{"as_of":"2026-08-18T11:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2f723e8d9bc3eae5fc8a4f8d83fd205c5984571f664566d64dcfc50529c4abb6","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T21:21:22.475887Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T05:01:17.254510Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.15811","last_updated":"2024-07-22T17:23:28Z","snapshot_observed_at":"2026-08-16T13:32:03.952838Z","submitted_at":"2024-07-22T17:23:28Z","title":"Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15811","snapshot_observed_at":"2026-08-11T22:12:27.433396Z","title":"Stretching each dollar: Diffusion training from scratch on a micro-budget","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03791","last_updated":"2025-05-29T01:03:51Z","snapshot_observed_at":"2026-08-16T11:32:04.507989Z","submitted_at":"2024-12-05T01:00:07Z","title":"INRFlow: Flow Matching for INRs in Ambient Space","version":2},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-11T22:12:27.433396Z"},"links":{"cited_paper":"/paper/2407.15811","citing_paper":"/paper/2412.03791"},"observation_digest":"sha256:a2916e52a12257dd4fa1ee3bfb789150fca813227f45674e8fb8c6088119a7f0","observation_id":"04c22d13-fa8c-443f-aadb-c6957bac94e7","resolution":{"observed_at":"2026-08-11T22:12:27.433396Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15811","last_updated":"2024-07-22T17:23:28Z","snapshot_observed_at":"2026-08-16T13:32:03.952838Z","submitted_at":"2024-07-22T17:23:28Z","title":"Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15811","snapshot_observed_at":"2026-08-11T19:57:41.145038Z","title":"Stretching each dollar: Diffu- sion training from scratch on a micro-budget","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.06248","last_updated":"2024-12-09T06:47:29Z","snapshot_observed_at":"2026-08-16T11:07:15.346366Z","submitted_at":"2024-12-09T06:47:29Z","title":"Rendering-Refined Stable Diffusion for Privacy Compliant Synthetic Data","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T19:57:41.145038Z"},"links":{"cited_paper":"/paper/2407.15811","citing_paper":"/paper/2412.06248"},"observation_digest":"sha256:0707f937ea16b75d25dbdcc28cbce46578709b273556c95efc1731661228fb0d","observation_id":"b6d763c1-2426-4e01-8c40-caefe13079fc","resolution":{"observed_at":"2026-08-11T19:57:41.145038Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15811","last_updated":"2024-07-22T17:23:28Z","snapshot_observed_at":"2026-08-16T13:32:03.952838Z","submitted_at":"2024-07-22T17:23:28Z","title":"Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15811","snapshot_observed_at":"2026-08-10T21:17:58.423660Z","title":"Stretching each dollar: Diffu- sion training from scratch on a micro-budget","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.05450","last_updated":"2025-01-10T18:58:11Z","snapshot_observed_at":"2026-08-13T02:56:56.761377Z","submitted_at":"2025-01-09T18:59:56Z","title":"Decentralized Diffusion Models","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T21:17:58.423660Z"},"links":{"cited_paper":"/paper/2407.15811","citing_paper":"/paper/2501.05450"},"observation_digest":"sha256:52aa84b0b0ea54f48c724ab6728e1cc8ad3876c4ad49bdccb54487fe42cd90b8","observation_id":"7ca19343-6976-4a12-b702-43d017bb12e7","resolution":{"observed_at":"2026-08-10T21:17:58.423660Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15811","last_updated":"2024-07-22T17:23:28Z","snapshot_observed_at":"2026-08-16T13:32:03.952838Z","submitted_at":"2024-07-22T17:23:28Z","title":"Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15811","snapshot_observed_at":"2026-08-15T21:21:22.475887Z","title":"Stretching each dol- lar: Diffusion training from scratch on a micro-budget","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.10046","last_updated":"2025-05-15T07:43:23Z","snapshot_observed_at":"2026-08-16T10:46:43.017879Z","submitted_at":"2025-05-15T07:43:23Z","title":"Exploring the Deep Fusion of Large Language Models and Diffusion Transformers for Text-to-Image Synthesis","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T21:21:22.475887Z"},"links":{"cited_paper":"/paper/2407.15811","citing_paper":"/paper/2505.10046"},"observation_digest":"sha256:438e80131fc960689a1b32b8049bc3cfc684efddd7d1ddae9a2606f58c78af67","observation_id":"770ff9e0-87c8-4cb8-9e05-40f25708c8ea","resolution":{"observed_at":"2026-08-15T21:21:22.475887Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15811","last_updated":"2024-07-22T17:23:28Z","snapshot_observed_at":"2026-08-16T13:32:03.952838Z","submitted_at":"2024-07-22T17:23:28Z","title":"Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget","version":1},"cited_work":{"arxiv_id":"2407.15811","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.15811","snapshot_observed_at":"2026-08-07T05:01:17.254510Z","title":"Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget","venue":"cs.CV","work_id":"3060c01b-0a06-4fda-8718-c8e1b25bc11b","year":2024},"citing_paper":{"arxiv_id":"2506.10038","last_updated":"2025-06-10T22:37:39Z","snapshot_observed_at":"2026-08-09T04:36:51.228004Z","submitted_at":"2025-06-10T22:37:39Z","title":"Ambient Diffusion Omni: Training Good Models with Bad Data","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T05:01:15.916702Z"},"links":{"cited_paper":"/paper/2407.15811","citing_paper":"/paper/2506.10038"},"observation_digest":"sha256:8128b4bf98dd40b667a43cae7d76e79ac872e31a4908f6409530078275377e18","observation_id":"2c1897b4-702a-4652-92d0-a8ad957d8d88","resolution":{"observed_at":"2026-08-07T05:01:17.330220Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15811","last_updated":"2024-07-22T17:23:28Z","snapshot_observed_at":"2026-08-16T13:32:03.952838Z","submitted_at":"2024-07-22T17:23:28Z","title":"Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15811","snapshot_observed_at":"2026-08-03T12:50:59.050999Z","title":"Stretching each dollar: Diffu- sion training from scratch on a micro-budget.arXiv preprint arXiv:2407.15811, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.01608","last_updated":"2026-05-26T14:50:02Z","snapshot_observed_at":"2026-08-14T12:49:28.468056Z","submitted_at":"2026-01-04T17:18:27Z","title":"Guiding Token-Sparse Diffusion Models","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-03T12:50:59.050999Z"},"links":{"cited_paper":"/paper/2407.15811","citing_paper":"/paper/2601.01608"},"observation_digest":"sha256:fb9c746a084013573380b526cf24a26b07d044f01cfc3b653fcb7873abdce371","observation_id":"1d40ae68-99c5-446e-9f29-4215fa0d2b9a","resolution":{"observed_at":"2026-08-03T12:50:59.050999Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2407.15811/citation-record","integrity":"/paper/2407.15811/integrity","json":"/paper/2407.15811/citation-record.json","paper":"/paper/2407.15811"},"outbound":[],"paper":{"arxiv_id":"2407.15811","last_updated":"2024-07-22T17:23:28Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T13:32:03.952838Z","submitted_at":"2024-07-22T17:23:28Z","title":"Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2407.15811."}