{"as_of":"2026-08-17T22:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a9401f85c12db866b5c620a18c0843112753dd565ae7cd0f89e6347a7b57285c","coverage":[{"denominator":51,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":51,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T18:38:40.745600Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T00:18:31.891590Z","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":"2026-05-14T22:08:04.887445Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11925","snapshot_observed_at":"2026-08-07T14:01:04.152535Z","title":"Continuous speculative decoding for autoregressive image generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20297","last_updated":"2025-05-26T17:59:57Z","snapshot_observed_at":"2026-08-15T22:03:53.924876Z","submitted_at":"2025-05-26T17:59:57Z","title":"DiSA: Diffusion Step Annealing in Autoregressive Image Generation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T14:01:04.152535Z"},"links":{"cited_paper":"/paper/2411.11925","citing_paper":"/paper/2505.20297"},"observation_digest":"sha256:61753965923f6ad277995ff4ad3a8186d35bca95468d431de0bf30a3a969d7dc","observation_id":"eeab8dee-d510-4c5a-abbe-33cb4135b3b6","resolution":{"observed_at":"2026-08-07T14:01:04.152535Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11925","snapshot_observed_at":"2026-08-15T20:56:29.113745Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01986","last_updated":"2025-05-16T22:12:29Z","snapshot_observed_at":"2026-08-17T19:26:28.026855Z","submitted_at":"2025-05-16T22:12:29Z","title":"SpecMemo: Speculative Decoding is in Your Pocket","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T20:56:29.113745Z"},"links":{"cited_paper":"/paper/2411.11925","citing_paper":"/paper/2506.01986"},"observation_digest":"sha256:ca70580c6364cc189d1b6ab26c51b807a5874e5195fb61f90646104c0d4f69fc","observation_id":"20eedfa6-f91e-4cd1-b9e1-5c24ef58938d","resolution":{"observed_at":"2026-08-15T20:56:29.113745Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11925","snapshot_observed_at":"2026-08-04T15:58:15.987436Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.18085","last_updated":"2026-06-11T00:26:51Z","snapshot_observed_at":"2026-08-13T05:15:01.921580Z","submitted_at":"2025-09-22T17:58:21Z","title":"Structuring The Future: Diffusion LLM Speculative Decoding via Calibrated Draft Graphs","version":4},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-04T15:58:15.987436Z"},"links":{"cited_paper":"/paper/2411.11925","citing_paper":"/paper/2509.18085"},"observation_digest":"sha256:8356799083b38a421f6daaa799cc89988293dbf9e8e671531c4ab0d63d76b92e","observation_id":"3f57ad72-6331-423b-95ce-f72200cd5c75","resolution":{"observed_at":"2026-08-04T15:58:15.987436Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"cited_work":{"arxiv_id":"2411.11925","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.11925","snapshot_observed_at":"2026-07-02T02:17:12.344258Z","title":"arXiv preprint arXiv:2411.11925 (2024) 10","venue":null,"work_id":"a559cc99-21c7-4f48-b316-c0697bb17a81","year":2024},"citing_paper":{"arxiv_id":"2603.28049","last_updated":"2026-06-29T03:15:39Z","snapshot_observed_at":"2026-08-14T06:03:38.289653Z","submitted_at":"2026-03-30T05:29:00Z","title":"Drift-AR: Single-Step Visual Autoregressive Generation via Anti-Symmetric Drifting","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-14T22:03:27.981438Z"},"links":{"cited_paper":"/paper/2411.11925","citing_paper":"/paper/2603.28049"},"observation_digest":"sha256:4e033d43c3589a929ddeeaf2642ce27d0e84cde228323c84acf0b6bc5bac68b7","observation_id":"785795ff-db45-4125-bd17-e3bae8ebdd82","resolution":{"observed_at":"2026-07-02T02:17:12.344258Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"cited_work":{"arxiv_id":"2411.11925","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.11925","snapshot_observed_at":"2026-07-02T02:17:12.344258Z","title":"arXiv preprint arXiv:2411.11925 (2024) 10","venue":null,"work_id":"a559cc99-21c7-4f48-b316-c0697bb17a81","year":2024},"citing_paper":{"arxiv_id":"2605.07230","last_updated":"2026-05-08T04:32:17Z","snapshot_observed_at":"2026-08-14T14:15:12.892178Z","submitted_at":"2026-05-08T04:32:17Z","title":"CASCADE: Context-Aware Relaxation for Speculative Image Decoding","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-11T02:08:27.374066Z"},"links":{"cited_paper":"/paper/2411.11925","citing_paper":"/paper/2605.07230"},"observation_digest":"sha256:b7b9192cdcbfb768083af3d9ffa0395d4a07556d9609ac6f202702fccb5579e7","observation_id":"597da089-7d8f-4719-b59a-816b5529e681","resolution":{"observed_at":"2026-07-02T02:17:12.344258Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11925","snapshot_observed_at":"2026-08-16T00:18:31.891590Z","title":"arXiv preprint arXiv:2411.11925 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-17T15:53:23.221657Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":220,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:31.891590Z"},"links":{"cited_paper":"/paper/2411.11925","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:c3942d775d19a3a6b3690b302ff1ed214692c1cb7b4c6885d632463634dd0af8","observation_id":"95a47129-54d6-4972-bea2-ff8bfc1c975f","resolution":{"observed_at":"2026-08-16T00:18:31.891590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2411.11925/citation-record","integrity":"/paper/2411.11925/integrity","json":"/paper/2411.11925/citation-record.json","paper":"/paper/2411.11925"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T18:38:39.730338Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.730338Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:ee64090276c64e1dc73fc545cbbfe6ff5469e11c152a1291d49d96833995be5e","observation_id":"e674247d-a3ee-443b-ac1c-0bef9c36e256","resolution":{"observed_at":"2026-08-12T18:38:39.730338Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10774","last_updated":"2024-06-14T23:32:32Z","snapshot_observed_at":"2026-08-17T10:13:54.763177Z","submitted_at":"2024-01-19T15:48:40Z","title":"Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.10774","snapshot_observed_at":"2026-08-12T18:38:39.802719Z","title":"Medusa: Simple llm inference acceleration framework with multiple decoding heads","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.802719Z"},"links":{"cited_paper":"/paper/2401.10774","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:31c0313c90da9afaaa72f6913dd4cac4ed735508c4ffc204eec0c69ebb9a1fae","observation_id":"abbe2166-e68d-4016-9102-d29bf3511c55","resolution":{"observed_at":"2026-08-12T18:38:39.802719Z","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":"2026-08-12T18:38:42.965592Z","title":"Generalized accept-reject sampling schemes","venue":null,"work_id":"6c9c589b-15a0-41d0-8476-d967338e928e","year":2004},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.815550Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:b8dd9af765643adcc59a5b3e667a79231f2e4e5de5b0c07ef209381920c2c974","observation_id":"b0a75ec7-ea1b-46b3-b365-d9fc8d8d2ae5","resolution":{"observed_at":"2026-08-12T18:38:42.972971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T18:38:42.864310Z","title":"Maskgit: Masked generative image transformer","venue":null,"work_id":"d6db5096-838d-46ab-983b-7c0f754ab152","year":2022},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.824831Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:737ba6fb643ca13d2d706aed362cb427756c29b7e3be4c38d0d7ccf8a5e7e8e1","observation_id":"41d2b7ec-1777-40f5-b611-81fbb69cab4e","resolution":{"observed_at":"2026-08-12T18:38:42.947343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.00704","last_updated":"2023-01-02T14:43:38Z","snapshot_observed_at":"2026-08-16T16:04:52.013149Z","submitted_at":"2023-01-02T14:43:38Z","title":"Muse: Text-To-Image Generation via Masked Generative Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.00704","snapshot_observed_at":"2026-08-12T18:38:39.833736Z","title":"Muse: Text-to-image generation via masked generative transformers","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.833736Z"},"links":{"cited_paper":"/paper/2301.00704","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:32ad9e90a4d0ccd88a55b358b1d022bde5a5b8e9c7b7931880aa7e8b320b8d9e","observation_id":"e16cb7ae-9a78-4138-92da-bc3c0754eb4d","resolution":{"observed_at":"2026-08-12T18:38:39.833736Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.01318","last_updated":"2023-02-02T18:44:11Z","snapshot_observed_at":"2026-08-13T23:55:57.074762Z","submitted_at":"2023-02-02T18:44:11Z","title":"Accelerating Large Language Model Decoding with Speculative Sampling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.01318","snapshot_observed_at":"2026-08-12T18:38:39.843924Z","title":"Accelerating large language model decoding with speculative sampling","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.843924Z"},"links":{"cited_paper":"/paper/2302.01318","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:086bca22dd2636c058169cb7a6cd5f42593ff3e675f4c1a1a038e62b19a96d66","observation_id":"c66250f3-438b-4f56-b7b9-acf804472bc5","resolution":{"observed_at":"2026-08-12T18:38:39.843924Z","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":"2026-08-12T18:38:42.754884Z","title":"Generative pretraining from pixels","venue":null,"work_id":"fcb9b893-1a9e-4a1f-b7f5-751247b862fc","year":2020},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.852478Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:c721e90b7fbf7e1e1b90279ad355bc83cf289f64e4fdb09778301e8803cdcac7","observation_id":"3a79e8dc-126e-4712-bfc1-f8056b3cfbe1","resolution":{"observed_at":"2026-08-12T18:38:42.762311Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T18:38:42.726239Z","title":"Pixelsnail: An improved autoregressive generative model","venue":null,"work_id":"0480d39b-c80c-4174-aa26-e618e8e56863","year":2018},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.861519Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:bf4ea19a26229105d473e353b750b897e1124d8f368eaff3da061ebc3ed3bbce","observation_id":"740f8edd-085e-4d07-bb9b-daedc2036c71","resolution":{"observed_at":"2026-08-12T18:38:42.732742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T18:38:42.698089Z","title":"Imagenet: A large-scale hierarchical image database","venue":null,"work_id":"f6f0f912-99a4-412a-ab00-2f14abc45703","year":2009},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.869657Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:c2029ee513caca7d7f2f036e53d76bafe7c5b2ded6de1d3f4569e84ac9e70853","observation_id":"07a1f916-25ee-4f14-a00c-c9abeb914550","resolution":{"observed_at":"2026-08-12T18:38:42.703728Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T18:38:42.657902Z","title":"Cogview: Mastering text-to-image generation via transformers","venue":null,"work_id":"c67293d9-6591-403e-9300-9dd66d057ccc","year":2021},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:39.973195Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:49e5c120eb91bdc700ce0405b0b987300b1638e321d0185d9717168fbd13282e","observation_id":"d0816ac4-1bd7-46bd-9b1b-d12b39d1c33f","resolution":{"observed_at":"2026-08-12T18:38:42.684824Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T18:38:42.596323Z","title":"Taming transformers for high-resolution image synthesis","venue":null,"work_id":"a9e1c29f-292d-415f-85b0-ae208ac24ebf","year":2021},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.007961Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:a0a15130be582c031fe0c9b53318e3a373b1e66c0be431c9471e04e550509661","observation_id":"25f5498d-dc9c-4d0c-bf0b-b5f1f77cc469","resolution":{"observed_at":"2026-08-12T18:38:42.602940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13863","last_updated":"2024-10-17T17:59:59Z","snapshot_observed_at":"2026-08-16T13:08:17.144750Z","submitted_at":"2024-10-17T17:59:59Z","title":"Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13863","snapshot_observed_at":"2026-08-12T18:38:40.017740Z","title":"Fluid: Scaling autoregressive text-to-image generative models with continuous tokens","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.017740Z"},"links":{"cited_paper":"/paper/2410.13863","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:07dd4fb02a5d0b88669c759daa494318834aa5c76a041c1c82013003e574186d","observation_id":"5aaf7ead-19ca-428b-80e7-58132bae3e0e","resolution":{"observed_at":"2026-08-12T18:38:40.017740Z","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":"2026-08-12T18:38:42.536547Z","title":"Deep autoregressive networks","venue":null,"work_id":"3296fdd2-a299-4f3d-93a3-5a95327c125e","year":2014},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.024699Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:bbd6fff7ddccdde779a27c8dc515468d75179f8070e96b272b38f56e594d0e8e","observation_id":"4c158064-cfce-437e-bb9c-47c326eac48c","resolution":{"observed_at":"2026-08-12T18:38:42.578403Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08159","last_updated":"2025-01-23T17:08:57Z","snapshot_observed_at":"2026-08-16T13:10:36.203586Z","submitted_at":"2024-10-10T17:41:54Z","title":"DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.08159","snapshot_observed_at":"2026-08-12T18:38:40.031080Z","title":"Dart: Denoising autoregressive transformer for scalable text-to-image generation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.031080Z"},"links":{"cited_paper":"/paper/2410.08159","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:01f1a5fa9cb1bac8fa1d598b68d0c1a3fd92929adac568b135a36a38f3169ff2","observation_id":"f261af9c-eb41-479f-9cd7-01ad98ba7e49","resolution":{"observed_at":"2026-08-12T18:38:40.031080Z","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":"2026-08-12T18:38:40.038376Z","title":"Gans trained by a two time-scale update rule converge to a local nash equilibrium","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.038376Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:ba4218c7d8cef18a942b3150ef9319bfe999d2a48b6ef41d4169cd479db51a87","observation_id":"3e06710a-6e42-4919-867e-6107690fdc3a","resolution":{"observed_at":"2026-08-12T18:38:40.038376Z","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":"2026-08-12T18:38:40.045983Z","title":"Denoising diffusion probabilistic models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.045983Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:35723530984d906b844c8f7bfe25e90af25fa4969ef69488828c7cb26cfa46ea","observation_id":"5012be85-6821-48c0-a233-217c1c672561","resolution":{"observed_at":"2026-08-12T18:38:40.045983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.03355","last_updated":"2025-03-02T07:45:09Z","snapshot_observed_at":"2026-08-16T13:12:37.517817Z","submitted_at":"2024-10-04T12:21:03Z","title":"LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.03355","snapshot_observed_at":"2026-08-12T18:38:40.054104Z","title":"Lantern: Accelerating visual autoregressive models with relaxed speculative decoding","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.054104Z"},"links":{"cited_paper":"/paper/2410.03355","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:d78719eae7e2503e92faf1d6f0721e4a7be13fc1e9964c23eea5ab9a71f8c046","observation_id":"57ffad67-6a14-4491-9939-98b240dffcc1","resolution":{"observed_at":"2026-08-12T18:38:40.054104Z","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":"2026-08-12T18:38:40.064740Z","title":"Speculative decoding with big little decoder","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.064740Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:ac12e44a90878afda3f18ecd38af64ce7e4480efde1b80615e41773cfb0b3070","observation_id":"9486d339-4efe-48be-be91-d0af105cf992","resolution":{"observed_at":"2026-08-12T18:38:40.064740Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00835","last_updated":"2024-06-13T08:41:28Z","snapshot_observed_at":"2026-08-16T14:14:22.648184Z","submitted_at":"2024-02-28T20:17:04Z","title":"CLLMs: Consistency Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.00835","snapshot_observed_at":"2026-08-12T18:38:40.073464Z","title":"Cllms: Consistency large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.073464Z"},"links":{"cited_paper":"/paper/2403.00835","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:929da74973cbff2f45b94852062bfea0e8c04b1ce7e63e3e858e9265eff48f8e","observation_id":"507527f4-9d90-4790-b50b-472c064980d0","resolution":{"observed_at":"2026-08-12T18:38:40.073464Z","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":"2026-08-12T18:38:40.120281Z","title":"Fast inference from transformers via speculative decoding","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.120281Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:f239170bade662be01655852d713ff5498cd3285fe4752307dd2793a2a980066","observation_id":"412d380d-6771-41a4-aa18-74b50794954d","resolution":{"observed_at":"2026-08-12T18:38:40.120281Z","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":"2026-08-12T18:38:42.263164Z","title":"Mage: Masked generative encoder to unify representation learning and image synthesis","venue":null,"work_id":"ef4f0c1d-a28b-4b80-b7ea-199361f72fc6","year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.129859Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:1d008e66cc966c8f420ee5d683e2d532ada90c09bc8f86afa86230ffd5092d1e","observation_id":"a68409da-e159-4d30-9b3e-d801e278797b","resolution":{"observed_at":"2026-08-12T18:38:42.270794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.11838","last_updated":"2024-11-01T14:45:36Z","snapshot_observed_at":"2026-08-16T13:42:07.461220Z","submitted_at":"2024-06-17T17:59:58Z","title":"Autoregressive Image Generation without Vector Quantization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.11838","snapshot_observed_at":"2026-08-12T18:38:40.139985Z","title":"Autoregressive image generation without vector quantization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.139985Z"},"links":{"cited_paper":"/paper/2406.11838","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:91d1d5dbb6080c20771966e2f14d96a366866f453c07207d08f8efb3b345ca06","observation_id":"8ef93f46-90cf-495e-9434-d09f46dafd4d","resolution":{"observed_at":"2026-08-12T18:38:40.139985Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.15077","last_updated":"2025-03-04T13:58:39Z","snapshot_observed_at":"2026-08-03T09:40:31.365295Z","submitted_at":"2024-01-26T18:59:01Z","title":"EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.15077","snapshot_observed_at":"2026-08-12T18:38:40.147873Z","title":"Eagle: Speculative sampling requires rethinking feature uncertainty","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.147873Z"},"links":{"cited_paper":"/paper/2401.15077","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:15abed51663f0dad6065e62333ddbcaf999df40c7978b1793a788a09c27d4073","observation_id":"17b7639e-2be5-4104-a366-48f5a2081be0","resolution":{"observed_at":"2026-08-12T18:38:40.147873Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.16858","last_updated":"2024-06-30T15:03:25Z","snapshot_observed_at":"2026-08-16T13:40:01.657235Z","submitted_at":"2024-06-24T17:59:11Z","title":"EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.16858","snapshot_observed_at":"2026-08-12T18:38:40.154167Z","title":"Eagle-2: Faster inference of language models with dynamic draft trees","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.154167Z"},"links":{"cited_paper":"/paper/2406.16858","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:f56464fafba0f67dd2255c5e5bd4701930f7bc759c83c6a6f448d14802e69cb2","observation_id":"2cbb9eeb-036f-47d7-a73e-baecaae03b05","resolution":{"observed_at":"2026-08-12T18:38:40.154167Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.02657","last_updated":"2025-04-24T16:16:27Z","snapshot_observed_at":"2026-08-16T13:28:23.779681Z","submitted_at":"2024-08-05T17:46:53Z","title":"Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.02657","snapshot_observed_at":"2026-08-12T18:38:40.166488Z","title":"Lumina-mgpt: Illuminate flexible photorealistic text-to-image generation with multimodal generative pretraining","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.166488Z"},"links":{"cited_paper":"/paper/2408.02657","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:aee9366049a6e40d6b7696ba2c374c9a0a79c89c58cf5b1b6e62ee8eb300f2e6","observation_id":"75412ecb-9e26-49f5-adc9-a0033df6ccd8","resolution":{"observed_at":"2026-08-12T18:38:40.166488Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07177","last_updated":"2024-06-10T01:36:31Z","snapshot_observed_at":"2026-08-16T14:53:13.373780Z","submitted_at":"2023-10-11T04:03:42Z","title":"Online Speculative Decoding","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07177","snapshot_observed_at":"2026-08-12T18:38:40.182734Z","title":"Online speculative decoding","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.182734Z"},"links":{"cited_paper":"/paper/2310.07177","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:0d4a1a8474d22dd6c7b830a14a89193d699691f3bdd39e044487614dd7ef1439","observation_id":"a8d2bc96-cf13-4089-a6df-9e12bb365bfd","resolution":{"observed_at":"2026-08-12T18:38:40.182734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.15505","last_updated":"2023-10-12T07:55:05Z","snapshot_observed_at":"2026-07-06T16:24:17.829828Z","submitted_at":"2023-09-27T09:13:40Z","title":"Finite Scalar Quantization: VQ-VAE Made Simple","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.15505","snapshot_observed_at":"2026-08-12T18:38:40.247127Z","title":"Finite scalar quantization: Vq-vae made simple","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.247127Z"},"links":{"cited_paper":"/paper/2309.15505","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:ea950b6802588e6966ab4f98f5f7dae59e8f97c405e3ac42823e6e517660487b","observation_id":"f6a9f1ac-81f2-45b6-ac88-c7d25aa0d46e","resolution":{"observed_at":"2026-08-12T18:38:40.247127Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.09781","last_updated":"2024-04-01T02:18:42Z","snapshot_observed_at":"2026-08-16T15:32:32.643405Z","submitted_at":"2023-05-16T20:12:59Z","title":"SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.09781","snapshot_observed_at":"2026-08-12T18:38:40.253429Z","title":"Specinfer: Accelerating generative large language model serving with tree-based speculative inference and verification","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.253429Z"},"links":{"cited_paper":"/paper/2305.09781","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:96d5bcbd379fa70081bccd7a96f83446f569cc99a34ca9f6fc57b5e60052d742","observation_id":"95f9d17b-52c0-4ddf-b64e-2190a531a5b1","resolution":{"observed_at":"2026-08-12T18:38:40.253429Z","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":"2026-08-12T18:38:42.174830Z","title":"Improved denoising diffusion probabilistic models","venue":null,"work_id":"20f543c5-fd33-488b-913f-0e003c7ed5c1","year":2021},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.260796Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:b9b40f7a67b4325ce9a16ebd45aacf397e1f894a7c7e77e070e9fdabef031ba9","observation_id":"01a4d74a-e4df-4ef9-a07a-9f34740feb6c","resolution":{"observed_at":"2026-08-12T18:38:42.231862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T18:38:40.271849Z","title":"Image transformer","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.271849Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:d97fc0ef021b655902d3f57e8fbf17c8ccba4edfae6c49e18e6c8669a3b82116","observation_id":"618b3fdb-68a4-4b96-b67a-9d444049828d","resolution":{"observed_at":"2026-08-12T18:38:40.271849Z","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":"2026-08-12T18:38:40.284159Z","title":"Zero-shot text-to-image generation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.284159Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:814e749f637322783ccee784637bf953f9401be9a7e00a343ccd10af9aa5abda","observation_id":"571eaf1a-2c7f-4208-9d85-e8c3cddc92cb","resolution":{"observed_at":"2026-08-12T18:38:40.284159Z","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":"2026-08-12T18:38:40.296799Z","title":"Improved techniques for training gans","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.296799Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:1fb5de7f358d61a312a17400aa6def14964f47ac14b2df29a83647aeb5ffd9b1","observation_id":"2da09fae-1d6b-4a6b-b693-c8c2806e70d1","resolution":{"observed_at":"2026-08-12T18:38:40.296799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10427","last_updated":"2023-05-17T17:57:34Z","snapshot_observed_at":"2026-08-16T15:32:15.157789Z","submitted_at":"2023-05-17T17:57:34Z","title":"Accelerating Transformer Inference for Translation via Parallel Decoding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10427","snapshot_observed_at":"2026-08-12T18:38:40.352953Z","title":"Accelerating transformer inference for translation via parallel decoding","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.352953Z"},"links":{"cited_paper":"/paper/2305.10427","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:7fb80aa6f281d1bbde09b44471fa7b3a73e5d78b089db619afba61c14c0e4064","observation_id":"3fdd15fd-f7eb-4174-8470-5edaee7de346","resolution":{"observed_at":"2026-08-12T18:38:40.352953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06525","last_updated":"2024-06-10T17:59:52Z","snapshot_observed_at":"2026-08-13T22:05:34.844117Z","submitted_at":"2024-06-10T17:59:52Z","title":"Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.06525","snapshot_observed_at":"2026-08-12T18:38:40.422871Z","title":"Autoregressive model beats diffusion: Llama for scalable image generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.422871Z"},"links":{"cited_paper":"/paper/2406.06525","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:0ec40498f8950ef17ae4d285077e1480dd9688f0790e442ae0bf7e83d523534c","observation_id":"7dccea71-e00b-4f72-a745-9135eae1fded","resolution":{"observed_at":"2026-08-12T18:38:40.422871Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10812","last_updated":"2024-10-14T17:59:42Z","snapshot_observed_at":"2026-08-16T13:09:29.086289Z","submitted_at":"2024-10-14T17:59:42Z","title":"HART: Efficient Visual Generation with Hybrid Autoregressive Transformer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.10812","snapshot_observed_at":"2026-08-12T18:38:40.438509Z","title":"Hart: Efficient visual generation with hybrid autoregressive transformer","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.438509Z"},"links":{"cited_paper":"/paper/2410.10812","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:561b0238d9cd10905453aa8a089b51cfdd2384787adddced75014d885917b939","observation_id":"e4690fc5-f4ef-483a-9827-57a01607c81a","resolution":{"observed_at":"2026-08-12T18:38:40.438509Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01699","last_updated":"2025-03-04T04:33:27Z","snapshot_observed_at":"2026-08-16T13:13:17.452400Z","submitted_at":"2024-10-02T16:05:27Z","title":"Accelerating Auto-regressive Text-to-Image Generation with Training-free Speculative Jacobi Decoding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01699","snapshot_observed_at":"2026-08-12T18:38:40.448816Z","title":"Accelerating auto-regressive text-to-image generation with training-free speculative jacobi decoding","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.448816Z"},"links":{"cited_paper":"/paper/2410.01699","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:641e023e604829ebad54162b33e7d5fa3198f17059ddaa465c1934d66438becb","observation_id":"05f7010d-db61-4eaf-9938-3d60296427c5","resolution":{"observed_at":"2026-08-12T18:38:40.448816Z","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":"2026-08-12T18:38:42.048270Z","title":"Visual autoregressive modeling: Scalable image generation via next-scale prediction","venue":null,"work_id":"8031400d-5fad-4350-9dc7-4b7d6fabdd26","year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.459664Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:5abb59de5f6cfadfe64c37c58ad60850731c743ce2679216af240e7fda04e865","observation_id":"78aebb47-4688-48ef-865a-ce1fc42afed2","resolution":{"observed_at":"2026-08-12T18:38:42.099657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T18:38:41.890938Z","title":"Givt: Generative infinite-vocabulary transformers","venue":null,"work_id":"aa542128-6ff4-46ad-bc21-2cbbece14985","year":2025},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.470517Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:18bb5840608ad0ec1bb1e1b55c55b4ee742c2a80c051bc9cf5f61071ef5ede16","observation_id":"706e3beb-316a-44b3-82a0-36a5d5ea18c9","resolution":{"observed_at":"2026-08-12T18:38:41.978466Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T18:38:40.483673Z","title":"Conditional image generation with pixelcnn decoders","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.483673Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:b6de345e05ef4962d54b1489a001deed7dc61eb51b2c650ceb8eedb2c1a4b316","observation_id":"70157210-219b-4396-977f-bc636fe8f5d4","resolution":{"observed_at":"2026-08-12T18:38:40.483673Z","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":"2026-08-12T18:38:40.489549Z","title":"Pixel recurrent neural networks","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.489549Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:12515a6f283866caaf040cee2f8dd5f1f9779e9e9386805cd4c34205ebf859c2","observation_id":"0d0c104b-198b-4f2a-9814-865e9b8bc4fc","resolution":{"observed_at":"2026-08-12T18:38:40.489549Z","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":"2026-08-12T18:38:40.495811Z","title":"Neural discrete representation learning","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.495811Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:c20cc41144ad2a5119f6f70512dbb2be5095f4a1e3680433b99b0ee55a3e113e","observation_id":"d71419af-46bd-438c-9a9d-46e8be21005b","resolution":{"observed_at":"2026-08-12T18:38:40.495811Z","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":"2026-08-12T18:38:41.795969Z","title":"Disco-diff: Enhancing continuous diffusion models with discrete latents","venue":null,"work_id":"af4d1b64-3ac2-453f-9cbc-771b90a281c9","year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.501232Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:003a21001d8be7944b31aef650f48deb0bd6ac5c3083465faae8ab584f894c72","observation_id":"4a40b8c9-952e-4fd6-a611-58a02f30b7c5","resolution":{"observed_at":"2026-08-12T18:38:41.811844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11809","last_updated":"2024-05-20T01:48:18Z","snapshot_observed_at":"2026-08-16T14:17:30.080588Z","submitted_at":"2024-02-19T03:39:10Z","title":"Generation Meets Verification: Accelerating Large Language Model Inference with Smart Parallel Auto-Correct Decoding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11809","snapshot_observed_at":"2026-08-12T18:38:40.513216Z","title":"Generation meets verification: Accelerating large language model inference with smart parallel auto-correct decoding","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.513216Z"},"links":{"cited_paper":"/paper/2402.11809","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:9408da891e0efb69608d12c7f21bf5a1b3f481c0218cf204b1b501b7ef207953","observation_id":"ba92f7c3-2526-4a01-8a3e-b6ff9d017a72","resolution":{"observed_at":"2026-08-12T18:38:40.513216Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.04627","last_updated":"2022-06-05T01:57:58Z","snapshot_observed_at":"2026-08-17T22:14:12.219954Z","submitted_at":"2021-10-09T18:36:00Z","title":"Vector-quantized Image Modeling with Improved VQGAN","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.04627","snapshot_observed_at":"2026-08-12T18:38:40.520756Z","title":"Vector-quantized image modeling with improved vqgan","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.520756Z"},"links":{"cited_paper":"/paper/2110.04627","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:c4e21e468f25f88fe49a06214f2f3cd6e96ff213d9e184c98007278dcb555842","observation_id":"96820ec6-521f-4a27-b89c-ca77b41be66c","resolution":{"observed_at":"2026-08-12T18:38:40.520756Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.10789","last_updated":"2022-06-22T01:11:29Z","snapshot_observed_at":"2026-08-14T02:29:38.306439Z","submitted_at":"2022-06-22T01:11:29Z","title":"Scaling Autoregressive Models for Content-Rich Text-to-Image Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.10789","snapshot_observed_at":"2026-08-12T18:38:40.595875Z","title":"Scaling autoregressive models for content-rich text-to-image generation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.595875Z"},"links":{"cited_paper":"/paper/2206.10789","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:65c5c82553e7abe4fb4bff9190cd3ac62d6394db914c00659d45d2d1a78c7891","observation_id":"59c54a90-f7d3-41d9-bc18-46f08b1785bd","resolution":{"observed_at":"2026-08-12T18:38:40.595875Z","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":"2026-08-12T18:38:41.774197Z","title":"Magvit: Masked generative video transformer","venue":null,"work_id":"7416b345-f1a9-4add-aebc-3af663d15665","year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.690569Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:f43cd0a0f0405d6f8026d5b8404aab56a5c46247cfbc2b741cd3727cc603b918","observation_id":"9c1f8e2c-9531-4300-9755-8b321d87fb93","resolution":{"observed_at":"2026-08-12T18:38:41.781658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.05737","last_updated":"2024-03-29T17:44:41Z","snapshot_observed_at":"2026-08-02T18:23:02.746177Z","submitted_at":"2023-10-09T14:10:29Z","title":"Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.05737","snapshot_observed_at":"2026-08-12T18:38:40.710619Z","title":"Language model beats diffusion--tokenizer is key to visual generation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.710619Z"},"links":{"cited_paper":"/paper/2310.05737","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:6badc1203bda5ed57b65e2dd48be3741b339133a2d332a75a67d945de4ea065a","observation_id":"1bc7354e-fef7-4814-b63a-dddc47b7df16","resolution":{"observed_at":"2026-08-12T18:38:40.710619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.00776","last_updated":"2024-11-01T17:59:58Z","snapshot_observed_at":"2026-08-16T13:03:42.693512Z","submitted_at":"2024-11-01T17:59:58Z","title":"Randomized Autoregressive Visual Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.00776","snapshot_observed_at":"2026-08-12T18:38:40.722246Z","title":"Randomized autoregressive visual generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.722246Z"},"links":{"cited_paper":"/paper/2411.00776","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:ea1d4d99b2418cf0afcb63843f79b7528c7fa2447845b0746294c0cc3477d62b","observation_id":"b4173788-a386-4702-aad5-8c8f5d60a162","resolution":{"observed_at":"2026-08-12T18:38:40.722246Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13720","last_updated":"2024-10-15T07:43:51Z","snapshot_observed_at":"2026-08-16T14:16:38.470776Z","submitted_at":"2024-02-21T11:31:28Z","title":"Ouroboros: Generating Longer Drafts Phrase by Phrase for Faster Speculative Decoding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13720","snapshot_observed_at":"2026-08-12T18:38:40.727981Z","title":"Ouroboros: Speculative decoding with large model enhanced drafting","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.727981Z"},"links":{"cited_paper":"/paper/2402.13720","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:a2509f961ca99dcd28ba2775ad8e074472525ae39a50cd30429cb7830b159863","observation_id":"6d7cc3d3-172e-438c-b5db-107910334d2f","resolution":{"observed_at":"2026-08-12T18:38:40.727981Z","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":"2026-08-12T18:38:41.721703Z","title":"Lookahead: An inference acceleration framework for large language model with lossless generation accuracy","venue":null,"work_id":"c04ba10e-0ab2-4d6e-aa35-51c13b1b2ddb","year":2024},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.735798Z"},"links":{"citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:0e2a51a9cbc85d328ee0068e55af087ee8c55afdef836e4a47724a6dd5c62e73","observation_id":"ca069b07-c3e7-41af-8d1c-fecf38cefbb2","resolution":{"observed_at":"2026-08-12T18:38:41.754763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08461","last_updated":"2024-03-31T03:06:51Z","snapshot_observed_at":"2026-08-16T14:52:38.095793Z","submitted_at":"2023-10-12T16:21:04Z","title":"DistillSpec: Improving Speculative Decoding via Knowledge Distillation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08461","snapshot_observed_at":"2026-08-12T18:38:40.745600Z","title":"Distillspec: Improving speculative decoding via knowledge distillation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation","version":3},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-12T18:38:40.745600Z"},"links":{"cited_paper":"/paper/2310.08461","citing_paper":"/paper/2411.11925"},"observation_digest":"sha256:e399c6c7f2b866b85d88c00433e2a4b7c4d3a21ef6f4ed59e70800a98b4ad0ee","observation_id":"404b26de-7ee0-4361-92a1-62b004223bc9","resolution":{"observed_at":"2026-08-12T18:38:40.745600Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.11925","last_updated":"2026-07-01T03:37:16Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T07:49:24.587874Z","submitted_at":"2024-11-18T09:19:15Z","title":"Continuous Speculative Decoding for Autoregressive Image Generation"},"reference_resolution":{"displayed":51,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":36,"verified_exact":0,"verified_fuzzy":15},"total_outbound_references":51},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 6 inbound Pith citation observations for arXiv:2411.11925."}