{"as_of":"2026-08-14T23:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ff10ed525a69ff38f21d244b952c51e6967f8687b5a6a4aef811afa7aa4a7850","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":52,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":52,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":52,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":52,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T17:51:01.432420Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":81,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2210.08933","last_updated":"2023-02-14T06:45:49Z","snapshot_observed_at":"2026-07-06T14:06:34.310083Z","submitted_at":"2022-10-17T10:49:08Z","title":"DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-20T06:50:38.258692Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2210.08933"},"observation_digest":"sha256:d5aa642f8a7d6b6790c3ea8579bcf2e8b3ca10e6dc570a9d632c930e1f9f1c16","observation_id":"4d9efefd-c65a-4b78-936b-063e063e018d","resolution":{"observed_at":"2026-05-20T06:50:38.286324Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2211.15089","last_updated":"2022-12-15T14:27:19Z","snapshot_observed_at":"2026-08-07T07:03:02.158312Z","submitted_at":"2022-11-28T06:08:54Z","title":"Continuous diffusion for categorical data","version":3},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-05-18T03:30:22.025578Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2211.15089"},"observation_digest":"sha256:a991b28dbf14750b15a74ef0f06ab7a41e093d5946c0d59be68820c12f84fb2a","observation_id":"275bf520-d88b-4b78-97d2-be77dc0e2150","resolution":{"observed_at":"2026-05-18T03:30:22.141666Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2309.16797","last_updated":"2023-09-28T19:01:07Z","snapshot_observed_at":"2026-08-14T11:37:32.461743Z","submitted_at":"2023-09-28T19:01:07Z","title":"Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-05-16T08:12:30.984870Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2309.16797"},"observation_digest":"sha256:5a99e7fc18c019ac952595885d19dc688db9e978186f750dd141dfb7367743bb","observation_id":"e05b2d76-9360-4da1-9578-745506e24951","resolution":{"observed_at":"2026-05-16T08:12:31.388876Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2310.16834","last_updated":"2024-06-06T21:06:44Z","snapshot_observed_at":"2026-08-14T20:57:18.809821Z","submitted_at":"2023-10-25T17:59:12Z","title":"Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-13T02:59:23.837269Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2310.16834"},"observation_digest":"sha256:0438fd8bf742a3629b65fd0b68efc3c40013701d16ff75a6a9df630417d49f68","observation_id":"4cc56589-a6fe-4994-867c-175570242cef","resolution":{"observed_at":"2026-05-13T02:59:23.870157Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-12T17:51:01.432420Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.12279","last_updated":"2025-03-10T11:08:17Z","snapshot_observed_at":"2026-08-12T17:41:18.800187Z","submitted_at":"2024-11-19T06:57:45Z","title":"HouseTune: Two-Stage Floorplan Generation with LLM Assistance","version":4},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T17:51:01.432420Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2411.12279"},"observation_digest":"sha256:657536d3c1986ec18f069edb48d7b63c8b92667dcb4741d07820f6cde3791582","observation_id":"c1ee6285-147a-4f49-84da-611dec9aaf1c","resolution":{"observed_at":"2026-08-12T17:51:01.432420Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-12T12:24:55.219635Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.17248","last_updated":"2024-11-26T09:26:36Z","snapshot_observed_at":"2026-08-13T15:07:53.230168Z","submitted_at":"2024-11-26T09:26:36Z","title":"DiffSLT: Enhancing Diversity in Sign Language Translation via Diffusion Model","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T12:24:55.219635Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2411.17248"},"observation_digest":"sha256:2f1c013b83e007e0ad3619de19e5de0c34cded8cf7de3185e023f1ba8a3037e4","observation_id":"ccef0c1a-a0f9-49c8-ab34-d512a345abe4","resolution":{"observed_at":"2026-08-12T12:24:55.219635Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-11T23:02:16.120211Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.02929","last_updated":"2025-02-22T05:58:21Z","snapshot_observed_at":"2026-08-14T05:17:41.334885Z","submitted_at":"2024-12-04T00:42:15Z","title":"Panoptic Diffusion Models: co-generation of images and segmentation maps","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-11T23:02:16.120211Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2412.02929"},"observation_digest":"sha256:32969d93ba5c2eee0f83f0e736d2ba51bc4b1e67e68b5b9e20dafa125a64dc0f","observation_id":"2bb28a40-ae9a-4eb5-93b1-5c7126b9263f","resolution":{"observed_at":"2026-08-11T23:02:16.120211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-11T21:30:03.640968Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.04452","last_updated":"2025-06-11T18:15:59Z","snapshot_observed_at":"2026-08-12T13:17:22.592181Z","submitted_at":"2024-12-05T18:58:17Z","title":"Factorized Video Autoencoders for Efficient Generative Modelling","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T21:30:03.640968Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2412.04452"},"observation_digest":"sha256:70fe1a4297868dc7b0bd4c25cf5c8052908b3a5fb90983162ecde7d7a03c1e4d","observation_id":"4d548e13-3cf5-4307-aa7d-a1ed5689ff5b","resolution":{"observed_at":"2026-08-11T21:30:03.640968Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-11T18:06:11.483467Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.08296","last_updated":"2025-05-03T07:09:58Z","snapshot_observed_at":"2026-08-12T03:15:26.926044Z","submitted_at":"2024-12-11T11:13:43Z","title":"GDSG: Graph Diffusion-based Solution Generator for Optimization Problems in MEC Networks","version":3},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-11T18:06:11.483467Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2412.08296"},"observation_digest":"sha256:d27093b8a2674d458c3fa162bab6fcd21c97092d671a93edae9e1ee247a1f7eb","observation_id":"01636d89-6222-4275-844b-968f3e177d34","resolution":{"observed_at":"2026-08-11T18:06:11.483467Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-11T11:38:24.400914Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.15213","last_updated":"2025-03-24T04:06:07Z","snapshot_observed_at":"2026-08-14T01:58:04.323386Z","submitted_at":"2024-12-19T18:59:56Z","title":"Flowing from Words to Pixels: A Noise-Free Framework for Cross-Modality Evolution","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T11:38:24.400914Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2412.15213"},"observation_digest":"sha256:28a3d17fe8b4b0329fc402891e95cea0077ca8fd5b3f9f78e31afd8439dce0a7","observation_id":"2f56a1d2-0998-4c99-9fb4-a4bf73db0424","resolution":{"observed_at":"2026-08-11T11:38:24.400914Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-10T23:02:07.591748Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.00289","last_updated":"2025-04-01T19:09:34Z","snapshot_observed_at":"2026-08-13T05:47:26.570433Z","submitted_at":"2024-12-31T05:49:00Z","title":"Dual Diffusion for Unified Image Generation and Understanding","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T23:02:07.591748Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2501.00289"},"observation_digest":"sha256:f2d63fd34983b9f7fbfdabb64e02bd42ff04e261ee6f64a17d7045a47611082d","observation_id":"7203fae7-e095-4923-9c80-a057ab80e1cd","resolution":{"observed_at":"2026-08-10T23:02:07.591748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-10T14:01:55.464466Z","title":"Chen, T., Zhang, R., and Hinton, G","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.15781","last_updated":"2025-06-03T11:52:35Z","snapshot_observed_at":"2026-08-13T01:45:51.986000Z","submitted_at":"2025-01-27T04:59:29Z","title":"Large Language Models to Diffusion Finetuning","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-10T14:01:55.464466Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2501.15781"},"observation_digest":"sha256:50fb55e950f77ea23b6d347133e8119c279d8421959ebae7d1fe86676e966858","observation_id":"0706661f-e94e-4081-b000-0bc171da4569","resolution":{"observed_at":"2026-08-10T14:01:55.464466Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-09T16:13:35.767609Z","title":"Diffusiondet: Diffusion model for object detection","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.06805","last_updated":"2025-06-06T14:57:09Z","snapshot_observed_at":"2026-08-12T17:53:05.592754Z","submitted_at":"2025-02-03T10:15:08Z","title":"Efficient Diffusion Models: A Survey","version":3},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-09T16:13:35.767609Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2502.06805"},"observation_digest":"sha256:e2728b33bba3b1348dba9b4c72f0cb7640aadc545d075cf0b6b6e767ae3abdfd","observation_id":"1fde2634-03fa-48db-a9c3-a763dbb9345b","resolution":{"observed_at":"2026-08-09T16:13:35.767609Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-07T20:56:22.739266Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.09622","last_updated":"2025-06-09T02:36:10Z","snapshot_observed_at":"2026-08-13T15:53:22.405222Z","submitted_at":"2025-02-13T18:59:47Z","title":"Theoretical Benefit and Limitation of Diffusion Language Model","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T20:56:22.739266Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2502.09622"},"observation_digest":"sha256:10908976e9bfdb193a9738912d7626ef30708fb32c93012dd2cfb97122b9408f","observation_id":"626451f0-b75b-447e-ab29-2be2722aec21","resolution":{"observed_at":"2026-08-07T20:56:22.739266Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2502.09992","last_updated":"2025-10-18T15:35:05Z","snapshot_observed_at":"2026-08-04T04:34:22.998376Z","submitted_at":"2025-02-14T08:23:51Z","title":"Large Language Diffusion Models","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-11T01:42:54.279353Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2502.09992"},"observation_digest":"sha256:3714d8de037c2f5a8862bcfe93f992133571fd8cecde6f177c90f4e191b4c75d","observation_id":"0f74e20c-a10a-4793-86b0-2e8a4632ff79","resolution":{"observed_at":"2026-05-11T01:42:55.193501Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-07T15:00:49.575504Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16680","last_updated":"2025-05-22T13:46:18Z","snapshot_observed_at":"2026-08-11T02:42:44.948124Z","submitted_at":"2025-05-22T13:46:18Z","title":"Learning Genomic Structure from $k$-mers","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:00:49.575504Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2505.16680"},"observation_digest":"sha256:6ef59f2e30fb3cd047f0fedd476b9e8ac443e210bde41721ed1fc3e4b6e2eda4","observation_id":"1234a14f-1c07-489c-9fe8-d74f0af1f105","resolution":{"observed_at":"2026-08-07T15:00:49.575504Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2505.16933","last_updated":"2025-06-04T05:52:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-22T17:23:26Z","title":"LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-05-17T03:46:06.074416Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2505.16933"},"observation_digest":"sha256:0cf29fef234adb9be5da01fe6367075a1d59bb41553883f5faa188f6998555fd","observation_id":"826ada18-bbca-486e-abb0-90a06845a8e1","resolution":{"observed_at":"2026-05-17T03:46:06.312461Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-07T14:36:00.148687Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.18392","last_updated":"2025-05-23T21:41:56Z","snapshot_observed_at":"2026-08-12T23:36:53.394491Z","submitted_at":"2025-05-23T21:41:56Z","title":"Applications of Modular Co-Design for De Novo 3D Molecule Generation","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T14:36:00.148687Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2505.18392"},"observation_digest":"sha256:b2c1e79663119fbf2e0ccbc943a7f065db8e42936811379a7297c39a729e7bd4","observation_id":"08f27d32-77cd-48c5-a5f4-41694f585fd7","resolution":{"observed_at":"2026-08-07T14:36:00.148687Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-07T13:26:22.495580Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.21833","last_updated":"2025-05-27T23:41:30Z","snapshot_observed_at":"2026-08-13T13:18:56.804926Z","submitted_at":"2025-05-27T23:41:30Z","title":"A Graph Completion Method that Jointly Predicts Geometry and Topology Enables Effective Molecule Assembly","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T13:26:22.495580Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2505.21833"},"observation_digest":"sha256:b55046fe789c2484ed54d74cb9f584256c00f03b1d024b427c67724bc5541cbc","observation_id":"f67d8e02-5f2f-4421-b3d8-f1da4c42f35f","resolution":{"observed_at":"2026-08-07T13:26:22.495580Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-07T05:14:34.769719Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.08541","last_updated":"2025-07-05T09:04:57Z","snapshot_observed_at":"2026-08-11T02:31:38.838862Z","submitted_at":"2025-06-10T08:08:31Z","title":"TrajFlow: Multi-modal Motion Prediction via Flow Matching","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:34.769719Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2506.08541"},"observation_digest":"sha256:0e1d5c6977e2e72f25df728909b921b5e2e8737db987498709bd02921fd54b12","observation_id":"894480e6-58d3-4343-abf7-f22f00fc0640","resolution":{"observed_at":"2026-08-07T05:14:34.769719Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-06T23:48:39.299295Z","title":"Analog bits: Gen- erating discrete data using diffusion models with self- conditioning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.16288","last_updated":"2025-06-19T13:05:12Z","snapshot_observed_at":"2026-08-14T18:43:03.762231Z","submitted_at":"2025-06-19T13:05:12Z","title":"Next-Token Prediction Should be Ambiguity-Sensitive: A Meta-Learning Perspective","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T23:48:39.299295Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2506.16288"},"observation_digest":"sha256:62b4be6a22af77fa212ec00284473385d261df44c0cf22578e68c330ca1b625d","observation_id":"71dbcc7d-98ba-4a84-ab08-013cdf62394e","resolution":{"observed_at":"2026-08-06T23:48:39.299295Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-06T19:14:23.025747Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.06203","last_updated":"2025-07-10T16:43:36Z","snapshot_observed_at":"2026-08-07T04:57:37.201438Z","submitted_at":"2025-07-08T17:29:07Z","title":"A Survey on Latent Reasoning","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T19:14:23.025747Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2507.06203"},"observation_digest":"sha256:3754fbd2ee5513eaa463b9193fe19dcb431c0083ab165e635d2421f09902fabe","observation_id":"f5bb0fb7-9040-432b-a5e2-5a0633b079f1","resolution":{"observed_at":"2026-08-06T19:14:23.025747Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-06T05:32:07.423687Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning.arXiv preprint arXiv:2208.04202, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.01616","last_updated":"2025-08-03T06:25:17Z","snapshot_observed_at":"2026-08-14T22:44:10.276538Z","submitted_at":"2025-08-03T06:25:17Z","title":"The Philosophy and Physics of Duality","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T05:32:07.423687Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2508.01616"},"observation_digest":"sha256:b322c17f15d680b111ea857b12ae57e1a9eccf7accdb2e4e24c30d84bcbae9af","observation_id":"b0fa07ab-34ea-4f8c-9c14-c19f0cbf81bc","resolution":{"observed_at":"2026-08-06T05:32:07.423687Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T18:43:42.404439Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.14352","last_updated":"2025-08-20T01:47:46Z","snapshot_observed_at":"2026-08-07T13:06:27.120692Z","submitted_at":"2025-08-20T01:47:46Z","title":"SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-05T18:43:42.404439Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2508.14352"},"observation_digest":"sha256:2d0dce065ce0cdfaba1f3ca75e8452e6b93cbf41e558ab230b0220a7ee7e8523","observation_id":"0a2f1641-0347-45f8-ad61-af1924a68ba4","resolution":{"observed_at":"2026-08-05T18:43:42.404439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-04T22:55:29.831085Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning.arXiv preprint arXiv:2208.04202, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.06932","last_updated":"2025-09-10T14:34:25Z","snapshot_observed_at":"2026-08-13T21:14:45.123295Z","submitted_at":"2025-09-08T17:45:40Z","title":"LLaDA-VLA: Vision Language Diffusion Action Models","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-04T22:55:29.831085Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2509.06932"},"observation_digest":"sha256:6fc7342f97334ccb1646b8af838f1060a0a191803538986199ad0d627af8b907","observation_id":"d000b2f0-3e47-4c7b-bc31-a64b339ac0cb","resolution":{"observed_at":"2026-08-04T22:55:29.831085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-04T17:57:46.949498Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.10396","last_updated":"2025-09-12T16:44:31Z","snapshot_observed_at":"2026-08-12T01:25:18.465764Z","submitted_at":"2025-09-12T16:44:31Z","title":"Inpainting-Guided Policy Optimization for Diffusion Large Language Models","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-04T17:57:46.949498Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2509.10396"},"observation_digest":"sha256:90b4155a850fa19f60bc431eb4cb521fb2f414929762baa822cfcf576cdf5a63","observation_id":"ff3fae01-91d5-48b5-bb51-d7b75d33a7d5","resolution":{"observed_at":"2026-08-04T17:57:46.949498Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-04T08:09:17.423679Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.22510","last_updated":"2026-07-11T23:42:33Z","snapshot_observed_at":"2026-08-14T04:12:00.631611Z","submitted_at":"2025-10-26T03:24:31Z","title":"CANDI: Hybrid Discrete-Continuous Diffusion Models","version":3},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-04T08:09:17.423679Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2510.22510"},"observation_digest":"sha256:6c21d807118956732e2f92bbfdc69c709935a4c57c5df0fce2511a07764d9f49","observation_id":"29a287a3-f63b-4ccc-a1ca-5a5551d04db2","resolution":{"observed_at":"2026-08-04T08:09:17.423679Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-03T15:46:06.476387Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning.arXiv preprint arXiv:2208.04202, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.15702","last_updated":"2026-07-01T03:39:09Z","snapshot_observed_at":"2026-08-06T15:52:47.972204Z","submitted_at":"2025-12-17T18:53:29Z","title":"End-to-End Training for Autoregressive Video Diffusion via Self-Resampling","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T15:46:06.476387Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2512.15702"},"observation_digest":"sha256:c678abebc610a191723062faca217cc65ec2b46faa79ae2531ae582adce4af49","observation_id":"87231de0-7fae-44ac-a936-de7cb778ff45","resolution":{"observed_at":"2026-08-03T15:46:06.476387Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2602.04883","last_updated":"2026-05-18T18:23:50Z","snapshot_observed_at":"2026-08-07T14:56:29.023603Z","submitted_at":"2026-02-04T18:59:49Z","title":"Protein Autoregressive Modeling via Multiscale Structure Generation","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-21T13:21:53.668727Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2602.04883"},"observation_digest":"sha256:fec2b5d9c487e2e87b7df1f3e913dc003d2b12f2f82758d5a700a9835aef5295","observation_id":"56a78ade-ea5e-4f3d-910c-f63fc6d310b2","resolution":{"observed_at":"2026-05-21T13:24:11.284361Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2602.16813","last_updated":"2026-05-20T16:23:05Z","snapshot_observed_at":"2026-08-11T06:21:47.511868Z","submitted_at":"2026-02-18T19:23:07Z","title":"Flow Map Language Models: One-step Language Modeling via Continuous Denoising","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-15T21:01:42.916835Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2602.16813"},"observation_digest":"sha256:15ac64d0aa86f440d5c698a6f07d9e1467e73410ad52af4dad42ff6ad8d28a0a","observation_id":"f6b759b9-c42e-433e-9c00-acdf3e212cee","resolution":{"observed_at":"2026-05-15T21:10:19.210172Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2602.16813","last_updated":"2026-05-20T16:23:05Z","snapshot_observed_at":"2026-08-11T06:21:47.511868Z","submitted_at":"2026-02-18T19:23:07Z","title":"Flow Map Language Models: One-step Language Modeling via Continuous Denoising","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-21T12:23:49.031978Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2602.16813"},"observation_digest":"sha256:136fe1a632fb54b3c8ddd78d75ea23f93c2c45a5f3e525994982b10d1995432a","observation_id":"10ed26c8-0c81-4146-aa79-1a981a207ce6","resolution":{"observed_at":"2026-05-21T12:24:10.592170Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-02T17:49:49.320322Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2603.22216","last_updated":"2026-07-23T16:32:10Z","snapshot_observed_at":"2026-08-09T02:33:41.982497Z","submitted_at":"2026-03-23T17:13:22Z","title":"Gumbel Distillation for Parallel Text Generation","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-02T17:49:49.320322Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2603.22216"},"observation_digest":"sha256:fcf4592e99d5cf7cebfa94e8c155dfce63839a2d7cf6677a1d24e9a9755b21cf","observation_id":"8447635e-cde6-4c44-baf8-70e5f7a3f626","resolution":{"observed_at":"2026-08-02T17:49:49.320322Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2604.11748","last_updated":"2026-04-15T16:15:30Z","snapshot_observed_at":"2026-08-14T05:04:31.628759Z","submitted_at":"2026-04-13T17:21:41Z","title":"LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T16:26:53.241071Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2604.11748"},"observation_digest":"sha256:d4747953c88bfca2bbf9044e9ee3551019acd7398182efb739097c9782794bc9","observation_id":"df0c4b38-2ced-4a63-b0a6-3dfa393a130f","resolution":{"observed_at":"2026-05-11T08:50:59.518122Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2604.18966","last_updated":"2026-05-17T12:00:22Z","snapshot_observed_at":"2026-08-01T19:53:45.797959Z","submitted_at":"2026-04-21T01:29:52Z","title":"Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training","version":1},"reference_index":201,"source":"arxiv_source","source_observed_at":"2026-05-10T03:04:54.146481Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2604.18966"},"observation_digest":"sha256:fc579a976c833a67160bb136669878694786487ae1338abeb3a9834075751136","observation_id":"0366da38-5726-4ea7-b703-b8adcf55016e","resolution":{"observed_at":"2026-05-11T12:46:03.894954Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2604.18995","last_updated":"2026-06-02T03:22:46Z","snapshot_observed_at":"2026-08-11T18:23:30.317276Z","submitted_at":"2026-04-21T02:26:08Z","title":"$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T02:56:32.367404Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2604.18995"},"observation_digest":"sha256:e115f22f0b6414e11c5f4a5d60ca4f64a7f4a30ee0c1456f5e4f03dc67f98801","observation_id":"b894e5b5-e5e6-4279-a827-5ce0bc51ffc2","resolution":{"observed_at":"2026-05-11T12:46:25.492440Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2604.26985","last_updated":"2026-06-06T20:43:37Z","snapshot_observed_at":"2026-08-14T18:26:18.933174Z","submitted_at":"2026-04-28T19:34:04Z","title":"Simple Self-Conditioning Adaptation for Masked Diffusion Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-07T16:38:22.306140Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2604.26985"},"observation_digest":"sha256:cbdd86f674b685674338c3ca28aa9edef2d89ca772d778f10425200d4ab827c3","observation_id":"d7f9282e-d4d0-40ce-8b0e-45634b4f3935","resolution":{"observed_at":"2026-05-11T23:36:33.506227Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2605.07193","last_updated":"2026-05-08T03:40:39Z","snapshot_observed_at":"2026-08-14T15:52:42.188625Z","submitted_at":"2026-05-08T03:40:39Z","title":"Coupling Models for One-Step Discrete Generation","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-05-11T02:58:10.909499Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2605.07193"},"observation_digest":"sha256:9e483f78f72754e99bbc3f45d0fb8d5d693175c87e6cc7a41f27c813f8eae62f","observation_id":"d169ac96-4801-4859-b905-17da94772aa2","resolution":{"observed_at":"2026-05-11T03:00:55.037893Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2605.11577","last_updated":"2026-05-12T06:02:59Z","snapshot_observed_at":"2026-08-11T16:38:18.584665Z","submitted_at":"2026-05-12T06:02:59Z","title":"BitLM: Unlocking Multi-Token Language Generation with Bitwise Continuous Diffusion","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-13T01:54:23.273159Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2605.11577"},"observation_digest":"sha256:632006e38be53c9dac56c9060b5d52d8b5b616c34d22ad60954aa623856251ca","observation_id":"a6f7751b-7a81-46ff-8f8e-b794203483a4","resolution":{"observed_at":"2026-05-13T01:57:05.326607Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2605.19726","last_updated":"2026-05-19T12:01:13Z","snapshot_observed_at":"2026-08-13T21:59:55.814750Z","submitted_at":"2026-05-19T12:01:13Z","title":"Efficient Long-Context Modeling in Diffusion Language Models via Block Approximate Sparse Attention","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-20T05:52:14.089334Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2605.19726"},"observation_digest":"sha256:5fe4164f9f1671094af8306bee42e7729d6ea36ad262df129b7f1146472885f4","observation_id":"52880562-8001-4b16-a0ac-55fe3b9a1aeb","resolution":{"observed_at":"2026-05-20T05:53:04.641918Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2605.29233","last_updated":"2026-05-30T19:57:27Z","snapshot_observed_at":"2026-08-13T05:21:45.371809Z","submitted_at":"2026-05-28T01:48:29Z","title":"BlockBatch: Multi-Scale Consensus Decoding for Efficient Diffusion Language Model Inference","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-29T08:34:28.624577Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2605.29233"},"observation_digest":"sha256:8e7755e43d42fe1bb2ce8c182f1679c526b9db0514d127e2ba9d579413c6103c","observation_id":"ad738634-47ed-40c5-bb17-eaa30fb77b53","resolution":{"observed_at":"2026-06-29T08:43:15.918439Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2606.02133","last_updated":"2026-06-11T17:13:32Z","snapshot_observed_at":"2026-08-05T11:37:25.145320Z","submitted_at":"2026-06-01T11:59:46Z","title":"Variational Learning for Insertion-based Generation","version":3},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-06-28T15:23:32.821620Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2606.02133"},"observation_digest":"sha256:ec11003498916640a9c6b47c1ac7523d3b32cef22351e0049f75274160f5f510","observation_id":"40db3e8f-c4e9-4176-b485-96109f14b143","resolution":{"observed_at":"2026-07-01T22:26:17.757727Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2606.08150","last_updated":"2026-06-06T13:00:34Z","snapshot_observed_at":"2026-08-06T22:58:07.064872Z","submitted_at":"2026-06-06T13:00:34Z","title":"Property-Informed Diffusion-Based Text-to-Microstructure Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T19:48:27.318590Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2606.08150"},"observation_digest":"sha256:573179e1cb4388a866bb653d6c61d02189b79a5c8cef307de61aebb780f90f85","observation_id":"412f5a60-2fef-4489-9304-0db36894b833","resolution":{"observed_at":"2026-07-02T21:17:25.133229Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2606.20404","last_updated":"2026-06-18T15:56:07Z","snapshot_observed_at":"2026-08-13T13:28:40.663689Z","submitted_at":"2026-06-18T15:56:07Z","title":"FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-26T18:17:25.479543Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2606.20404"},"observation_digest":"sha256:cf99c253849e8639d853c7560e96e3ab2ac30e44bd4af730f6defe644b3ad345","observation_id":"6204e9d3-684d-4c1c-b0f9-8b16a90f8abe","resolution":{"observed_at":"2026-07-04T03:19:30.004069Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2606.21061","last_updated":"2026-06-19T03:14:00Z","snapshot_observed_at":"2026-07-31T07:50:26.534774Z","submitted_at":"2026-06-19T03:14:00Z","title":"Neural Architecture Distributions: A New Paradigm for Stochastic Segmentation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-26T14:56:52.316735Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2606.21061"},"observation_digest":"sha256:ee360f9fc405ed3e3b9cb8ce4a70b4e804ce00c9b90c9f0b2d9c007379743794","observation_id":"83133e6f-d6ef-4f69-87a4-222e6cc6bf80","resolution":{"observed_at":"2026-07-04T05:59:38.353919Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2606.22702","last_updated":"2026-06-21T22:38:35Z","snapshot_observed_at":"2026-08-14T23:38:56.679804Z","submitted_at":"2026-06-21T22:38:35Z","title":"Modular Diffusion Models for Structured Visual Recognition","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-26T10:29:04.711627Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2606.22702"},"observation_digest":"sha256:50402cabc9efc75ae7fd1287acc7ae678bcee2cde39bb849e499a17bf97de34c","observation_id":"f7c5e9a6-9437-4450-a707-8c3d40b85988","resolution":{"observed_at":"2026-07-04T09:09:43.116042Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2606.27617","last_updated":"2026-06-26T00:16:40Z","snapshot_observed_at":"2026-08-13T20:29:40.928847Z","submitted_at":"2026-06-26T00:16:40Z","title":"Masked Language Flow Models","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-06-29T01:17:56.122002Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2606.27617"},"observation_digest":"sha256:251ddb681e408f9a7b928e0569279000ed31ab9189a9a79a146b2dbca46d310c","observation_id":"0810526b-92e4-4f41-8266-134504019441","resolution":{"observed_at":"2026-07-01T19:06:02.664543Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2606.29150","last_updated":"2026-06-28T02:10:36Z","snapshot_observed_at":"2026-08-14T07:39:55.571318Z","submitted_at":"2026-06-28T02:10:36Z","title":"Flow Reasoning Models: Scaling Reasoning Through Iterative Self-Refinement","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-30T07:55:28.254309Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2606.29150"},"observation_digest":"sha256:e5ba5d17160de910dc935e4e2009f3f6326085cbca9ae5cf876ca01d04a9aa8d","observation_id":"50910bb2-1866-49a9-bc9c-98a5df05dc81","resolution":{"observed_at":"2026-06-30T08:04:28.463260Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2607.00588","last_updated":"2026-07-01T08:13:07Z","snapshot_observed_at":"2026-08-06T06:20:07.932561Z","submitted_at":"2026-07-01T08:13:07Z","title":"Low Perplexity is Repetition: A One-Dimensional Self-Conditioning Attractor in Continuous Diffusion LMs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-02T13:17:01.144370Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2607.00588"},"observation_digest":"sha256:bbfd818f0d8f00c4a78dde6bde5c538dfa3faf385c46ed114b64b2ac9444e196","observation_id":"29aedbae-512d-4782-8138-bdeb81e720ba","resolution":{"observed_at":"2026-07-02T13:26:58.650265Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2607.00714","last_updated":"2026-07-01T10:02:20Z","snapshot_observed_at":"2026-07-07T00:06:20.346610Z","submitted_at":"2026-07-01T10:02:20Z","title":"Self-conditioned Flow Map Language Models via Fixed-point Flows","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-02T13:01:21.252611Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2607.00714"},"observation_digest":"sha256:4a2bf469a1d330a0c42af247b2c2fbbcba88bd357e897f4a7a4cf43b792caab1","observation_id":"e5696531-b9ad-497e-82f8-c796d190024f","resolution":{"observed_at":"2026-07-02T13:06:58.542798Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2607.01775","last_updated":"2026-07-02T06:45:43Z","snapshot_observed_at":"2026-08-05T08:13:48.395073Z","submitted_at":"2026-07-02T06:45:43Z","title":"Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-07-03T17:30:39.458521Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2607.01775"},"observation_digest":"sha256:ce00d8421ae44f5caaed6e39041e9c95f3757465e3951134726cbfb1640680e0","observation_id":"6ddd1c37-fdec-48d3-9f2b-59d7cf6cc01b","resolution":{"observed_at":"2026-07-03T17:38:43.585386Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":"2208.04202","doi":"10.48550/arxiv.2208.04202","metadata_source":"pith","pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analog bits: Generating discrete data using diffusion models with self-conditioning","venue":"cs.CV","work_id":"89278cce-9610-430c-a4e1-9c5915aa5c95","year":2022},"citing_paper":{"arxiv_id":"2607.06930","last_updated":"2026-07-08T02:50:02Z","snapshot_observed_at":"2026-08-06T14:13:36.728143Z","submitted_at":"2026-07-08T02:50:02Z","title":"Imputation Meets Clustering: Exploiting Latent Subgroup Structure for Missing Data Recovery","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-09T22:53:25.139723Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2607.06930"},"observation_digest":"sha256:dda36668c85788f89602e5b88a5849f068ed0e2a56e157367efa367ead16a623","observation_id":"300f6da9-df23-436e-b842-0e851817e251","resolution":{"observed_at":"2026-07-09T22:56:37.659585Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.04202","snapshot_observed_at":"2026-08-06T22:57:59.754749Z","title":"arXiv preprint arXiv:2208.04202 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04525","last_updated":"2026-08-05T06:57:30Z","snapshot_observed_at":"2026-08-13T17:40:35.657293Z","submitted_at":"2026-08-05T06:57:30Z","title":"Coupled Continuous-Discrete Generation for Scene Text Image Super-Resolution","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-06T22:57:59.754749Z"},"links":{"cited_paper":"/paper/2208.04202","citing_paper":"/paper/2608.04525"},"observation_digest":"sha256:7d081eaf89ccc4b23602407849a43cf939e86ade3538150cf76b700e53acc736","observation_id":"b4c5b4e5-c694-4aa0-9e09-508f322afe8f","resolution":{"observed_at":"2026-08-06T22:57:59.754749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2208.04202/citation-record","integrity":"/paper/2208.04202/integrity","json":"/paper/2208.04202/citation-record.json","paper":"/paper/2208.04202"},"outbound":[],"paper":{"arxiv_id":"2208.04202","last_updated":"2023-03-01T00:18:33Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T14:48:56.811001Z","submitted_at":"2022-08-08T15:08:40Z","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 52 inbound Pith citation observations for arXiv:2208.04202."}