{"as_of":"2026-08-21T22:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d3045bd907a1ee3bbb60b6296bd5adddccd897f128b51d6a2aeb270ff07fbd18","coverage":[{"denominator":82,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":82,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T14:05:06.657362Z","state":"measured"},{"denominator":85,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":85,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:03:42.075088Z","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":"2026-07-02T02:36:26.425440Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.07829","snapshot_observed_at":"2026-08-07T15:03:42.075088Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16425","last_updated":"2025-05-22T09:10:09Z","snapshot_observed_at":"2026-08-17T07:09:21.847569Z","submitted_at":"2025-05-22T09:10:09Z","title":"$I^2G$: Generating Instructional Illustrations via Text-Conditioned Diffusion","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-07T15:03:42.075088Z"},"links":{"cited_paper":"/paper/2502.07829","citing_paper":"/paper/2505.16425"},"observation_digest":"sha256:52ff769351a60856c73d7042a14d9081cbbb9449c48858096ddafc5109a56d80","observation_id":"cc03890c-d637-4de9-869d-5b6a16afdb0f","resolution":{"observed_at":"2026-08-07T15:03:42.075088Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"cited_work":{"arxiv_id":"2502.07829","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.07829","snapshot_observed_at":"2026-07-02T02:36:26.425440Z","title":"Preference alignment on diffusion model: A comprehensive survey for image generation and editing","venue":null,"work_id":"62cc3b20-19d7-4f13-8e8e-8a08a2377108","year":2025},"citing_paper":{"arxiv_id":"2605.08378","last_updated":"2026-05-08T18:36:25Z","snapshot_observed_at":"2026-08-16T09:49:54.305056Z","submitted_at":"2026-05-08T18:36:25Z","title":"Reinforcement Learning for Scalable and Trustworthy Intelligent Systems","version":1},"reference_index":200,"source":"pdf_text","source_observed_at":"2026-05-12T01:47:40.772146Z"},"links":{"cited_paper":"/paper/2502.07829","citing_paper":"/paper/2605.08378"},"observation_digest":"sha256:49ea176463124dcbda6738ca33ff256c1df1c65ff6f9b0112c3efa8226c1eb4a","observation_id":"d32d965d-a825-4a23-a6c8-4c34dffa7f8e","resolution":{"observed_at":"2026-05-12T07:51:40.769034Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"cited_work":{"arxiv_id":"2502.07829","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.07829","snapshot_observed_at":"2026-07-02T02:36:26.425440Z","title":"Preference alignment on diffusion model: A comprehensive survey for image generation and editing","venue":null,"work_id":"62cc3b20-19d7-4f13-8e8e-8a08a2377108","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":69,"source":"pdf_text","source_observed_at":"2026-06-28T10:51:40.605583Z"},"links":{"cited_paper":"/paper/2502.07829","citing_paper":"/paper/2606.03216"},"observation_digest":"sha256:7bf08cff4061bf5c24718cc64570ed3f6134fa78b25fc299ede21aba8ac08e25","observation_id":"7a140f76-1943-4d00-a2e4-8c9ad992feda","resolution":{"observed_at":"2026-07-02T02:36:26.427693Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.07829/citation-record","integrity":"/paper/2502.07829/integrity","json":"/paper/2502.07829/citation-record.json","paper":"/paper/2502.07829"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T14:05:06.276503Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.276503Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:a83ec83354aeab903aa22a0f9eb615df0a69afbbadb6cfbd50e5cd771e41f87b","observation_id":"c5c54f6e-0e05-47f8-8407-6d3793cdc273","resolution":{"observed_at":"2026-08-08T14:05:06.276503Z","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":"2026-08-08T14:05:06.281945Z","title":"Gflownet foundations","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.281945Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:13dbb5729168298c0d045db8365af2143fb972c947032d76bcf98536c8567008","observation_id":"d564eb03-d878-4e15-9c25-0428f62dccd7","resolution":{"observed_at":"2026-08-08T14:05:06.281945Z","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":"2026-08-08T14:05:07.874185Z","title":"Training diffusion models with reinforcement learning","venue":null,"work_id":"2fef11c2-85e6-441d-a752-645f46016201","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.286807Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:2148d3934d5b36f603c0ccbcf10f9553fe2b4216fce408755a9555b45151304c","observation_id":"7e7a129d-edf6-4e24-9d46-bb773e259aaa","resolution":{"observed_at":"2026-08-08T14:05:07.878879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.859780Z","title":"Sheng, and et al","venue":null,"work_id":"93cdb66d-1f48-46b7-b670-ffbfc4869ab6","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.291452Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:5bcd96244e02f5b19749a0231c4eaaecf0361a44c5dc0b999d4979bd26638664","observation_id":"90b62637-ea82-47c9-815d-23b150e62aa0","resolution":{"observed_at":"2026-08-08T14:05:07.864454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.845229Z","title":"Drivinggpt: Unifying driving world modeling and planning with multi-modal autoregressive transformers","venue":null,"work_id":"888da1ea-1db8-4f34-939f-828642af173e","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.299466Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:bf6ed7d1e48b6bf4ba5061b201ce1db019d53357ef63bc2d09471f7add8ef9cc","observation_id":"731478f7-67d2-41d2-b281-53dcbb577fc2","resolution":{"observed_at":"2026-08-08T14:05:07.849918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.830745Z","title":"Deep reinforcement learning from human preferences","venue":null,"work_id":"194e8813-a212-49f7-9358-c439cc159b07","year":2017},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.304646Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:8167b4204274205a14da0532cad2ba4d20de9764dcc6ff9fb25e514a0dd10a17","observation_id":"2529b83f-c0f0-4a6e-a0a5-151859c426a6","resolution":{"observed_at":"2026-08-08T14:05:07.835458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.816603Z","title":"Directly fine-tuning diffusion models on differentiable rewards","venue":null,"work_id":"f24d70a7-0bed-458f-9fce-420c67c5b6c5","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.309854Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:973b476ce6ae8df494cedea8dd8fb9a54af28f6490881bee995100c25a0de824","observation_id":"225259be-b0e0-499a-a46e-55a5ae6934cd","resolution":{"observed_at":"2026-08-08T14:05:07.821179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.802172Z","title":"On differentially private 3d medical image synthesis with controllable latent diffusion models","venue":null,"work_id":"e1e43be1-4f39-4e3f-9f8e-38f0b25dc7cb","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.314253Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:5e31077ada31cc50858d2341771aa75354405d4d6bc6ce951fb673adda618dfc","observation_id":"32eeb8d6-3c39-4ffe-be8f-0b2a4ce909d0","resolution":{"observed_at":"2026-08-08T14:05:07.806890Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.787295Z","title":"Prdp: Proximal reward difference prediction for large-scale reward finetuning of diffusion models","venue":null,"work_id":"ae960ae9-9e30-46ac-a010-ad49f645f0d9","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.318938Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:18a89b58ade384186f6009ec532703adbed10efc6d6d595f3cf5a273c6b6312b","observation_id":"195e6d64-8b2c-4947-b8ca-e50149466377","resolution":{"observed_at":"2026-08-08T14:05:07.792113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.772573Z","title":"Aligndiff: Aligning diverse human preferences via behavior-customisable diffusion model","venue":null,"work_id":"fccf94af-d4ea-46a5-973b-66c9e3011dec","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.323467Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:d8697c791befada0b67d0d38a1e9e0fc3c485bb03df6eaea8ec0d51e3aeb04c4","observation_id":"25225b8b-277f-476d-8518-e42bae575ee1","resolution":{"observed_at":"2026-08-08T14:05:07.777547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.757755Z","title":"Beyond deep reinforcement learning: A tutorial on generative diffusion models in network optimization","venue":null,"work_id":"a011c4bd-4e63-435e-8ca4-ce2d7097ce71","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.328049Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:6bc66b8d8512b2e08280ff23905c46aaf563da197c639135ab94317926b9ccad","observation_id":"71382614-84db-411b-9336-27b477a28410","resolution":{"observed_at":"2026-08-08T14:05:07.762694Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.743090Z","title":"Reinforcement learning for fine-tuning text-to-image diffusion models","venue":null,"work_id":"525dfa91-0184-4808-a145-30099d7cb31e","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.332577Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:7e328ca36b0e41d1e01b0f2dc21d06a6b30d5283f6e886f41ea23d5ca85fd067","observation_id":"412711ec-f980-4860-984b-d6d04957e40b","resolution":{"observed_at":"2026-08-08T14:05:07.747862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.728472Z","title":"A survey of world models for autonomous driving","venue":null,"work_id":"b6163585-bbe9-4eeb-9442-f24827fd56a2","year":2025},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.337295Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:f5646c74ca9baad6b5a2116c212d07bef5541e611b683bd265d7c4aabe86842f","observation_id":"f0615a3f-456f-453b-aafe-3ebcaedb9b52","resolution":{"observed_at":"2026-08-08T14:05:07.733287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.712815Z","title":"Can pre-trained text-to-image models generate visual goals for reinforcement learning? Neurips , 2023","venue":null,"work_id":"5fac7f09-f372-4d6e-940b-6ec7962fab86","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.341812Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:da8035046f486937c662af43afce3cf98222a386c752dc81bb3c80c5c4ffecd9","observation_id":"56cb77a5-37b5-48b9-bad6-e51fd7bc8bc7","resolution":{"observed_at":"2026-08-08T14:05:07.718224Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.698598Z","title":"World models for autonomous driving: An initial survey","venue":null,"work_id":"81f51fd5-bb9c-4848-89ec-0f9b24c7b9d3","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.346182Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:8cebadf74aae031bba925fd459573b1e08c4886883ec420084f09e4d5925552b","observation_id":"fbdc95bb-7f10-48cf-909f-bbc67905fe6c","resolution":{"observed_at":"2026-08-08T14:05:07.703315Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.683552Z","title":"Versat2i: Improving text-to-image models with versatile reward","venue":null,"work_id":"e2ddfd9c-c568-494a-ab04-39b22b40d1e0","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.350652Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:3761fdfb9e92d5ad5b168de9d6e2210698909ad14ba556125b4d46c5464cc0e3","observation_id":"1da53522-caf8-4069-848b-6c6bbe936f00","resolution":{"observed_at":"2026-08-08T14:05:07.688386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.668637Z","title":"Advancing text-driven chest x-ray generation with policy-based reinforcement learning","venue":null,"work_id":"21a44e95-f51e-452a-a5b5-6ec92e04b510","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.354895Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:3dd1a7eaf006d84b35b3abc6e5b8a907f637f06523870f83eb0b342c9afcf536","observation_id":"98336724-377c-43a2-9c18-0b01ed08d5e1","resolution":{"observed_at":"2026-08-08T14:05:07.673528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.653895Z","title":"Learning profitable nft image diffusions via multiple visual-policy guided reinforcement learning","venue":null,"work_id":"fb3ade37-3cce-4db8-872e-e07a4734c094","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.359014Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:64c051d3cc0ca078e7caab40a0081a0fd4ca12bf461c26d231a82220d393cab4","observation_id":"b7ab1461-b963-478c-acd0-7ce382bda1fb","resolution":{"observed_at":"2026-08-08T14:05:07.658531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.639560Z","title":"Denoising diffusion probabilistic models","venue":null,"work_id":"077bf5de-1ee0-4fb1-bdb4-bb4b4f7cd27e","year":2020},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.363351Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:b4ee1722a0f94508fe4abdd589c383be40fafda0133951919031b3be21297be6","observation_id":"a67ea632-d9c5-4718-a21b-c49cb3c214c7","resolution":{"observed_at":"2026-08-08T14:05:07.644103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.624457Z","title":"Diffusion model-based image editing: A survey","venue":null,"work_id":"703a774f-9a85-446c-b0e6-5a28284949de","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.367711Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:d6aa886956ca2eeca6236f16c6a70cb32136c26b4f42ccef4855e33d6477cf4f","observation_id":"cf8a7940-8130-4ec9-9361-968c859c8e71","resolution":{"observed_at":"2026-08-08T14:05:07.629291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.609369Z","title":"Gen-drive: Enhancing diffusion generative driving policies with reward modeling and reinforcement learning fine-tuning","venue":null,"work_id":"98192bfc-f493-456b-8ba7-f7437efac535","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.372250Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:e1606f382e7a9ea2eb635d0f61e40496c41764e2eb383ea914f103dddd414de1","observation_id":"10406fde-2ed9-4d29-8246-7d5228c82576","resolution":{"observed_at":"2026-08-08T14:05:07.614351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.594316Z","title":"Planning with diffusion for flexible behavior synthesis","venue":null,"work_id":"10685564-e31f-434c-945c-355c021a946c","year":2022},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.376688Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:b1febd35851ccc031ac19c95dda0e788d7e97f8db213af6980fed32d38850df3","observation_id":"607925df-17e0-4047-acd0-848322b17156","resolution":{"observed_at":"2026-08-08T14:05:07.599315Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.579283Z","title":"A theory of continuous generative flow networks","venue":null,"work_id":"0ed9519f-9d08-419a-a52c-fb0bb673fc18","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.381211Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:fc0e1c2f921a6ce1ca0fd6dedb27f534859cec1877ad8805e8bf4cd8e1bc2ad9","observation_id":"ec0a6843-f183-4b8a-b08e-cbc6f1bd0159","resolution":{"observed_at":"2026-08-08T14:05:07.584263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.564153Z","title":"Aligning text-to-image models using human feedback","venue":null,"work_id":"94847a7b-d841-46ad-ae80-ab8c3a1160d5","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.385588Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:75cdfe95ceff8feb7b2a5bb377b2a81b76ecda13321c50e9783d28964ebee950","observation_id":"25573ed4-0d71-44f9-b76c-c70554614a30","resolution":{"observed_at":"2026-08-08T14:05:07.569173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.549164Z","title":"Parrot: Pareto-optimal multi-reward reinforcement learning framework for text-to-image generation","venue":null,"work_id":"59d2c89c-7b55-493e-860e-04595cceb9f8","year":2025},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.389774Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:beb97916e06f486bd53170fdc08ca93b9264f760db0e6f81cc70cbbd5d39184b","observation_id":"a2005368-d309-4142-be30-0af07c86f998","resolution":{"observed_at":"2026-08-08T14:05:07.553865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.534535Z","title":"Drivingdiffusion: Layout-guided multi-view driving scene video generation with latent diffusion model","venue":null,"work_id":"2b0737ff-d985-418e-89e8-6d343f792f2e","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.394111Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:0418ce6f19f8c57ce798eb3c42b27bd64f83b3fc65d85b915d79c0040703fdd4","observation_id":"12c7cdb7-d7c0-4b66-9811-b8d70a969523","resolution":{"observed_at":"2026-08-08T14:05:07.539304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.519775Z","title":"Aligning diffusion models by optimizing human utility","venue":null,"work_id":"3351156b-d8e5-444f-9f92-704b56195cdc","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.398499Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:82d5670186caf97ca18a8725be56a1279efb0ae097ea9ea1dc16c88fe527c151","observation_id":"3b5f23a7-bc8f-4829-876c-344d64f39b6f","resolution":{"observed_at":"2026-08-08T14:05:07.524733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.504257Z","title":"Instructrl4pix: Training diffusion for image editing by reinforcement learning","venue":null,"work_id":"ddce3614-fb41-4571-a24d-3fe01e8f0931","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.402864Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:206b45800c738cc62833d1742240fecd334d112b297ace53d7850eb3bb7ce552","observation_id":"9ceeafb8-4c4e-4c5d-b2b0-f9d1c2095451","resolution":{"observed_at":"2026-08-08T14:05:07.509104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.489994Z","title":"Textcraftor: Your text encoder can be image quality controller","venue":null,"work_id":"721d9c62-5caa-4f1b-b03e-5d65593d4aec","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.407369Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:bbcef2b6312799e0e9256d2fe9f17cd551b8514b91d4aa8159ac8744542a5202","observation_id":"83d31a28-9921-4ea1-b416-41a75b74748a","resolution":{"observed_at":"2026-08-08T14:05:07.494645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.475067Z","title":"Rich human feedback for text-to-image generation","venue":null,"work_id":"4ea67253-3463-4775-b03e-25c3a31850bb","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.411884Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:6e463b8eeeb5d5e445eba50efd3335db18a7d2f3eb5eaef8274ef2d5dc10b607","observation_id":"d35a84c4-001a-419d-b40d-c8d3a8bcf5b7","resolution":{"observed_at":"2026-08-08T14:05:07.480170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.460219Z","title":"Diffusiondrive: Truncated diffusion model for end-to-end autonomous driving","venue":null,"work_id":"9d82698d-132c-4c30-b410-1ab7d04b8b85","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.416250Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:c7607c66bb01d10c35a0593c84568702effe729d9ff4c02b0da120b7aea571e8","observation_id":"6bd7d5b8-ae0c-4df6-887b-3b49ca122cdb","resolution":{"observed_at":"2026-08-08T14:05:07.465120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.443944Z","title":"Magic3d: High-resolution text-to-3d content creation","venue":null,"work_id":"ee171f99-518b-4018-9b2f-d376d56d5b2e","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.420770Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:25221123ef57047051174d5aa2573adfc2d3937b9d51d1fb6b81620aa58f3826","observation_id":"274e4549-8fda-4b9a-8298-1d124c69d160","resolution":{"observed_at":"2026-08-08T14:05:07.448767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.429534Z","title":"Ddm-lag: A diffusion-based decision-making model for autonomous vehicles with lagrangian safety enhancement","venue":null,"work_id":"e9d61c12-6a30-4065-86a3-8dbfaa4a39e4","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.425103Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:eb3446e58bdfe459ce86d30d5aaf1787da70a8c2b141fe38f1747f293b444b95","observation_id":"9c06f95c-f6c8-46db-b488-f4e86251a36a","resolution":{"observed_at":"2026-08-08T14:05:07.434130Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.415308Z","title":"Rdt-1b: a diffusion foundation model for bimanual manipulation","venue":null,"work_id":"a95d21d2-1547-41ac-9df4-76ef79974931","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.429734Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:26d9d0be13d27f1ca3ac5b4ade98cec81ae8b0a2e8219dd27d602ed5bb7a4449","observation_id":"986c406a-7e16-460a-acd8-fd2ab48b3532","resolution":{"observed_at":"2026-08-08T14:05:07.420014Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.401160Z","title":"Improving text-to-image consistency via automatic prompt optimization","venue":null,"work_id":"1ac891db-ae6e-4bf1-b626-0edc354296bc","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.434394Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:9145f50ce43dd6a70066e1c404a499a023253e1117c47dd22b13c741500e944f","observation_id":"c0335251-ed7b-4795-a97f-2b060aae0b39","resolution":{"observed_at":"2026-08-08T14:05:07.405825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.386957Z","title":"Promptable game models: Text-guided game simulation via masked diffusion models","venue":null,"work_id":"5195c6be-7996-40a1-9eed-66039db0efb4","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.439348Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:921fa732274e0dd6b1c34042310e0401406a523795dbab912e1bc74cbc0d77ed","observation_id":"57027566-1ac0-4762-863d-801295ccb17e","resolution":{"observed_at":"2026-08-08T14:05:07.391520Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.372899Z","title":"Training diffusion models towards diverse image generation with rl","venue":null,"work_id":"fd794ed3-db07-4fef-8675-24453313dfcd","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.444215Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:0ce1c4bd9839e92ef7abf0e6ba210271706ac31f879b686c715ed6a153974fa8","observation_id":"de3069e5-a68a-4498-b16c-cd9992c2e0ab","resolution":{"observed_at":"2026-08-08T14:05:07.377581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.358535Z","title":"Dynamic prompt optimizing for text-to-image generation","venue":null,"work_id":"3b195120-8b6e-4ec1-a327-b7f77094cbea","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.448925Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:62b8f0caf13ecc147729803483b4e7988a1179e5f7aa61aa5ad1987f2a38945d","observation_id":"6595ed8e-4351-415f-81ca-22f8a3988b36","resolution":{"observed_at":"2026-08-08T14:05:07.363448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.344011Z","title":"Rl for consistency models: Reward guided text-to-image generation with fast inference","venue":null,"work_id":"15bab3b1-8c8b-4b34-9cc4-1979d5e7aae5","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.453575Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:80bda3d625400ff9f71662c928af4a9ec8e34cdbafb0390d1ff54921ff5a98b5","observation_id":"96e72e9c-24f5-4061-857b-959a15f0beef","resolution":{"observed_at":"2026-08-08T14:05:07.348732Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.329018Z","title":"Optimizing negative prompts for enhanced aesthetics and fidelity in text-to-image generation","venue":null,"work_id":"2b646d34-c5d8-490c-b1ed-452529033684","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.458000Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:bc4b7e708e927d9925ad9bc33816997e4edfe553247c60e44710f328b223c355","observation_id":"7ab8fd94-240a-4fa1-968f-a76363aed9d4","resolution":{"observed_at":"2026-08-08T14:05:07.334144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.313253Z","title":"Aligning text-to-image diffusion models with reward backpropagation, 2024","venue":null,"work_id":"a4cbe5c1-b3d2-4e1d-aaa6-4eefa5740f7e","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.463003Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:ec4ee545336c63a1a4e419eaddc16375baa0fea56faa72efa6b5056c30d54964","observation_id":"d82d8202-c731-4175-a8b4-d41b983d9eee","resolution":{"observed_at":"2026-08-08T14:05:07.318128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.298021Z","title":"Utilizing generative ai for vr exploration testing: A case study","venue":null,"work_id":"837c85d6-5442-4aa2-aba8-708165f1e427","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.467537Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:ce1cb3e1f06fae0b0741aa6e066b1fd257d15ef99be51b3d63ebc7705b484d53","observation_id":"117ce508-c861-45d1-a418-47283687fbc1","resolution":{"observed_at":"2026-08-08T14:05:07.302952Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.282837Z","title":"Direct preference optimization: Your language model is secretly a reward model","venue":null,"work_id":"1861075b-fc9f-420c-8045-27bfa4492eb6","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.472315Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:abeb160ca88cbd8e977854a538c86a3521f67d007c3002ba6d9933dd74d8db70","observation_id":"de7c7f8a-71d9-48ec-9231-0fe558a7fa33","resolution":{"observed_at":"2026-08-08T14:05:07.287856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.267987Z","title":"Ambiguous medical image segmentation using diffusion models","venue":null,"work_id":"e79f3c5c-7b64-40eb-aa64-0d7cd2c3f65a","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.477026Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:249bf96be1a060aec9c734cc8298c01eb47396c644084e4904a5cfbd4398fdf3","observation_id":"db1a98a6-5792-43e4-bc15-5d222df8fe67","resolution":{"observed_at":"2026-08-08T14:05:07.272811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.251561Z","title":"Hierarchical text-conditional image generation with clip latents","venue":null,"work_id":"07549844-64b2-454d-a54d-abc2070296a7","year":2022},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.481893Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:7591668ed9ef7deb015990b764278aa32abdda779cf1f0255cb04a6e26d531af","observation_id":"51f1d252-e11d-4b59-9db5-b8b167f1b02f","resolution":{"observed_at":"2026-08-08T14:05:07.256559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.237713Z","title":"Refining alignment framework for diffusion models with intermediate-step preference ranking","venue":null,"work_id":"8165e087-c86f-47cb-87c8-f15ed2ed912a","year":2025},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.486413Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:31a208845c52072f0dceb055f158d3b5bfc84ae4b31c086bcf75c9d160006cab","observation_id":"91a5b6ca-f6ed-4393-88d2-d8ff3ba4745e","resolution":{"observed_at":"2026-08-08T14:05:07.242212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.224244Z","title":"Photorealistic text-to-image diffusion models with deep language understanding","venue":null,"work_id":"4557f132-1772-49bb-a746-269e00cb695e","year":2022},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.491007Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:141c29ba6d7e30aadc1b93e2fb5116ead435f775dbddcabf9f74ba33f24844b4","observation_id":"3b6cea2a-31eb-4417-b851-9df2eb1b4a4f","resolution":{"observed_at":"2026-08-08T14:05:07.228632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.210208Z","title":"High-dimensional continuous control using generalized advantage estimation","venue":null,"work_id":"de6ac3a4-3635-4e23-94d0-102a0e4b828f","year":2015},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.496007Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:b4fa899f0259cb46d0282ca7ff5656aee4ca1af173976a3055eb0cea6f71773a","observation_id":"40b56b29-b639-41a7-8acc-5286a8998c54","resolution":{"observed_at":"2026-08-08T14:05:07.214949Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.194870Z","title":"Proximal policy optimization algorithms","venue":null,"work_id":"6f1dc599-5cd2-4340-91a0-e279066cfb38","year":2017},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.500692Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:0a2a353aced80f5688906ab92144b9ebe05e8a89ce6c812532a71910b6331798","observation_id":"16816cfe-31f9-4939-a33a-1f674f2da3ad","resolution":{"observed_at":"2026-08-08T14:05:07.199729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.180162Z","title":"Denoising diffusion implicit models","venue":null,"work_id":"1eda09a8-148b-4b96-844e-94790ac42741","year":2020},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.505354Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:c100c4c9f461ebb12e68194160003a54f9707f65806f4274f54d21f169e64c07","observation_id":"3edee188-31dc-461b-bf30-7defda6a77c2","resolution":{"observed_at":"2026-08-08T14:05:07.184624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.165174Z","title":"Fine-tuning of continuous-time diffusion models as entropy-regularized control","venue":null,"work_id":"d28d9986-4003-4811-aeb1-b414526b22b0","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.509790Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:1747fa47522f2d56899494e7da008267e87c0c0b9576ebabcb2a6d5cd31acf64","observation_id":"5e182c9c-54cd-40ce-bcfd-ac1c8ca7fd64","resolution":{"observed_at":"2026-08-08T14:05:07.169987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.150677Z","title":"Understanding reinforcement learning-based fine-tuning of diffusion models: A tutorial and review","venue":null,"work_id":"48ce2ddb-9ecc-483e-8a93-802155c241a5","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.514560Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:2c40eaf197b3fb577656e76a7d895496bda2db433f902ccb141ae41215ca30e2","observation_id":"e6529dad-4fb7-4820-a199-c1630be7dfee","resolution":{"observed_at":"2026-08-08T14:05:07.155246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.136294Z","title":"Diffusion model alignment using direct preference optimization","venue":null,"work_id":"4a31c936-2a94-43cb-a34c-d562d9712eab","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.519184Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:275234bdcf9ec2e7b6bfb52471ba0bdc930c0e07195447788d39d81040a7e171","observation_id":"b415bf7e-406d-49ce-ac3f-f1160be40b0d","resolution":{"observed_at":"2026-08-08T14:05:07.140414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.121360Z","title":"Diffusebot: Breeding soft robots with physics-augmented generative diffusion models","venue":null,"work_id":"04b4be91-4b35-42ca-a00f-9773a64dff71","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.523473Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:fe645f55daa41e9d15d082e145603de6b9525169cd7c9268c822f431d2c74e14","observation_id":"9cf2fc5a-09a9-4236-b58f-19ec4d0670cd","resolution":{"observed_at":"2026-08-08T14:05:07.126557Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.106092Z","title":"Diffchat: Learning to chat with text-to-image synthesis models for interactive image creation","venue":null,"work_id":"4c31701a-d37e-494d-91d0-0c43fcb2205f","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.527919Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:30baa2d8b3ae32a085a7a187f3fa80a5c6bbc4dde82f084e834e106d190bca68","observation_id":"bd0bcd09-12b1-4433-92ce-96c12c0a05ec","resolution":{"observed_at":"2026-08-08T14:05:07.111166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.092230Z","title":"Sparse diffusion policy: A sparse, reusable, and flexible policy for robot learning","venue":null,"work_id":"3e8390e8-72cc-427e-b4b6-7fe49108b767","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.532437Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:ac52943b56d4c655ad9432486cd8b5a6787d55a11990bd47b4d4dc31c8b5631f","observation_id":"e5580e84-5161-40a8-a9bc-3f51c53c68b1","resolution":{"observed_at":"2026-08-08T14:05:07.096695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.078008Z","title":"Panacea: Panoramic and controllable video generation for autonomous driving","venue":null,"work_id":"cb0341f9-a1d0-431d-b1f6-cd0ccb52a71d","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.537849Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:65966f1a4955354733649a518b2cf8268c89193ac5f469bed88c0bcdcbc99c94","observation_id":"6199c7f0-fe1f-448b-8419-18cdc7ba3f16","resolution":{"observed_at":"2026-08-08T14:05:07.082872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.062853Z","title":"Improving compositional text-to-image generation with large vision-language models","venue":null,"work_id":"4f9975f6-eeaf-499b-ae2d-48042bea06e2","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.543056Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:b2ac689bbbb3b2e1e81e3cbf613a6deb511834a55680d098cde6a0de38c1bcd5","observation_id":"5232448c-7452-4412-a432-86751ec01636","resolution":{"observed_at":"2026-08-08T14:05:07.068124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.048004Z","title":"Preference tuning with human feedback on language, speech, and vision tasks: A survey","venue":null,"work_id":"76f71cd5-9b6b-46aa-baa5-7067ca16e4a7","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.548925Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:a631e148cbb6476e692ab3a0c254b1b9ae47851d5302d436f2b52c3307bec648","observation_id":"9520edbb-f173-4958-9ed0-3f63fcaeae8e","resolution":{"observed_at":"2026-08-08T14:05:07.052891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.034117Z","title":"Medsegdiff: Medical image segmentation with diffusion probabilistic model","venue":null,"work_id":"d972a62b-eb48-41a2-9f8a-e89d90f280d2","year":2022},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.555277Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:205c5ddabc4428956b4e51b4cae474ca1444e55cf1d1135f9b729f716b01ecc5","observation_id":"34acfd8f-b2a3-48cc-87fb-1c71ae8273fd","resolution":{"observed_at":"2026-08-08T14:05:07.038374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.019325Z","title":"Medsegdiff-v2: Diffusion-based medical image segmentation with transformer","venue":null,"work_id":"cfd4ac39-6f26-4234-bd7f-c022842e0960","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.561535Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:b150e0bf24ee7eb3e93e7dce7c6757f89e6be0c7649acfb4044ef8a45ab5330e","observation_id":"940495cc-dc82-46da-abe6-c97522450897","resolution":{"observed_at":"2026-08-08T14:05:07.024212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:07.004821Z","title":"Human preference score: Better aligning text-to-image models with human preference","venue":null,"work_id":"9c9bc612-c9b6-4458-8326-4f2073c91c2a","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.567162Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:f4904a7e0f5fd51e609c0c5df124d041403aefdf46f7f80e6122da6fc218d1e1","observation_id":"fc878867-9ca8-4a23-a8cc-ccc669d9b00b","resolution":{"observed_at":"2026-08-08T14:05:07.009606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.990359Z","title":"Protein structure generation via folding diffusion","venue":null,"work_id":"d4f82059-1443-4691-b0b6-40895fd40672","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.572780Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:c29189c8fb008bd37a19dcdd28a9d85312c3c5da1c9e2955866048a8e6586e8b","observation_id":"7691c93f-2753-4f77-869d-32051b1ca29a","resolution":{"observed_at":"2026-08-08T14:05:06.995194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.973030Z","title":"Deep reward supervisions for tuning text-to-image diffusion models","venue":null,"work_id":"5607407f-3826-4244-bd1a-6e3da40e35af","year":2025},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.577030Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:d0a151ef555fd85b920dd6044b3756a91b00430e85ba7cafea33f8ade6f25432","observation_id":"eb65684b-11cc-480f-a603-764865cf280c","resolution":{"observed_at":"2026-08-08T14:05:06.979815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.958368Z","title":"Measurement-conditioned denoising diffusion probabilistic model for under-sampled medical image reconstruction","venue":null,"work_id":"6674e44c-4ad3-4301-8e95-d0d960545f08","year":2022},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.581466Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:ee23827885241fb952f2374452e5e04a358e748fd2d718612a27bd8452c6dcac","observation_id":"d9c3686c-3b8f-4e12-901d-32f474e180a6","resolution":{"observed_at":"2026-08-08T14:05:06.963036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.943559Z","title":"Imagereward: Learning and evaluating human preferences for text-to-image generation","venue":null,"work_id":"5ef21782-dd6e-477b-92a2-15054b6dde9a","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.586016Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:fa633f6cf49b0895d9754b628aa74590ebb87974fdc5544be5595b61d6f7c756","observation_id":"c5138aca-59ab-42ef-89e2-30bda9825a30","resolution":{"observed_at":"2026-08-08T14:05:06.948325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.928719Z","title":"Using human feedback to fine-tune diffusion models without any reward model","venue":null,"work_id":"5fd10719-fa59-40d1-b058-6a4aa9a06c3b","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.590182Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:79b62ff73f71af7f1b71637d1f3c653354033bb3b004071c0b294581178fdb44","observation_id":"c5ae2176-05b5-4461-933a-835a5e672222","resolution":{"observed_at":"2026-08-08T14:05:06.933547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.912893Z","title":"Learning interactive real-world simulators","venue":null,"work_id":"6cd01ff0-8f63-45c0-b248-6154cf089cd5","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.594751Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:5507407620e023d5aad46d5a67f7090e23c07ba81d9a7979570be3743a8eb44d","observation_id":"151c17e2-4a1b-46d1-b7d1-550b89fb8d78","resolution":{"observed_at":"2026-08-08T14:05:06.918177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.897469Z","title":"Mastering text-to-image diffusion: Recaptioning, planning, and generating with multimodal llms","venue":null,"work_id":"d6b34094-9ea1-4323-88b7-c167ef289695","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.599345Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:1d88e8cbbe6be72fedfc45e052c23801446e2e3639321a887057a43d17bbf376","observation_id":"41587aa3-1aa2-42ab-b725-d3c2b5d0d303","resolution":{"observed_at":"2026-08-08T14:05:06.902652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.881866Z","title":"A dense reward view on aligning text-to-image diffusion with preference","venue":null,"work_id":"e419a096-5471-46b8-a8fe-1ef79f65e5a2","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.603602Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:832f446f2ea50fc742c23646eb6a6c8c46cdd5382999b398400a910f05512f86","observation_id":"eee61959-f5cd-4657-b3d8-33cb9d8b369a","resolution":{"observed_at":"2026-08-08T14:05:06.887092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.866456Z","title":"Ipo: Iterative preference optimization for text-to-video generation","venue":null,"work_id":"006d34e6-8b79-4e37-bf5f-2666b8b866a0","year":2025},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.608049Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:e2a1804b396a7610f5b5e03f59e8398df200e74ea692d9886a98c7b3e27fd099","observation_id":"0d57f3fc-6076-46d3-9965-4fec847ead25","resolution":{"observed_at":"2026-08-08T14:05:06.871536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.850412Z","title":"Regularized conditional diffusion model for multi-task preference alignment","venue":null,"work_id":"8af73fe9-74fd-40e4-ab1b-171adb6099db","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.612424Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:473a1e7aea7f38f43397724e7ef5dd74253c364a9ce6c6861d72cea3bd61f095","observation_id":"61a5a42d-dd38-455f-a231-b5636f18f994","resolution":{"observed_at":"2026-08-08T14:05:06.855650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.834411Z","title":"Self-play fine-tuning of diffusion models for text-to-image generation","venue":null,"work_id":"7cf5ad4d-8263-4157-b414-899b8567ff6d","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.616838Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:eec29be620c22169c25cc34e48391c3842c17451968ca96a83f2739d65f040d8","observation_id":"c4197ad8-451c-43b2-8408-4b03548cdd12","resolution":{"observed_at":"2026-08-08T14:05:06.840011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.819280Z","title":"Preference aligned diffusion planner for quadrupedal locomotion control","venue":null,"work_id":"c95eb644-72fc-4baa-b648-d7832dc7c105","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.621050Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:847f28b80b75c4282a3bb29812d525f41c410ffe00b5a8ff604263896e8194a3","observation_id":"dbf01e66-3102-415f-aea7-9c03ba39aa82","resolution":{"observed_at":"2026-08-08T14:05:06.824034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.803806Z","title":"Unifying generative models with gflownets and beyond","venue":null,"work_id":"9c5e8471-4c8e-4530-84a5-f6eef1e469fd","year":2022},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.625598Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:eec35f929bac6c3e3fc43f80a55f3dfed1edae8c189d78fcb469736a3b89a2cb","observation_id":"000eb5c4-1494-480b-ae46-d1383258ba6d","resolution":{"observed_at":"2026-08-08T14:05:06.808530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.787063Z","title":"Text-to-image diffusion models in generative AI: A survey","venue":null,"work_id":"431d9420-4543-43f3-84b0-b5c324ec33d3","year":2023},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.629939Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:c91e816e1faf36b5245fb38e4ed7496c903227248e6f9bd27360159e620854a0","observation_id":"626dacd5-39b2-4a0c-ad80-2bb987c67cf7","resolution":{"observed_at":"2026-08-08T14:05:06.792302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.771140Z","title":"Improving gflownets for text-to-image diffusion alignment","venue":null,"work_id":"cfde4136-a241-4be0-a912-bee13375f886","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.634210Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:99b09eb16592dbd79ff600f7b767a395c3ae007ea7a0b05cbee41b9733604455","observation_id":"1e2dcfe9-c15b-42e3-a969-6d4f746fa4cd","resolution":{"observed_at":"2026-08-08T14:05:06.775873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.754746Z","title":"Onlinevpo: Align video diffusion model with online video-centric preference optimization","venue":null,"work_id":"47f5d1c1-6be1-4642-997a-06b3f732d5e1","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.638912Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:75424eea1a45668ade4745f4c1e314edc461a75b5c76d45e9833102b5ee7cb64","observation_id":"0343b017-e8fc-4756-90c5-70de898316e8","resolution":{"observed_at":"2026-08-08T14:05:06.760272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.739005Z","title":"Hive: Harnessing human feedback for instructional visual editing","venue":null,"work_id":"adde18da-8ae2-4163-a735-935d39bdaef0","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.643720Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:d0de38b8932215cc9862c2242ed1e7c31eeb5ca70ae97272b3a95ffa3207b0d1","observation_id":"1f8f53ff-fdc9-464c-bff0-0139b79db40f","resolution":{"observed_at":"2026-08-08T14:05:06.744288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.723572Z","title":"Large-scale reinforcement learning for diffusion models","venue":null,"work_id":"597ac7b9-b479-4f68-aaaa-d4d49aa3958e","year":2025},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.648309Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:4df1c6367e5cd4737d1e0ca8a1515ba509e7dee21687edd6dc51fef0d22acf41","observation_id":"f1c9f7d6-6fa0-4651-8ca6-c45277c13f75","resolution":{"observed_at":"2026-08-08T14:05:06.728645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.703429Z","title":"A survey on generative ai and llm for video generation, understanding, and streaming","venue":null,"work_id":"c33589a7-02d3-4729-9e78-6c07dfedc90e","year":2024},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.653131Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:81909b5225310902670a0c6ab5dc3b46d508b2c73bb78202a4d4dd22155cd758","observation_id":"985b9447-961c-4ea0-ba01-babd0043ad94","resolution":{"observed_at":"2026-08-08T14:05:06.710976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-08T14:05:06.657362Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-08T14:05:06.657362Z"},"links":{"citing_paper":"/paper/2502.07829"},"observation_digest":"sha256:951f202b7827bcd827a00e3c0c01309a9dabf1a76641c8718ca69b8699853b73","observation_id":"3c4e6c9f-5e24-4b23-9d82-ec162090f77e","resolution":{"observed_at":"2026-08-08T14:05:06.657362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.07829","last_updated":"2025-02-10T20:25:11Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T13:30:34.328366Z","submitted_at":"2025-02-10T20:25:11Z","title":"Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing"},"reference_resolution":{"displayed":82,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":79},"total_outbound_references":82},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 82 of 82 outbound references and 3 inbound Pith citation observations for arXiv:2502.07829."}