{"as_of":"2026-08-08T05:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5830f909dc242921ec4ec1b0174a0344f3e3e9d1455f272094336a05845214cc","coverage":[{"denominator":6,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:57:55.667868Z","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":"2026-08-07T06:34:17.273281+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/2507.04300/citation-record","integrity":"/paper/2507.04300/integrity","json":"/paper/2507.04300/citation-record.json","paper":"/paper/2507.04300"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:57:55.856549Z","title":"Locating and editing factual associations in gpt","venue":null,"work_id":"6a781723-aab4-41f8-b30f-e344df23e561","year":2022},"citing_paper":{"arxiv_id":"2507.04300","last_updated":"2025-07-06T08:56:41Z","snapshot_observed_at":"2026-08-06T19:48:33.873827Z","submitted_at":"2025-07-06T08:56:41Z","title":"QF: Quick Feedforward AI Model Training without Gradient Back Propagation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:57:55.268989Z"},"links":{"citing_paper":"/paper/2507.04300"},"observation_digest":"sha256:25b410199011732562c7207ff3b1688fe0c0f850f2bdf45915cf8615698e82ed","observation_id":"b47e0bc8-ffa5-4a02-82ad-a492d986219b","resolution":{"observed_at":"2026-08-06T19:57:55.905475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08696","last_updated":"2022-03-10T02:28:59Z","snapshot_observed_at":"2026-08-05T12:39:09.493409Z","submitted_at":"2021-04-18T03:38:26Z","title":"Knowledge Neurons in Pretrained Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08696","snapshot_observed_at":"2026-08-06T19:57:55.322574Z","title":"Knowledge neurons in pretrained transformers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.04300","last_updated":"2025-07-06T08:56:41Z","snapshot_observed_at":"2026-08-06T19:48:33.873827Z","submitted_at":"2025-07-06T08:56:41Z","title":"QF: Quick Feedforward AI Model Training without Gradient Back Propagation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:57:55.322574Z"},"links":{"cited_paper":"/paper/2104.08696","citing_paper":"/paper/2507.04300"},"observation_digest":"sha256:bfaa35787a4b9ed6b0c4660636e83e2f4a5374fd75939b05af169d4cc193a087","observation_id":"5b74a649-33b4-4b3c-a370-b2692a9d0bf9","resolution":{"observed_at":"2026-08-06T19:57:55.322574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08164","last_updated":"2021-09-08T20:44:44Z","snapshot_observed_at":"2026-08-07T07:18:37.623241Z","submitted_at":"2021-04-16T15:24:42Z","title":"Editing Factual Knowledge in Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08164","snapshot_observed_at":"2026-08-06T19:57:55.387085Z","title":"Editing factual knowledge in language models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.04300","last_updated":"2025-07-06T08:56:41Z","snapshot_observed_at":"2026-08-06T19:48:33.873827Z","submitted_at":"2025-07-06T08:56:41Z","title":"QF: Quick Feedforward AI Model Training without Gradient Back Propagation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:57:55.387085Z"},"links":{"cited_paper":"/paper/2104.08164","citing_paper":"/paper/2507.04300"},"observation_digest":"sha256:ccaa6595da4376df9bb0826bfc56d895a007049dd89340a270ae0428cc012166","observation_id":"cbe50de7-ea2b-4f0c-a61f-12b706c19001","resolution":{"observed_at":"2026-08-06T19:57:55.387085Z","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":"2026-08-06T19:57:55.505644Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.04300","last_updated":"2025-07-06T08:56:41Z","snapshot_observed_at":"2026-08-06T19:48:33.873827Z","submitted_at":"2025-07-06T08:56:41Z","title":"QF: Quick Feedforward AI Model Training without Gradient Back Propagation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:57:55.505644Z"},"links":{"citing_paper":"/paper/2507.04300"},"observation_digest":"sha256:27bcbd56e9450177e9e279d23b40ecdf10983efd2f702c750f0e665f846d12e0","observation_id":"7be7bbc1-482e-46a9-a25d-b9cd173e80af","resolution":{"observed_at":"2026-08-06T19:57:55.505644Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-06T19:57:55.598885Z","title":"Qwen2 technical report","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04300","last_updated":"2025-07-06T08:56:41Z","snapshot_observed_at":"2026-08-06T19:48:33.873827Z","submitted_at":"2025-07-06T08:56:41Z","title":"QF: Quick Feedforward AI Model Training without Gradient Back Propagation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:57:55.598885Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2507.04300"},"observation_digest":"sha256:3d6c57012d1dbdcaccf743883af832c7e1d7813bfae173d8aa9efae1c31f268c","observation_id":"c94d623f-8146-4d53-892e-114842cf8307","resolution":{"observed_at":"2026-08-06T19:57:55.598885Z","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":"2026-08-06T19:57:55.667868Z","title":"Deep learning","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.04300","last_updated":"2025-07-06T08:56:41Z","snapshot_observed_at":"2026-08-06T19:48:33.873827Z","submitted_at":"2025-07-06T08:56:41Z","title":"QF: Quick Feedforward AI Model Training without Gradient Back Propagation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:57:55.667868Z"},"links":{"citing_paper":"/paper/2507.04300"},"observation_digest":"sha256:780e2279ec711e366aef06cbd4b3c464df684e7aef7e24ccc276497f89e7d0a9","observation_id":"473d76c7-1860-4aa0-b232-1d3f659c68aa","resolution":{"observed_at":"2026-08-06T19:57:55.667868Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.04300","last_updated":"2025-07-06T08:56:41Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T19:48:33.873827Z","submitted_at":"2025-07-06T08:56:41Z","title":"QF: Quick Feedforward AI Model Training without Gradient Back Propagation"},"reference_resolution":{"displayed":6,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":0,"verified_fuzzy":1},"total_outbound_references":6},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 0 inbound Pith citation observations for arXiv:2507.04300."}