{"as_of":"2026-08-17T14:33:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:01c2dd2821c9d1416e7b80198780cd35f092edc37b96f2c2aa74785eb3add9ee","coverage":[{"denominator":293,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T00:18:29.941357Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2608.12276/citation-record","integrity":"/paper/2608.12276/integrity","json":"/paper/2608.12276/citation-record.json","paper":"/paper/2608.12276"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T00:18:28.456003Z","title":"ICLR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.456003Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:0947b05e471b019f0cb0919bd1d363f3244ec3658172b9fae37ac8e99b8fe060","observation_id":"ae7a894b-2ca8-449d-812e-e94cf0aea9ae","resolution":{"observed_at":"2026-08-16T00:18:28.456003Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.14389","last_updated":"2024-02-21T15:45:20Z","snapshot_observed_at":"2026-08-16T15:45:27.168056Z","submitted_at":"2023-03-25T07:47:21Z","title":"MDTv2: Masked Diffusion Transformer is a Strong Image Synthesizer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.14389","snapshot_observed_at":"2026-08-16T00:18:28.473516Z","title":"arXiv preprint arXiv:2303.14389 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.473516Z"},"links":{"cited_paper":"/paper/2303.14389","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:4ef2448a9f278238a850ec2ab51d6bdce1cc425511eb4c192597e8d32e6d11ff","observation_id":"c63acc0f-92c3-4626-ade5-ceaa74f2800f","resolution":{"observed_at":"2026-08-16T00:18:28.473516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16609","last_updated":"2023-09-28T17:07:49Z","snapshot_observed_at":"2026-08-09T21:25:20.369782Z","submitted_at":"2023-09-28T17:07:49Z","title":"Qwen Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16609","snapshot_observed_at":"2026-08-16T00:18:28.478744Z","title":"arXiv preprint arXiv:2309.16609 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.478744Z"},"links":{"cited_paper":"/paper/2309.16609","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:c20d4898d8327b1a7d6c4142f9b4e332f960943cfdfbac0dc62d684670aa4185","observation_id":"2b90d420-33e4-49ba-96e2-e93e873dded4","resolution":{"observed_at":"2026-08-16T00:18:28.478744Z","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":"2026-08-16T00:18:28.484454Z","title":"Journal of Machine Learning Research , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.484454Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:94afd4f098f4b50abb487ad3f35f532a8aac53b21663dc7d6948cf6aebbb8a53","observation_id":"509f9680-5356-4b24-9c42-e165699b165d","resolution":{"observed_at":"2026-08-16T00:18:28.484454Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-16T00:18:28.488773Z","title":"arXiv preprint arXiv:2312.11805 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.488773Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:46c7f8783b3304686693201af3fc49dee8daada0d9ff303b101685ff68741e70","observation_id":"a2d93bd2-880e-42de-bb13-b9be9b28d9f7","resolution":{"observed_at":"2026-08-16T00:18:28.488773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-16T00:18:28.493369Z","title":"arXiv preprint arXiv:2407.21783 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.493369Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:1590ea76c82790e34f3ec2ea4c0cc5850b8cc5963f7ff95f90cda005d934f900","observation_id":"faa4df9c-26ed-4ea9-a8bb-81488081d9dc","resolution":{"observed_at":"2026-08-16T00:18:28.493369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-16T00:18:28.498193Z","title":"arXiv preprint arXiv:2307.09288 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.498193Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:56d1a34ef283b93dfb5bae1ff397939a6d90bfccd2b9ad7e8c41b75c49624764","observation_id":"928e18ba-261f-440d-a126-1af9a5951919","resolution":{"observed_at":"2026-08-16T00:18:28.498193Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.04410","last_updated":"2025-02-09T08:59:19Z","snapshot_observed_at":"2026-08-16T13:20:41.485941Z","submitted_at":"2024-09-06T17:14:53Z","title":"Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.04410","snapshot_observed_at":"2026-08-16T00:18:28.503040Z","title":"arXiv preprint arXiv:2409.04410 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.503040Z"},"links":{"cited_paper":"/paper/2409.04410","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:68f8d08030fbe08e0009e0d52780376fe8e57ac5c9201a9252a9d8eff0124a00","observation_id":"a3d70d31-22c6-4f7d-880d-9b612783c871","resolution":{"observed_at":"2026-08-16T00:18:28.503040Z","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":"2026-08-16T00:18:28.507310Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.507310Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:1b0f75c9ca1671078cc3cd008922426cc3aca25a27b6566787fa47d673614790","observation_id":"eb909a2c-2d45-4e1f-9114-ec6f56c7fc38","resolution":{"observed_at":"2026-08-16T00:18:28.507310Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.11096","last_updated":"2019-02-25T21:32:06Z","snapshot_observed_at":"2026-07-06T07:04:57.275371Z","submitted_at":"2018-09-28T15:38:49Z","title":"Large Scale GAN Training for High Fidelity Natural Image Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.11096","snapshot_observed_at":"2026-08-16T00:18:28.511124Z","title":"arXiv preprint arXiv:1809.11096 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.511124Z"},"links":{"cited_paper":"/paper/1809.11096","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:dabe8943bc6973948648b1df042a37dfbf7e8b4d749185f05e334380f06a54c2","observation_id":"1ffa0eff-1adf-4711-8bc0-693dfeba00b5","resolution":{"observed_at":"2026-08-16T00:18:28.511124Z","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":"2026-08-16T00:18:28.515288Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.515288Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:f7b176607ebba84e969d3e78610969465af0346fb5641e5b279d76795c6471f2","observation_id":"9b7bd4d8-1800-42d6-bfdf-637d7632f6f8","resolution":{"observed_at":"2026-08-16T00:18:28.515288Z","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":"2026-08-16T00:18:28.539268Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.539268Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:5d98f74329a0ce0e27e0409f1210356ed19b38c6a0219232eb1d7813906c945b","observation_id":"2042bd8a-d498-4c2e-9b39-60ef1a212655","resolution":{"observed_at":"2026-08-16T00:18:28.539268Z","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":"2026-08-16T00:18:28.563061Z","title":"ECCV , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.563061Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:c5f91ac9895602936b385f83692da2ab447cc49a678de3f4d8668da2467c00aa","observation_id":"b2652670-4793-4b1b-b3b2-3e01d3b5dd29","resolution":{"observed_at":"2026-08-16T00:18:28.563061Z","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":"2026-08-16T00:18:28.599743Z","title":"ICCV , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.599743Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:ad48d2a504fe8b64603f96dd60fb3c5644daecd6027e6b59bd408139b84e3ebd","observation_id":"1571b0ee-3d9a-4079-99c8-25cc2f3f6470","resolution":{"observed_at":"2026-08-16T00:18:28.599743Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.00273","last_updated":"2022-01-02T02:18:10Z","snapshot_observed_at":"2026-08-16T17:30:45.799863Z","submitted_at":"2022-01-02T02:18:10Z","title":"Disorder in Andreev reflection of a quantum Hall edge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.00273","snapshot_observed_at":"2026-08-16T00:18:28.676279Z","title":"arXiv preprint arXiv:2201.00273 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.676279Z"},"links":{"cited_paper":"/paper/2201.00273","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:8f1a78e3f7199628cc20df5a5e5ea1b990534eb3e13921f13d4f9dec06e01709","observation_id":"0ee65f3a-6fd9-49cb-bc85-5bcb2ca716e7","resolution":{"observed_at":"2026-08-16T00:18:28.676279Z","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":"2026-08-16T00:18:28.764201Z","title":"Return of Unconditional Generation: A Self-supervised Representation Generation Method , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.764201Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:c27d5312310f0a0253933a78467230ab6e35e2932f76f982eca0194ba49f93af","observation_id":"d598f7c5-8946-4227-81b4-87e26c434e1c","resolution":{"observed_at":"2026-08-16T00:18:28.764201Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.13447","last_updated":"2025-05-19T17:59:42Z","snapshot_observed_at":"2026-08-17T11:34:19.285953Z","submitted_at":"2025-05-19T17:59:42Z","title":"Mean Flows for One-step Generative Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.13447","snapshot_observed_at":"2026-08-16T00:18:28.767973Z","title":"arXiv preprint arXiv:2505.13447 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.767973Z"},"links":{"cited_paper":"/paper/2505.13447","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:6fc08a7ce155ba33cda93ced009bb6d54964c2e297d4d9167593a33f0725f15c","observation_id":"d9234d8c-c048-4f22-b427-6df2d33f77ac","resolution":{"observed_at":"2026-08-16T00:18:28.767973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.23589","last_updated":"2025-06-30T07:51:58Z","snapshot_observed_at":"2026-08-11T16:25:47.851476Z","submitted_at":"2025-06-30T07:51:58Z","title":"Transition Matching: Scalable and Flexible Generative Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.23589","snapshot_observed_at":"2026-08-16T00:18:28.775943Z","title":"arXiv preprint arXiv:2506.23589 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.775943Z"},"links":{"cited_paper":"/paper/2506.23589","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:56f915d7352e331eb842f7f6aeff308e70fb8b32f33d0a7f18aa69c6a2454282","observation_id":"c74f1261-69d9-40b6-b0c2-f173c98bf5c6","resolution":{"observed_at":"2026-08-16T00:18:28.775943Z","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":"2026-08-16T00:18:28.780462Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.780462Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:6c826f88dc3eb2140a5a813da4c71af40ddf37405093b27ad0de562264da9d3f","observation_id":"6c015523-925c-4acc-b00a-2025465ec6a6","resolution":{"observed_at":"2026-08-16T00:18:28.780462Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.15571","last_updated":"2023-03-09T15:18:40Z","snapshot_observed_at":"2026-08-14T22:23:53.150627Z","submitted_at":"2022-09-30T16:30:31Z","title":"Building Normalizing Flows with Stochastic Interpolants","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.15571","snapshot_observed_at":"2026-08-16T00:18:28.785032Z","title":"arXiv preprint arXiv:2209.15571 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.785032Z"},"links":{"cited_paper":"/paper/2209.15571","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:8ace2be9fddc1c4cea00c083eb7161cec762f17144a7512f5be7b2d7547835b1","observation_id":"d5af6db2-ffad-4cb4-902a-a274d6bd18cf","resolution":{"observed_at":"2026-08-16T00:18:28.785032Z","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":"2026-08-16T00:18:28.788974Z","title":"ICML , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.788974Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:78d21f2ed7526fa82de0d790936f900fa9ab8194f830d55f6740fe694aa39655","observation_id":"efe64f62-8ed3-4634-b50e-63a2cbff0ec2","resolution":{"observed_at":"2026-08-16T00:18:28.788974Z","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":"2026-08-16T00:18:28.792590Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.792590Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:50fbe79259fa374207cf02028d5bb6ac4d4dc87ff0db7874f5f0d2b817cffcac","observation_id":"27508c57-9aa1-418e-b2ef-53dc0b8217b8","resolution":{"observed_at":"2026-08-16T00:18:28.792590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1607.06450","last_updated":"2016-07-21T19:57:52Z","snapshot_observed_at":"2026-08-15T04:53:45.483331Z","submitted_at":"2016-07-21T19:57:52Z","title":"Layer Normalization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1607.06450","snapshot_observed_at":"2026-08-16T00:18:28.795920Z","title":"arXiv preprint arXiv:1607.06450 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.795920Z"},"links":{"cited_paper":"/paper/1607.06450","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:2c29e306915e7aef84e9651ce54f3b20d641cc5cea74d243789d9175995bc95b","observation_id":"b28df356-0d4a-48d0-bc49-cfc2dce27f51","resolution":{"observed_at":"2026-08-16T00:18:28.795920Z","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":"2026-08-16T00:18:28.799575Z","title":"NeurIPS , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.799575Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:2a036c39206f329f4330f4551df7b0cc42a6abed5f6f3fee87ea40716356635f","observation_id":"0b6f9a9f-d791-4066-81dd-cc8bb2865e04","resolution":{"observed_at":"2026-08-16T00:18:28.799575Z","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":"2026-08-16T00:18:28.802757Z","title":"NeurIPS , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.802757Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:291d8c31e4e7bb42735ef887e4af84155721554195a1b233c60bec8acd5a45e9","observation_id":"f7ced0f6-f9af-491b-8a00-e0a33b30d5d5","resolution":{"observed_at":"2026-08-16T00:18:28.802757Z","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":"2026-08-16T00:18:28.806627Z","title":"NeurIPS , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.806627Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:a49c51884c1f95323807c1725be4b7bdd4f20a4532cbd566c631f8dd21a9fff0","observation_id":"1fc5205b-8d1c-43ea-82f7-5381f41bfa97","resolution":{"observed_at":"2026-08-16T00:18:28.806627Z","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":"2026-08-16T00:18:28.810742Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.810742Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:f0765e48cc30f9300cc0a035310d520b520ee4684b912efa8d5c4cb2e6a61888","observation_id":"6689daa9-6420-4a22-b78b-aa3f8075e5e1","resolution":{"observed_at":"2026-08-16T00:18:28.810742Z","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":"2026-08-16T00:18:28.814374Z","title":"arXiv preprint arXiv:2406.06525 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.814374Z"},"links":{"cited_paper":"/paper/2406.06525","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:524399e9b7b739d810f3286255d604297f24217607645344da7f9ccde1a2f5bd","observation_id":"3448985d-4932-48f4-b6c9-714e2cb1f507","resolution":{"observed_at":"2026-08-16T00:18:28.814374Z","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":"2026-08-16T00:18:28.818559Z","title":"NeurIPS , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.818559Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:b5b2984ef8d4aa50ad543c36f6083c4c2dfff92b34045a22bd5350cae8089e53","observation_id":"435b3d51-9819-4d71-997a-cbf97cd1f0f5","resolution":{"observed_at":"2026-08-16T00:18:28.818559Z","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":"2026-08-16T00:18:28.822872Z","title":"NeurIPS , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.822872Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:8dd9bd33b1019e0c7f3088a11f11d807b8c021744b56ff5c1c89189bb0906e61","observation_id":"14184933-fca1-44f1-a31e-0e232c6f0fac","resolution":{"observed_at":"2026-08-16T00:18:28.822872Z","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":"2026-08-16T00:18:28.826414Z","title":"Journal of Machine Learning Research , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.826414Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:a44d7d841aaf5040cf2dbb26ac47578ccde7c522c0332d3c28eb6804825cd210","observation_id":"d204a963-a574-40b2-84c6-88ecfabb0c54","resolution":{"observed_at":"2026-08-16T00:18:28.826414Z","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":"2026-08-16T00:18:28.829600Z","title":"Large-dit-imagenet , url=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.829600Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:9fc1886b89e9e8c4f26c9e29e2030fe6f1977f56b7896d635420849153673e2f","observation_id":"44bbe8ee-785d-4284-baba-ed05bb6cda17","resolution":{"observed_at":"2026-08-16T00:18:28.829600Z","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":"2026-08-16T00:18:28.833500Z","title":"arXiv preprint arXiv:2206.10789 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.833500Z"},"links":{"cited_paper":"/paper/2206.10789","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:dcaf55708c184eb4520355cc3b48fa7dc02489f5bfe39606cabffd6b83be9119","observation_id":"8a0c79b7-9be6-4b03-9420-afea6c8357ad","resolution":{"observed_at":"2026-08-16T00:18:28.833500Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-08-14T18:16:28.847993Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-16T00:18:28.893207Z","title":"arXiv preprint arXiv:1810.04805 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.893207Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:6dca53fbf30b2046a154fe4b46c98e30029c2a8cdef97ff11981e5ca4709a2e7","observation_id":"dfe52f0a-3c19-44cc-a5a0-afda194b46e5","resolution":{"observed_at":"2026-08-16T00:18:28.893207Z","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":"2026-08-16T00:18:28.975783Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:28.975783Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:8273cd57f25ad3642f09e4c6a8a6d9b2bcc6dfc4be7e7c6e1eb43cbae0d31455","observation_id":"34befc36-3a4c-4f10-9f6d-20ba1650afae","resolution":{"observed_at":"2026-08-16T00:18:28.975783Z","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":"2026-08-16T00:18:29.005040Z","title":"NeurIPS , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.005040Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:f6473625935d1b1c327d20a3891541680b6f876f5c9120ff1eb56ea19b0e95b9","observation_id":"20eb5ceb-87dd-427b-a4dc-9b62452aa60e","resolution":{"observed_at":"2026-08-16T00:18:29.005040Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00752","last_updated":"2024-05-31T17:55:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-01T18:01:34Z","title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00752","snapshot_observed_at":"2026-08-16T00:18:29.009048Z","title":"arXiv preprint arXiv:2312.00752 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.009048Z"},"links":{"cited_paper":"/paper/2312.00752","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:06151c8d6438010de466fc23d84b2b70531422a90615d1b0d4d7b97e82d73188","observation_id":"c0cf535e-446a-4f79-b98b-1e1b84fafa0b","resolution":{"observed_at":"2026-08-16T00:18:29.009048Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.21060","last_updated":"2024-05-31T17:50:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-05-31T17:50:01Z","title":"Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.21060","snapshot_observed_at":"2026-08-16T00:18:29.013098Z","title":"arXiv preprint arXiv:2405.21060 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.013098Z"},"links":{"cited_paper":"/paper/2405.21060","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:b9f75ada7e47a7325105faf56d1f1ab86fe0e724ed53d71bc4fb974357c02b65","observation_id":"ae5be7bb-ed60-412a-9065-929c9bf6c5df","resolution":{"observed_at":"2026-08-16T00:18:29.013098Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.09417","last_updated":"2024-11-14T02:00:33Z","snapshot_observed_at":"2026-08-14T11:12:31.002605Z","submitted_at":"2024-01-17T18:56:18Z","title":"Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.09417","snapshot_observed_at":"2026-08-16T00:18:29.016948Z","title":"arXiv preprint arXiv:2401.09417 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.016948Z"},"links":{"cited_paper":"/paper/2401.09417","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:118e77929c7a0a2e9140f8b0e2d116a657262bdb25d34bff2b9a1246688b821b","observation_id":"09e3fbd1-2c55-4e63-8f6b-008dd57662ed","resolution":{"observed_at":"2026-08-16T00:18:29.016948Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07537","last_updated":"2024-06-11T17:58:34Z","snapshot_observed_at":"2026-08-17T01:19:58.448727Z","submitted_at":"2024-06-11T17:58:34Z","title":"Autoregressive Pretraining with Mamba in Vision","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07537","snapshot_observed_at":"2026-08-16T00:18:29.021500Z","title":"arXiv preprint arXiv:2406.07537 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.021500Z"},"links":{"cited_paper":"/paper/2406.07537","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:b47d24ac6aa06bfac9331089f42705970928923474b2c0d42adc8651bd52a723","observation_id":"eb467768-e22c-42c1-b435-f51b9a65914c","resolution":{"observed_at":"2026-08-16T00:18:29.021500Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01159","last_updated":"2024-06-03T09:51:59Z","snapshot_observed_at":"2026-08-16T13:46:49.329986Z","submitted_at":"2024-06-03T09:51:59Z","title":"Dimba: Transformer-Mamba Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01159","snapshot_observed_at":"2026-08-16T00:18:29.025359Z","title":"arXiv preprint arXiv:2406.01159 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.025359Z"},"links":{"cited_paper":"/paper/2406.01159","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:e3e934ac94606d405a6ba924e273c4b6a9a892166e84152ffe599a515c582501","observation_id":"0d56c45b-373a-4236-948b-07a0a0d4f5ca","resolution":{"observed_at":"2026-08-16T00:18:29.025359Z","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":"2026-08-16T00:18:29.030244Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.030244Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:08faf082a50536eb854047153df343d315a99eda81f1a335368014da3885b2ca","observation_id":"70dae6f5-34a5-4149-b5f0-f9d655dfad19","resolution":{"observed_at":"2026-08-16T00:18:29.030244Z","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":"2026-08-16T00:18:29.034426Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.034426Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:77d163d3f82cc57fe6ca4bfd84de6c9704eaab18666662b5c22be324d08481c3","observation_id":"5cb83cac-2a5a-40ab-9b7e-fb4a1834950d","resolution":{"observed_at":"2026-08-16T00:18:29.034426Z","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":"2026-08-16T00:18:29.039443Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.039443Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:1e4a25f7077add754b141347988a0dfc967ed2b938752bfaa1589618400d48ea","observation_id":"3d0f1e2d-657d-4a4c-a44d-3ec8e5b64d00","resolution":{"observed_at":"2026-08-16T00:18:29.039443Z","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":"2026-08-16T00:18:29.044271Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.044271Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:0d9f1e26f478f76160b91a12c25c8a4877d5674e6c8c657b841aa30b243a2017","observation_id":"2405d889-2a8b-470d-ad29-1d7fcb945e1e","resolution":{"observed_at":"2026-08-16T00:18:29.044271Z","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":"2026-08-16T00:18:29.048152Z","title":"Neural computation , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.048152Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:f286bc8828b66bd8de2f6a25a2c3220918cb3be8f7a820f8743f03aba2221548","observation_id":"6f6fe7e4-0c92-4b1d-bedb-b54939b4fea1","resolution":{"observed_at":"2026-08-16T00:18:29.048152Z","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":"2026-08-16T00:18:29.052398Z","title":"arXiv preprint arXiv:2411.00776 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.052398Z"},"links":{"cited_paper":"/paper/2411.00776","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:53ca1ef006a8edcf911105f39aa3387a8be0ced5194350664915192114c08913","observation_id":"7dd1c9c9-d542-4e8c-b08f-c2c0c61bc234","resolution":{"observed_at":"2026-08-16T00:18:29.052398Z","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":"2026-08-16T21:20:27.257089Z","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":"2026-08-16T00:18:29.056475Z","title":"arXiv preprint arXiv:2110.04627 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.056475Z"},"links":{"cited_paper":"/paper/2110.04627","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:9993bee29a952fbebc57dc024435fbaf5ed2f840751409217bf29c40c7b4c0f9","observation_id":"d8c9527c-99fe-4ade-8a0d-835f1dd4e676","resolution":{"observed_at":"2026-08-16T00:18:29.056475Z","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":"2026-08-16T00:18:29.059771Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.059771Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:7b33ba7c0d672299d7d95dc56559ac16f3e9b037a2701cd52b328ff92271864d","observation_id":"5aa15114-c872-46cf-8f7b-0af03e50f561","resolution":{"observed_at":"2026-08-16T00:18:29.059771Z","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":"2026-08-16T00:18:29.063504Z","title":"2018 , howpublished=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.063504Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:6f38dd3f88175726ca57dbf5cb8e899e0f4a02c93975ef71321e951d8ea2fd17","observation_id":"3314cc77-eeb5-4ce7-8247-b5b9a7aedf0b","resolution":{"observed_at":"2026-08-16T00:18:29.063504Z","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":"2026-08-16T00:18:29.067770Z","title":"2020 , url=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.067770Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:f9d6cecf9539095357f5a42a67b1a4f8f799c753ec6737f06d12ee061353981c","observation_id":"4aca7c08-a9fb-4191-85a5-bd024e6f74dc","resolution":{"observed_at":"2026-08-16T00:18:29.067770Z","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":"2026-08-16T00:18:29.071669Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.071669Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:a6c785c3f7058b1122a3b188e00b43c5f9654d05c77549337f8f19a3b013a7bc","observation_id":"26b9000e-fe0e-4d51-8878-bb047c9482c7","resolution":{"observed_at":"2026-08-16T00:18:29.071669Z","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":"2026-08-16T00:18:29.075348Z","title":"2022 , howpublished =","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.075348Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:5f112afb4acdc3904ed596221892e34feb89741b28e61abcee6bb0ad10921f5a","observation_id":"d7c819f3-df6c-49ff-b1c5-33a7720dfdfe","resolution":{"observed_at":"2026-08-16T00:18:29.075348Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-17T09:58:46.058102Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-16T00:18:29.117764Z","title":"arXiv preprint arXiv:2303.08774 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.117764Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:52649731d260e3179b3cca6337b7b530ed49a7243f5d2565ec36f7df22991d2e","observation_id":"78120551-c619-4749-a8b9-3b282aef6543","resolution":{"observed_at":"2026-08-16T00:18:29.117764Z","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":"2026-08-16T00:18:29.221419Z","title":"Proceedings of the IEEE , volume=","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.221419Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:5ed546ebb101734cbf212e8594d9622caf38fda4097e002af9c2d0d0fa382f7e","observation_id":"501a74a1-60db-4381-8605-30e8d86092ae","resolution":{"observed_at":"2026-08-16T00:18:29.221419Z","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":"2026-08-16T00:18:29.292674Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.292674Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:0093fd1745d7d6c7f00b2332d00710c7b120bc397faebd1c2fb07b6ad13d61fc","observation_id":"206afeae-32e9-4529-b20c-15ebbfd3b2b8","resolution":{"observed_at":"2026-08-16T00:18:29.292674Z","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":"2026-08-16T00:18:29.296748Z","title":"arXiv preprint arXiv:2408.12245 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.296748Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:13dc02647aed18d5d5528802a3cef4b22f1c9176246ac2385a8f5b51e242101a","observation_id":"f93204bb-ba84-4060-8255-57bfcabf357a","resolution":{"observed_at":"2026-08-16T00:18:29.296748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.00396","last_updated":"2022-08-05T17:54:38Z","snapshot_observed_at":"2026-08-14T01:02:41.198730Z","submitted_at":"2021-10-31T03:32:18Z","title":"Efficiently Modeling Long Sequences with Structured State Spaces","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.00396","snapshot_observed_at":"2026-08-16T00:18:29.301546Z","title":"arXiv preprint arXiv:2111.00396 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.301546Z"},"links":{"cited_paper":"/paper/2111.00396","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:e36e46665165e702768b4a815e1407d7063fd50df01c3a805e795a94bfe85180","observation_id":"280ba9de-734f-48ad-a934-a2e904e4e438","resolution":{"observed_at":"2026-08-16T00:18:29.301546Z","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":"2026-08-16T00:18:29.306356Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.306356Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:7fa2d39611754b68c4e752aca879f4cfb9f261e9f2a4013a68da2f08840953c7","observation_id":"bdc1b419-a128-470c-add1-ff4339257003","resolution":{"observed_at":"2026-08-16T00:18:29.306356Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.13947","last_updated":"2022-07-02T17:58:04Z","snapshot_observed_at":"2026-08-16T16:50:15.793766Z","submitted_at":"2022-06-27T01:50:18Z","title":"Long Range Language Modeling via Gated State Spaces","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.13947","snapshot_observed_at":"2026-08-16T00:18:29.310336Z","title":"arXiv preprint arXiv:2206.13947 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.310336Z"},"links":{"cited_paper":"/paper/2206.13947","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:aee3323861f62fc63e572c463068b8a656856fcd2f6c0879168e20153cef608d","observation_id":"47319e62-a617-4405-a693-fa08c047d5bd","resolution":{"observed_at":"2026-08-16T00:18:29.310336Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.12037","last_updated":"2022-08-05T17:35:04Z","snapshot_observed_at":"2026-08-17T01:22:45.391090Z","submitted_at":"2022-06-24T02:24:41Z","title":"How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.12037","snapshot_observed_at":"2026-08-16T00:18:29.315247Z","title":"arXiv preprint arXiv:2206.12037 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.315247Z"},"links":{"cited_paper":"/paper/2206.12037","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:6b26c631999edb6fb35bbab1e453bf0c3a84a6aff0fcc76cebacce323f243ea7","observation_id":"71b784e7-905a-4b34-8a3e-5318563eb066","resolution":{"observed_at":"2026-08-16T00:18:29.315247Z","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":"2026-08-16T00:18:29.319039Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.319039Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:084ca10c91843e04b4e14f3af21dc368b8ff1c8e69ee724c7f4309120983eb79","observation_id":"6f80e33d-6e15-4100-96e6-ccababf3f677","resolution":{"observed_at":"2026-08-16T00:18:29.319039Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.16211","last_updated":"2024-12-08T19:55:36Z","snapshot_observed_at":"2026-08-16T13:15:48.133270Z","submitted_at":"2024-09-24T16:12:12Z","title":"MaskBit: Embedding-free Image Generation via Bit Tokens","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.16211","snapshot_observed_at":"2026-08-16T00:18:29.322865Z","title":"arXiv preprint arXiv:2409.16211 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.322865Z"},"links":{"cited_paper":"/paper/2409.16211","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:df808cd531b18f4c5af5485b5b6a04c9376c8a5a57cfbac8bc704f4119067087","observation_id":"cf77b03d-0187-4d44-9fde-b398aa542877","resolution":{"observed_at":"2026-08-16T00:18:29.322865Z","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":"2026-08-16T00:18:29.327255Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.327255Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:670b487e855ad6d74a6a3cce928fe7a41eda520f454c82eaa187671b8083252c","observation_id":"393cfc63-53ab-431c-bba9-f7580a73b53a","resolution":{"observed_at":"2026-08-16T00:18:29.327255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15119","last_updated":"2025-04-03T02:34:24Z","snapshot_observed_at":"2026-08-16T08:29:08.547642Z","submitted_at":"2024-12-19T17:59:54Z","title":"Parallelized Autoregressive Visual Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15119","snapshot_observed_at":"2026-08-16T00:18:29.331175Z","title":"arXiv preprint arXiv:2412.15119 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.331175Z"},"links":{"cited_paper":"/paper/2412.15119","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:abad0a144054d955d5e57b57201cf8539fbfd6458cf9443a43f2119a4665ea8f","observation_id":"9df297d6-28bf-43d8-993d-bdfd5803cb5f","resolution":{"observed_at":"2026-08-16T00:18:29.331175Z","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":"2026-08-16T00:18:29.334902Z","title":"and Ermon, Stefano and Rudra, Atri and R","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.334902Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:34094b74ae0b1fafae42934beb3c55b4e553a316f1b5f96e8308082bd4c82fc8","observation_id":"7fc783a5-5071-4fc6-a3a8-54f38fc58260","resolution":{"observed_at":"2026-08-16T00:18:29.334902Z","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":"2026-08-16T00:18:29.338642Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.338642Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:35e2df63b83efc817c19dd2c648e3cdf21a7e43fff111ceecc48b7b1702a8a22","observation_id":"58b8013b-2732-48de-8512-4a154975c323","resolution":{"observed_at":"2026-08-16T00:18:29.338642Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-16T00:18:29.396792Z","title":"arXiv preprint arXiv:2302.13971 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.396792Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:6f2f251e49a32275c83ff7afe7235f17fac6ebda7048d9f4c89674fc849c507e","observation_id":"57363b52-a683-4df5-907e-7b3460d37e33","resolution":{"observed_at":"2026-08-16T00:18:29.396792Z","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":"2026-08-16T00:18:29.462117Z","title":"International Conference on Artificial Intelligence and Statistics , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.462117Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:a6f10149611dd1a8f5de96813b9f66dedf25e7b2f751e3a4a74c94cb0fcfb3aa","observation_id":"d942c78c-9049-4fd5-b536-e37a15d15444","resolution":{"observed_at":"2026-08-16T00:18:29.462117Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.06758","last_updated":"2019-02-26T09:06:47Z","snapshot_observed_at":"2026-08-16T17:55:08.620986Z","submitted_at":"2018-10-16T00:06:54Z","title":"Discriminator Rejection Sampling","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.06758","snapshot_observed_at":"2026-08-16T00:18:29.466158Z","title":"arXiv preprint arXiv:1810.06758 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.466158Z"},"links":{"cited_paper":"/paper/1810.06758","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:65aa2b68a90d687433630a4e265666ed965fe4258215963a07653ae5c4ed14af","observation_id":"6b7ec73f-4fed-4606-96dd-c46391d848ef","resolution":{"observed_at":"2026-08-16T00:18:29.466158Z","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":"2026-08-16T00:18:29.471253Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.471253Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:88739bf5ea18687ea3f486ee69afbe3eac6a93dc792de962063c2db5c55f8897","observation_id":"d69d7c4f-8c30-4cbe-a485-b88502a7df90","resolution":{"observed_at":"2026-08-16T00:18:29.471253Z","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":"2026-08-16T00:18:29.475684Z","title":"NeurIPS , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.475684Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:4875363e303ca8b0046912f3d5a99ee038b37733c238c719becbc25f5424434c","observation_id":"2d04fc78-55bc-4cb4-9450-ef959d51de5f","resolution":{"observed_at":"2026-08-16T00:18:29.475684Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-08-11T15:38:14.931716Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-16T00:18:29.480256Z","title":"arXiv preprint arXiv:2010.02502 , year=","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.480256Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:6d89ce78a18f3e12867d1b779e0a0d26bcf178cca9d28f34e490f1921178aa1f","observation_id":"0b501c37-b3b1-49d3-9527-e760b892b5fa","resolution":{"observed_at":"2026-08-16T00:18:29.480256Z","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":"2026-08-16T00:18:29.486233Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.486233Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:9783023f9242dbc09739e1a7dafeb6e50834f49f2af873774ded151357b227c6","observation_id":"8f740279-487d-4e15-897b-3d3ba9241f85","resolution":{"observed_at":"2026-08-16T00:18:29.486233Z","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":"2026-08-16T00:18:29.526484Z","title":"ICML , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.526484Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:5fce16ec217fcf0a383c0482b209aa2a8f538dac240d948c40874f82e2801548","observation_id":"89e9c131-4e14-48a2-9f3e-3f58bd473645","resolution":{"observed_at":"2026-08-16T00:18:29.526484Z","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":"2026-08-16T00:18:29.570513Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.570513Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:6914fe44a2d74e826ebdb27921aae604bc8ea9139c4e8af9a6e51a6eafca5542","observation_id":"7a2546bf-5597-40c4-a393-0106314ac3de","resolution":{"observed_at":"2026-08-16T00:18:29.570513Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.16280","last_updated":"2024-09-24T17:51:04Z","snapshot_observed_at":"2026-08-16T13:15:46.020505Z","submitted_at":"2024-09-24T17:51:04Z","title":"MonoFormer: One Transformer for Both Diffusion and Autoregression","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.16280","snapshot_observed_at":"2026-08-16T00:18:29.613783Z","title":"arXiv preprint arXiv:2409.16280 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.613783Z"},"links":{"cited_paper":"/paper/2409.16280","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:2940c4f751048b49fb0999b998abf27385ddfbfc71a8b5662a97901f5216b051","observation_id":"3f45680d-a785-4969-995c-b1a2d5af13ca","resolution":{"observed_at":"2026-08-16T00:18:29.613783Z","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":"2026-08-16T00:18:29.618474Z","title":"ICLR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.618474Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:430b587f42d7dee82825d0665955ae74029f53f42ae890b0ed6168c0eaf1f963","observation_id":"07058ce1-9d23-4cbb-be42-d132e0fb4554","resolution":{"observed_at":"2026-08-16T00:18:29.618474Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12095","last_updated":"2024-12-17T18:45:55Z","snapshot_observed_at":"2026-08-16T04:54:08.902738Z","submitted_at":"2024-12-16T18:59:29Z","title":"Causal Diffusion Transformers for Generative Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.12095","snapshot_observed_at":"2026-08-16T00:18:29.622519Z","title":"arXiv preprint arXiv:2412.12095 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.622519Z"},"links":{"cited_paper":"/paper/2412.12095","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:eefbcaca754de121f58d8e270e35f30c99f56a61f5fb599532d03e6042337b27","observation_id":"9bb8db5c-2e5a-438f-9886-280925bbeeed","resolution":{"observed_at":"2026-08-16T00:18:29.622519Z","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":"2026-08-16T00:18:29.626870Z","title":"ECCV , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.626870Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:48c7164bbab2a8aceac7b25ddd13994ac19399aad2f3c8ce9cc6a26fec22ae0f","observation_id":"80c73408-bda4-44a6-8007-2e211e27ecce","resolution":{"observed_at":"2026-08-16T00:18:29.626870Z","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":"2026-08-16T00:18:29.630929Z","title":"MICCAI , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.630929Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:715d94c7390e1f22bf41522542637c64e881ea272cc4daa436dd8d1a91442dcb","observation_id":"0e5c7cda-c69e-4372-ad07-672e4c8ec00f","resolution":{"observed_at":"2026-08-16T00:18:29.630929Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10733","last_updated":"2025-05-18T21:17:22Z","snapshot_observed_at":"2026-08-16T13:09:31.280702Z","submitted_at":"2024-10-14T17:15:07Z","title":"Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models","version":8},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.10733","snapshot_observed_at":"2026-08-16T00:18:29.634701Z","title":"arXiv preprint arXiv:2410.10733 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.634701Z"},"links":{"cited_paper":"/paper/2410.10733","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:4c3a672a0a7820b6afd8456c167c7a663f5a0ebe8ececef1a9da185aefd442f3","observation_id":"7bc6196f-ddbb-4034-aed4-3936a875fd3c","resolution":{"observed_at":"2026-08-16T00:18:29.634701Z","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":"2026-08-16T00:18:29.639064Z","title":"Proceedings of Machine Learning and Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.639064Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:8d22aac19a6075fd71b61e514862c80daa71e8bdebe58e07421c94aab63baed2","observation_id":"f8d90475-aa67-4be3-8df4-c3e9eb2cca18","resolution":{"observed_at":"2026-08-16T00:18:29.639064Z","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":"2026-08-16T00:18:29.642779Z","title":"2002 , publisher=","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.642779Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:cf93e61caa7b04b92bee2bb9a42a628141d9c1f863ed34cfc3095ed984dd51c0","observation_id":"5663f742-a6a3-49fb-9c7f-91226002f6cd","resolution":{"observed_at":"2026-08-16T00:18:29.642779Z","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":"2026-08-16T00:18:29.647990Z","title":"NeurIPS , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.647990Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:d0fb5bec13e1fc26fed9c9552c0b471b0698eb80ba37931b34f30c6424b68036","observation_id":"d0810b2e-97c9-4f0a-a459-44333a8a420b","resolution":{"observed_at":"2026-08-16T00:18:29.647990Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.16061","last_updated":"2020-10-11T02:15:11Z","snapshot_observed_at":"2026-08-16T19:14:25.354526Z","submitted_at":"2020-10-11T02:15:11Z","title":"Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.16061","snapshot_observed_at":"2026-08-16T00:18:29.651698Z","title":"arXiv preprint arXiv:2010.16061 , year=","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":87,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.651698Z"},"links":{"cited_paper":"/paper/2010.16061","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:79a6d59ccce6fb3bfbe16238a8f81f78fd32f5485636e52c98fdff554ed6e1cc","observation_id":"1b739a28-e5d2-4f43-a1a9-94885e060fc3","resolution":{"observed_at":"2026-08-16T00:18:29.651698Z","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":"2026-08-16T00:18:29.655232Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.655232Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:6c2bc31ccc1bb9d7d7e4306507486520c1b768e5eec1c271ca91ac9d10c19fcd","observation_id":"555acbd6-cdb7-4ea1-8cd2-f67580410e5a","resolution":{"observed_at":"2026-08-16T00:18:29.655232Z","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":"2026-08-16T00:18:29.745945Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.745945Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:427ca3d04c13c48d2be419ed2a589d5b456f436ef43a73a3ac6b4ed25a75021c","observation_id":"1c55581a-c32a-4690-a494-50a0592c16c0","resolution":{"observed_at":"2026-08-16T00:18:29.745945Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.19324","last_updated":"2025-03-22T19:42:20Z","snapshot_observed_at":"2026-08-16T13:06:02.643386Z","submitted_at":"2024-10-25T06:20:06Z","title":"Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.19324","snapshot_observed_at":"2026-08-16T00:18:29.799380Z","title":"arXiv preprint arXiv:2410.19324 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.799380Z"},"links":{"cited_paper":"/paper/2410.19324","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:5aa9d64a70faf74487c363703019e611a5de10104987694b2b7d6eb9032ad0cc","observation_id":"69c618fc-42e7-446e-a049-0ffec0bd4bdc","resolution":{"observed_at":"2026-08-16T00:18:29.799380Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.06940","last_updated":"2025-06-18T04:35:42Z","snapshot_observed_at":"2026-07-06T19:30:26.233621Z","submitted_at":"2024-10-09T14:34:53Z","title":"Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.06940","snapshot_observed_at":"2026-08-16T00:18:29.803412Z","title":"arXiv preprint arXiv:2410.06940 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":91,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.803412Z"},"links":{"cited_paper":"/paper/2410.06940","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:617af5008d97c9936477946af532be081f6bb6eee1ffc1615ae61153d4bd3ba3","observation_id":"1629ab7f-faec-4ccc-855b-d9d43f81c017","resolution":{"observed_at":"2026-08-16T00:18:29.803412Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.01423","last_updated":"2025-03-10T11:43:42Z","snapshot_observed_at":"2026-08-15T15:57:30.372623Z","submitted_at":"2025-01-02T18:59:40Z","title":"Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.01423","snapshot_observed_at":"2026-08-16T00:18:29.808278Z","title":"Generation: Taming Optimization Dilemma in Latent Diffusion Models , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.808278Z"},"links":{"cited_paper":"/paper/2501.01423","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:42118140b139c6684f911e80b48e3028c83cff3ac857cd12a2486c63dc7a6301","observation_id":"299aafc6-be85-449a-aa3a-071e93332035","resolution":{"observed_at":"2026-08-16T00:18:29.808278Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07724","last_updated":"2024-11-06T14:29:36Z","snapshot_observed_at":"2026-08-16T14:01:46.140668Z","submitted_at":"2024-04-11T13:16:47Z","title":"Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07724","snapshot_observed_at":"2026-08-16T00:18:29.812667Z","title":"arXiv preprint arXiv:2404.07724 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":93,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.812667Z"},"links":{"cited_paper":"/paper/2404.07724","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:11c152242234e360e32274b7e21d66a2ccca52895dbe7a0bd2851ac015099f28","observation_id":"58b9dccb-01a1-4550-ab60-af422db73e26","resolution":{"observed_at":"2026-08-16T00:18:29.812667Z","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":"2026-08-16T00:18:29.912329Z","title":"ICCV , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":94,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.912329Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:34f131e2faec0e0dc3fbbf1ae6fde669f1473f50a039f17491c39d7418842aa4","observation_id":"ab8a5693-e725-4f9d-87df-4302b29e93c7","resolution":{"observed_at":"2026-08-16T00:18:29.912329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-17T13:03:40.359628Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-16T00:18:29.916417Z","title":"arXiv preprint arXiv:2304.07193 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":95,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.916417Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:43da7f46bc9fa72b6744e40731258abc426a3bfbddd145a71035f2016d3a8299","observation_id":"648619f1-ab95-45b5-84a9-24ef16b52159","resolution":{"observed_at":"2026-08-16T00:18:29.916417Z","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":"2026-08-16T00:18:29.921242Z","title":"ICML , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.921242Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:f37770bde6476ad553e2eb6b70640ab9f9961d03daf576a646dd298066bd1981","observation_id":"72569ace-1ae2-401d-a4b3-c30c67dd0731","resolution":{"observed_at":"2026-08-16T00:18:29.921242Z","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":"2026-08-16T00:18:29.924977Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":97,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.924977Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:d12adfb25eb0739416982a3b9ee971af2c5e718ce4bb70fe3da60afd5d48e296","observation_id":"49d31b32-b6f8-4c6b-add5-26564605184a","resolution":{"observed_at":"2026-08-16T00:18:29.924977Z","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":"2026-08-16T00:18:29.929173Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":98,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.929173Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:ec2e322202c28a5bdb3659a9b1c2324d4bc24b3458fa31a4767ce68fe506b2b5","observation_id":"fecac4af-7170-40f9-b198-f58c7e227285","resolution":{"observed_at":"2026-08-16T00:18:29.929173Z","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":"2026-08-16T00:18:29.933499Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":99,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.933499Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:c29ea9f382d14aaa3c98e4d2c6b2188243952ece9fbf4f9fd5e7ffbc88dbf868","observation_id":"0d3de23d-3765-4046-a369-a7b0711b2cd9","resolution":{"observed_at":"2026-08-16T00:18:29.933499Z","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":"2026-08-16T00:18:29.937674Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":100,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.937674Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:9c4e38a8438cdc514e5ce8effc6db0ece6b3600a8df12150770957b038fc0548","observation_id":"8327ddd5-1575-43a1-981a-4b60c9bbc248","resolution":{"observed_at":"2026-08-16T00:18:29.937674Z","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":"2026-08-16T00:18:29.941357Z","title":"CVPR , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling","version":2},"reference_index":101,"source":"arxiv_source","source_observed_at":"2026-08-16T00:18:29.941357Z"},"links":{"citing_paper":"/paper/2608.12276"},"observation_digest":"sha256:1a5e8c8007cc42f11ce0ee532d59d92f4b469ea7eacac0c7bf9ac2c1845ec12d","observation_id":"ec114d58-d2e3-4e08-8ada-3b17f7b379f8","resolution":{"observed_at":"2026-08-16T00:18:29.941357Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.12276","last_updated":"2026-08-13T07:13:58Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T23:10:08.269509Z","submitted_at":"2026-08-12T17:15:42Z","title":"XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":100,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":293},"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 100 of 293 outbound references and 0 inbound Pith citation observations for arXiv:2608.12276."}