{"as_of":"2026-08-10T09:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e5d793f7bf69e89ab4a26cf997e70f26ca6627fe3c27fd506cf8d3f3a6159edc","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":13,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T15:29:27.574955Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T01:07:29.868540Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-08-09T15:29:27.574955Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.01416","last_updated":"2025-08-16T08:29:31Z","snapshot_observed_at":"2026-08-10T06:55:53.637300Z","submitted_at":"2025-02-03T14:55:28Z","title":"Categorical Schr\\\"odinger Bridge Matching","version":4},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-09T15:29:27.574955Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2502.01416"},"observation_digest":"sha256:e0157304dbd83d66e84a54aec9f66f5808e0a7612b83bd8dfcd3c141ec2e3e3d","observation_id":"1a85574d-7b9c-42c4-acfc-3bfb75e0996f","resolution":{"observed_at":"2026-08-09T15:29:27.574955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-08-08T14:30:26.579065Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.06768","last_updated":"2025-08-19T23:35:57Z","snapshot_observed_at":"2026-08-09T09:47:58.662011Z","submitted_at":"2025-02-10T18:47:21Z","title":"Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T14:30:26.579065Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2502.06768"},"observation_digest":"sha256:e22d1cf75e8cfe1f45e3234cdef72cdd10b37379186edebd15020aa2336ec6ea","observation_id":"8c43c252-643c-4c56-9e67-9cc13f14db8b","resolution":{"observed_at":"2026-08-08T14:30:26.579065Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-08-08T17:10:39.767786Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06901","last_updated":"2025-02-09T20:02:05Z","snapshot_observed_at":"2026-08-09T13:14:38.685381Z","submitted_at":"2025-02-09T20:02:05Z","title":"Enabling Autoregressive Models to Fill In Masked Tokens","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-08T17:10:39.767786Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2502.06901"},"observation_digest":"sha256:3cc024e2dbe57db0a7a4c081fde3eca434daaa0a9d38c5c04c7985f21fb0345e","observation_id":"5de9f587-e63d-415a-8319-08328890cb91","resolution":{"observed_at":"2026-08-08T17:10:39.767786Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":"2410.01949","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-07-03T01:07:29.868540Z","title":"Discrete copula diffusion","venue":null,"work_id":"0c991ec3-ee66-4039-8d3e-62fead3b60fd","year":2024},"citing_paper":{"arxiv_id":"2505.17384","last_updated":"2026-04-14T11:59:44Z","snapshot_observed_at":"2026-07-31T16:20:27.798904Z","submitted_at":"2025-05-23T01:45:47Z","title":"Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-19T14:20:49.548475Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2505.17384"},"observation_digest":"sha256:3f94ecc282a30bb0056ed5e7db6f93ab8b6d3be704f2eed4f1d4849a72c4abde","observation_id":"36f7f940-f0bb-4e4f-b1e2-a69034782336","resolution":{"observed_at":"2026-05-19T14:22:23.846791Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-08-07T14:22:21.919608Z","title":"Discrete copula diffusion","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.19089","last_updated":"2025-05-25T10:57:35Z","snapshot_observed_at":"2026-08-07T22:16:50.088839Z","submitted_at":"2025-05-25T10:57:35Z","title":"Plug-and-Play Context Feature Reuse for Efficient Masked Generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T14:22:21.919608Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2505.19089"},"observation_digest":"sha256:a7d8af1811d67a2b4c8112c8e4a802142821ac764681104522b0a7c6a6c1e2b4","observation_id":"ebd10694-5bfd-499c-918e-2d38c0357b32","resolution":{"observed_at":"2026-08-07T14:22:21.919608Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":"2410.01949","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-07-03T01:07:29.868540Z","title":"Discrete copula diffusion","venue":null,"work_id":"0c991ec3-ee66-4039-8d3e-62fead3b60fd","year":2024},"citing_paper":{"arxiv_id":"2505.22618","last_updated":"2025-07-03T04:51:05Z","snapshot_observed_at":"2026-07-06T21:32:23.537939Z","submitted_at":"2025-05-28T17:39:15Z","title":"Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-16T04:28:02.231373Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2505.22618"},"observation_digest":"sha256:54de9240536162373d75d7b9db8c6c08711f05b40d96da027c161d6278953535","observation_id":"887112ce-c74e-46c3-b185-1c147adf9719","resolution":{"observed_at":"2026-05-16T04:28:02.365726Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-08-07T12:12:29.271327Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.00290","last_updated":"2025-05-30T22:42:23Z","snapshot_observed_at":"2026-08-07T23:07:24.814063Z","submitted_at":"2025-05-30T22:42:23Z","title":"DLM-One: Diffusion Language Models for One-Step Sequence Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T12:12:29.271327Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2506.00290"},"observation_digest":"sha256:de3407e5d85c24dd9b4b862397c34abfbbf61e192208965b725d9d921a83bbfa","observation_id":"c0244614-9e58-4881-a0d8-89a9001b271b","resolution":{"observed_at":"2026-08-07T12:12:29.271327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":"2410.01949","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-07-03T01:07:29.868540Z","title":"Discrete copula diffusion","venue":null,"work_id":"0c991ec3-ee66-4039-8d3e-62fead3b60fd","year":2024},"citing_paper":{"arxiv_id":"2509.19707","last_updated":"2026-05-19T14:33:26Z","snapshot_observed_at":"2026-07-06T22:30:36.671861Z","submitted_at":"2025-09-24T02:33:29Z","title":"Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-05-21T21:51:41.885012Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2509.19707"},"observation_digest":"sha256:9f73c796507221de4c2844cb3132eb0550c91885a18c250bdf1e6ec0a9b94133","observation_id":"a507843f-6900-48b5-bc56-2683ec0a9b7b","resolution":{"observed_at":"2026-05-21T21:54:22.911471Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-08-04T13:15:31.725312Z","title":"Discrete copula diffusion","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.01384","last_updated":"2026-05-22T19:48:31Z","snapshot_observed_at":"2026-08-09T16:34:10.718069Z","submitted_at":"2025-10-01T19:15:25Z","title":"Fine-Tuning Masked Diffusion for Provable Self-Correction","version":4},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T13:15:31.725312Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2510.01384"},"observation_digest":"sha256:d1542b0964271bcbdc3a6530b6145bf8961f19d5efd7c6dd63d3736b0abbdc85","observation_id":"e099e0fb-d202-403a-982b-7e2f971de2c2","resolution":{"observed_at":"2026-08-04T13:15:31.725312Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-08-02T17:49:53.702696Z","title":"Discrete copula diffusion","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.22216","last_updated":"2026-07-23T16:32:10Z","snapshot_observed_at":"2026-08-09T02:33:41.982497Z","submitted_at":"2026-03-23T17:13:22Z","title":"Gumbel Distillation for Parallel Text Generation","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-02T17:49:53.702696Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2603.22216"},"observation_digest":"sha256:dea4caa7c0a3f797a639cf30ab32120d4bab2fe3e7d75e9276fd23c111ad6765","observation_id":"4da25fce-245c-4068-8af3-90535d941606","resolution":{"observed_at":"2026-08-02T17:49:53.702696Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":"2410.01949","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-07-03T01:07:29.868540Z","title":"Discrete copula diffusion","venue":null,"work_id":"0c991ec3-ee66-4039-8d3e-62fead3b60fd","year":2024},"citing_paper":{"arxiv_id":"2606.02955","last_updated":"2026-06-01T23:18:59Z","snapshot_observed_at":"2026-08-07T04:11:40.526950Z","submitted_at":"2026-06-01T23:18:59Z","title":"Fast-dLLM++: Fr\\'{e}chet Profile Decoding for Faster Diffusion LLM Inference","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-06-28T14:10:24.931859Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2606.02955"},"observation_digest":"sha256:92451aa9b7e337c2ed701e6b2a5b6f29f859aa2346f0cca9f7d51108999af0da","observation_id":"d107a51b-6cb2-4507-9461-47572288a061","resolution":{"observed_at":"2026-07-01T23:36:23.345457Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":"2410.01949","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-07-03T01:07:29.868540Z","title":"Discrete copula diffusion","venue":null,"work_id":"0c991ec3-ee66-4039-8d3e-62fead3b60fd","year":2024},"citing_paper":{"arxiv_id":"2606.09159","last_updated":"2026-06-08T07:50:12Z","snapshot_observed_at":"2026-08-06T04:24:09.944512Z","submitted_at":"2026-06-08T07:50:12Z","title":"Unified Energy for Invariant and Independent Decoding in Diffusion Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-27T16:51:04.460958Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2606.09159"},"observation_digest":"sha256:8878f209796519e0444a034a1be52f23fdb93362090cafb6a3b33dd51cf59f6e","observation_id":"91b06dd6-649b-4eda-8dbb-ed87e38a1f2b","resolution":{"observed_at":"2026-07-03T01:07:29.870345Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01949","snapshot_observed_at":"2026-08-01T20:54:02.144962Z","title":"https://arxiv.org/pdf/2410.01949","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16528","last_updated":"2026-07-17T22:09:01Z","snapshot_observed_at":"2026-08-07T07:19:10.753414Z","submitted_at":"2026-07-17T22:09:01Z","title":"Hierarchical Domain Generalization","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-01T20:54:02.144962Z"},"links":{"cited_paper":"/paper/2410.01949","citing_paper":"/paper/2607.16528"},"observation_digest":"sha256:7a242d14c86b64c22da9b51e5df515c3db0a6e6f6c544b085ce6e6d1dc3cb99a","observation_id":"f1ebbd1d-f588-4353-ab0b-faf3a76107c7","resolution":{"observed_at":"2026-08-01T20:54:02.144962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.01949/citation-record","integrity":"/paper/2410.01949/integrity","json":"/paper/2410.01949/citation-record.json","paper":"/paper/2410.01949"},"outbound":[],"paper":{"arxiv_id":"2410.01949","last_updated":"2025-03-19T08:34:29Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T07:06:17.534336Z","submitted_at":"2024-10-02T18:51:38Z","title":"Discrete Copula Diffusion"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2410.01949."}