5d73d271-b4c2-474c-934c-22d4900827d2","year":2023},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.893160Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:215da92904287d1428a9a5278c9c1e60a8e3670b3ba5aa94750190551fc61c08","observation_id":"c12feaf1-4000-42f0-8a5f-b80a045d4c71","resolution":{"observed_at":"2026-08-06T04:23:13.282394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:13.119365Z","title":"Human preference score: Better aligning text- to-image models with human preference","venue":null,"work_id":"ff8436d9-bcf4-4866-836c-37340b8942df","year":2023},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.983974Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:e24d3a8d27b99d3602a16e6fecc69c7b5a25a9c7f802f75c9dd67432b50beb47","observation_id":"606bdf9d-2cbe-4805-ba41-602d7a986198","resolution":{"observed_at":"2026-08-06T04:23:13.176181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:12.950135Z","title":"Deep reward supervisions for tuning text-to-image diffusion models","venue":null,"work_id":"d069eeda-e129-4d9b-aacb-21b2faaa697c","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.088654Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:04344576dba712a3a5419991c7789305a85ea30945d405ef84a8ebddcf69ec33","observation_id":"040c92d5-e01b-4d92-a37a-cb0993d80e43","resolution":{"observed_at":"2026-08-06T04:23:13.008193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.04947","last_updated":"2025-07-07T12:45:23Z","snapshot_observed_at":"2026-08-08T12:12:25.015685Z","submitted_at":"2025-07-07T12:45:23Z","title":"DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer","version":1},"cited_work":{"arxiv_id":"2507.04947","doi":null,"metadata_source":"pith","pith_arxiv_id":"2507.04947","snapshot_observed_at":"2026-08-06T04:23:09.921374Z","title":"DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer","venue":"cs.CV","work_id":"80001308-6a23-4e21-bfd6-10e5f49608fa","year":2025},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.137866Z"},"links":{"cited_paper":"/paper/2507.04947","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:ec0c8c94ca842cefba7e9391f1c28a09909e23dff7c8f212b2ed055753cd9897","observation_id":"70406000-a5b0-4912-b562-5cf97973bb31","resolution":{"observed_at":"2026-08-06T04:23:09.993343Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:12.800783Z","title":"ImageReward: 10 Learning and Evaluating Human Preferences for Text-to- Image Generation, 2023","venue":null,"work_id":"f9592403-cc4f-4148-821d-b9aa0c273f60","year":2023},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.234165Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:bd606e92f0f71faf5734bdfc7c9a48a1e7c1e68426422afc261ed7dc5c6c9373","observation_id":"23235580-d5b6-44a0-a033-e7fd773ad0e5","resolution":{"observed_at":"2026-08-06T04:23:12.873810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:12.624778Z","title":"Imagere- ward: Learning and evaluating human preferences for text- to-image generation","venue":null,"work_id":"96db264d-3cf8-4dbe-a370-643741808fc8","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.318746Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:0d703c1935e7286bd35e9f879af45c62838e9f6b12f21bbe275c881261cdefa2","observation_id":"ed887f7b-82e3-4173-88a8-bd7c2691d774","resolution":{"observed_at":"2026-08-06T04:23:12.705930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.07818","last_updated":"2025-08-28T17:19:45Z","snapshot_observed_at":"2026-07-31T14:51:03.625964Z","submitted_at":"2025-05-12T17:59:34Z","title":"DanceGRPO: Unleashing GRPO on Visual Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.07818","snapshot_observed_at":"2026-08-06T04:23:08.436009Z","title":"Dancegrpo: Unleashing grpo on visual generation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.436009Z"},"links":{"cited_paper":"/paper/2505.07818","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:9902dcb184601a4f181540d2825d6188cdf9a70cb5758aeb87e38d0cd802d28a","observation_id":"62db4790-5ff8-4029-a1fa-820c03bead13","resolution":{"observed_at":"2026-08-06T04:23:08.436009Z","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":"2026-08-06T04:23:12.509163Z","title":"Learning multi- dimensional human preference for text-to-image generation,","venue":null,"work_id":"24eff9ac-187a-4f87-8989-06b5a36fa737","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.510045Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:b58e50321d99e7f8c1dfd078e0417bfac23e3b81e2513d219c5f67603a0cb6e8","observation_id":"c43354f3-119a-49a4-850a-2bc1751eabee","resolution":{"observed_at":"2026-08-06T04:23:12.559081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:12.319763Z","title":"Cogview3: Finer and faster text-to-image generation via relay diffusion, 2024","venue":null,"work_id":"8aa4d0bd-6f1f-40b4-a8ef-b3c17cf78fde","year":2024},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.605612Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:fce1b22ac5fabe245b0a86e3fff47e10627b2ed8efa98d338d4439b724b23844","observation_id":"40d21ead-5e65-4af8-b70c-42086d61d277","resolution":{"observed_at":"2026-08-06T04:23:12.417571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:12.148183Z","title":null,"venue":null,"work_id":"74496b06-eea7-40b9-992c-de707285df5c","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.681842Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:4863781c2ff62bd50f917cbf2cacb1d369f16931c4a017cbc3335be040924d48","observation_id":"2984f98b-0e26-4046-a3e4-e4c9c0f8d1b3","resolution":{"observed_at":"2026-08-06T04:23:12.237710Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:12.014659Z","title":"As shown in Figure S2, we compare the category distri- butions of HPDv3, HPDv2, ImageReward, and Pick-a-Pic datasets","venue":null,"work_id":"ca9ab8a9-f9f3-454c-9471-9124053a29b6","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.757421Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:430569b461b956244514593c35ce60ddd2b4e35308567cc82371089c869b703a","observation_id":"69602ab9-d877-458e-955a-e9fb6fd46945","resolution":{"observed_at":"2026-08-06T04:23:12.075167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:11.880090Z","title":null,"venue":null,"work_id":"68c639a8-83fc-4e56-b691-8e85044bd2d6","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.850622Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:b5881873f420ce33981cd228820998740f5bd93a9c0bc8c122141a971f84e64b","observation_id":"0678ac91-38cf-465c-ac21-8a83dd5a59b5","resolution":{"observed_at":"2026-08-06T04:23:11.941989Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:11.745601Z","title":"Image Annotation","venue":null,"work_id":"14e3e9dd-8ed0-4daf-8a71-3053064cc141","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:08.977421Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:c82dd9266551f2ceba7cc343296071bf33702b1bc4355d9fedd3430cd45eeedb","observation_id":"94043613-16a5-45d3-9e62-39c6d103283d","resolution":{"observed_at":"2026-08-06T04:23:11.794461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:11.610438Z","title":"Training Dataset For training our final model, we use data from four sources: HPDv3, subsets of Pick-A-Pic and ImageReward, and real user preference data collected from Midjourney","venue":null,"work_id":"45dcad79-9278-4f7b-a215-7611acb166be","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:09.075219Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:9d51205e91a6bf062bca3f74e1e1abce1586d4346c2f35fc09306d8e019782bd","observation_id":"f022e4bc-5560-490c-9566-de40fc181461","resolution":{"observed_at":"2026-08-06T04:23:11.666219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:11.452721Z","title":"Dataset Visualization Figure S10 showcases examples from the HPDv3 dataset","venue":null,"work_id":"5f804348-39c4-4e39-8359-69fbe936a1ee","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:09.263797Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:d389eb6178f6e173594119a5d3deb23822670f822cd88600836fea25607abc2f","observation_id":"6d343574-69f5-4e72-890f-1bbb51379929","resolution":{"observed_at":"2026-08-06T04:23:11.541726Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:11.235518Z","title":"We showcase diverse outputs pro- 5 duced across multiple iterations","venue":null,"work_id":"bfaf6e9b-0843-465c-bff8-3a3fde88513d","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:09.426289Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:076ab67473c9392e4e708b9c3a4f6dbff6c406fde8abebebbe646f306ba22bfc","observation_id":"af9fc052-f685-42e0-83d7-2c164b594ced","resolution":{"observed_at":"2026-08-06T04:23:11.329770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:11.052915Z","title":null,"venue":null,"work_id":"17a52f1e-bc4f-4faf-b200-692d273ed2d5","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:09.544155Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:9ed8fc5ed3d32987f3f5d49bea393ad52c1224bee989dd43eb2b1bca333f752b","observation_id":"c6ee876e-5004-4c9b-a326-6ad41d73c675","resolution":{"observed_at":"2026-08-06T04:23:11.127515Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:10.794903Z","title":"The HPDv3 dataset con- tains some parts of images obtained from the Internet, which are not the property of MizzenAI","venue":null,"work_id":"210742f8-6fdc-4f85-904e-3090a016d9c3","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:09.648384Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:c1f95186d4b3e9013827b13e6cb7c54f6b953b7d62f8065379eecc93f621b3fa","observation_id":"8a7082c0-6b49-403c-b230-da41cc062122","resolution":{"observed_at":"2026-08-06T04:23:10.918727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T04:23:10.605519Z","title":null,"venue":null,"work_id":"1f2c4d5c-f9f1-4f49-99da-ac00ac284d11","year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:09.771186Z"},"links":{"citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:5f14bceee3e9a49c53156627c3a6b54790fd642ce7187f4a5e81b9e80791be12","observation_id":"d4b2d249-34b1-42d3-b28a-27c92d941151","resolution":{"observed_at":"2026-08-06T04:23:10.688899Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T20:35:27.515637Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":19,"verified_exact":3,"verified_fuzzy":38},"total_outbound_references":60},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 27 inbound Pith citation observations for arXiv:2508.03789."}