{"as_of":"2026-08-09T05:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f3050110ccfd7bb377dff18a9ac65ac614e558ac2e62c147fe72b2a0b868622c","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":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":12,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:38:16.960316Z","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":"2026-07-04T20:30:07.618721Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":"2310.02244","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-07-04T20:30:07.618721Z","title":"arXiv:2310.02244 , year=","venue":null,"work_id":"0fd5a41b-417e-42b2-9095-845ee77a0305","year":2024},"citing_paper":{"arxiv_id":"2404.06395","last_updated":"2024-06-03T08:54:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-04-09T15:36:50Z","title":"MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-13T18:00:53.389420Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2404.06395"},"observation_digest":"sha256:6c9c8318f130423e5a0d1f64444b4bd8cebb94b124296208c6a3a47a70761dc2","observation_id":"4c706d38-bffc-4f2f-b8bd-2735c200193c","resolution":{"observed_at":"2026-05-13T18:00:53.495472Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-08-06T19:38:16.960316Z","title":"Tensor programs vi: Feature learning in infinite-depth neural networks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.05566","last_updated":"2025-07-08T01:11:30Z","snapshot_observed_at":"2026-08-08T16:17:52.381589Z","submitted_at":"2025-07-08T01:11:30Z","title":"SingLoRA: Low Rank Adaptation Using a Single Matrix","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T19:38:16.960316Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2507.05566"},"observation_digest":"sha256:a79f5c1c5512350353d920617471b99d7e2f9fc97fd0c1cf1e88a5e4ac6439aa","observation_id":"902f8844-e176-4fce-ad62-704af23d6f40","resolution":{"observed_at":"2026-08-06T19:38:16.960316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-08-06T17:56:44.143579Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.10613","last_updated":"2025-07-13T15:15:24Z","snapshot_observed_at":"2026-08-08T22:32:30.066463Z","submitted_at":"2025-07-13T15:15:24Z","title":"Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-06T17:56:44.143579Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2507.10613"},"observation_digest":"sha256:71dd728bfcea119b32ccaf34333e43d52d2853b83b4d071e091e72dffc16b097","observation_id":"107d6887-7ae2-4a9e-bec6-70f8aee2ef48","resolution":{"observed_at":"2026-08-06T17:56:44.143579Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-08-06T11:44:05.211741Z","title":"Tensor programs vi: Feature learning in infinite-depth neural networks, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.22448","last_updated":"2025-07-30T07:55:33Z","snapshot_observed_at":"2026-08-06T11:43:58.532083Z","submitted_at":"2025-07-30T07:55:33Z","title":"Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance","version":1},"reference_index":118,"source":"arxiv_source","source_observed_at":"2026-08-06T11:44:05.211741Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2507.22448"},"observation_digest":"sha256:e6092e3be79dc4986a6f452346ba2e7e07021a0aff38d8f2df2b8f97c1dd497b","observation_id":"abc3c35c-811b-4b2d-9a84-c1e0bec61442","resolution":{"observed_at":"2026-08-06T11:44:05.211741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":"2310.02244","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-07-04T20:30:07.618721Z","title":"arXiv:2310.02244 , year=","venue":null,"work_id":"0fd5a41b-417e-42b2-9095-845ee77a0305","year":2024},"citing_paper":{"arxiv_id":"2604.21691","last_updated":"2026-04-23T13:58:12Z","snapshot_observed_at":"2026-08-02T12:48:50.592713Z","submitted_at":"2026-04-23T13:58:12Z","title":"There Will Be a Scientific Theory of Deep Learning","version":1},"reference_index":94,"source":"arxiv_source","source_observed_at":"2026-05-09T20:11:17.616190Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2604.21691"},"observation_digest":"sha256:ae17ad77b495e4fa3dc37fa3c3d0f142c7bf5377f52b3abf3ff476ca4734d1f7","observation_id":"3a04f458-6a3a-4a6b-bf76-703cf6543861","resolution":{"observed_at":"2026-05-11T15:21:09.150893Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":"2310.02244","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-07-04T20:30:07.618721Z","title":"arXiv:2310.02244 , year=","venue":null,"work_id":"0fd5a41b-417e-42b2-9095-845ee77a0305","year":2024},"citing_paper":{"arxiv_id":"2605.07815","last_updated":"2026-05-08T14:47:56Z","snapshot_observed_at":"2026-07-06T23:20:11.042952Z","submitted_at":"2026-05-08T14:47:56Z","title":"OrScale: Orthogonalised Optimization with Layer-Wise Trust-Ratio Scaling","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-11T02:47:08.766380Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2605.07815"},"observation_digest":"sha256:fb87944412c67b97dcd1c920a1c9e49c961b41ff119fc4a16badd7f2d1154ece","observation_id":"0af56707-e610-460f-9ee0-198ac4b29270","resolution":{"observed_at":"2026-05-11T03:05:55.506654Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":"2310.02244","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-07-04T20:30:07.618721Z","title":"arXiv:2310.02244 , year=","venue":null,"work_id":"0fd5a41b-417e-42b2-9095-845ee77a0305","year":2024},"citing_paper":{"arxiv_id":"2605.14200","last_updated":"2026-05-13T23:32:00Z","snapshot_observed_at":"2026-07-06T23:25:39.415637Z","submitted_at":"2026-05-13T23:32:00Z","title":"How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization","version":1},"reference_index":114,"source":"arxiv_source","source_observed_at":"2026-05-15T04:45:20.091598Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2605.14200"},"observation_digest":"sha256:954a4b4080745cc68c877cb63d487504c3ac9161c390adf0a693bdcd592af6d7","observation_id":"821d2fe6-a39f-4046-8209-a0b0731b2d3c","resolution":{"observed_at":"2026-05-15T04:49:44.894754Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":"2310.02244","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-07-04T20:30:07.618721Z","title":"arXiv:2310.02244 , year=","venue":null,"work_id":"0fd5a41b-417e-42b2-9095-845ee77a0305","year":2024},"citing_paper":{"arxiv_id":"2606.05610","last_updated":"2026-06-04T02:32:11Z","snapshot_observed_at":"2026-07-06T23:45:33.157370Z","submitted_at":"2026-06-04T02:32:11Z","title":"Predictable Scaling Laws of Optimal Hyperparameters for LLM Continued Pre-training","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-06-28T01:53:04.715108Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2606.05610"},"observation_digest":"sha256:8d37750b905e6a01c6ab143a2110fb960f3269cdb23de8465cdf2c8666e59c70","observation_id":"d2d0464d-499f-43a4-90c6-7343b27f61b9","resolution":{"observed_at":"2026-07-02T12:46:56.723544Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":"2310.02244","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-07-04T20:30:07.618721Z","title":"arXiv:2310.02244 , year=","venue":null,"work_id":"0fd5a41b-417e-42b2-9095-845ee77a0305","year":2024},"citing_paper":{"arxiv_id":"2606.25971","last_updated":"2026-07-17T13:42:08Z","snapshot_observed_at":"2026-08-02T10:13:56.529128Z","submitted_at":"2026-06-24T15:40:26Z","title":"Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-06-25T20:05:09.179627Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2606.25971"},"observation_digest":"sha256:c437195a298f50d1b403223a63d6f3c325b8e91085aa1898d3fd375b1f793059","observation_id":"9289830a-a35b-4792-ab8a-c0a5642b785c","resolution":{"observed_at":"2026-07-04T20:30:07.620284Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-08-02T10:14:13.056533Z","title":"Tensor programs VI : Feature learning in infinite-depth neural networks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.25971","last_updated":"2026-07-17T13:42:08Z","snapshot_observed_at":"2026-08-02T10:13:56.529128Z","submitted_at":"2026-06-24T15:40:26Z","title":"Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors","version":2},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-02T10:14:13.056533Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2606.25971"},"observation_digest":"sha256:420576662982d3a5cd53137d56f643c000371b19f1285b5676aa2ff0f50a3e35","observation_id":"afdf5d92-3aad-43d7-98bc-10132918a436","resolution":{"observed_at":"2026-08-02T10:14:13.056533Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-08-02T05:05:25.727834Z","title":"Tensor programs vi: Feature learning in infinite-depth neural networks.arXiv preprint arXiv:2310.02244, 2023a","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2607.13491","last_updated":"2026-07-15T06:37:05Z","snapshot_observed_at":"2026-08-06T10:33:55.264647Z","submitted_at":"2026-07-15T06:37:05Z","title":"DeepLoop: Depth Scaling for Looped Transformers","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T05:05:25.727834Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2607.13491"},"observation_digest":"sha256:d0d09c3b96d0201717b0504b1068c070f1528c3655821f5da44c8ab9c61d4dd2","observation_id":"43a20b59-8207-448e-8146-886ab29ac9f2","resolution":{"observed_at":"2026-08-02T05:05:25.727834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02244","snapshot_observed_at":"2026-07-30T12:53:41.186767Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23777","last_updated":"2026-07-26T17:55:40Z","snapshot_observed_at":"2026-07-30T23:56:43.497541Z","submitted_at":"2026-07-26T17:55:40Z","title":"Scale Weight Decay and Train Better","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-07-30T12:53:41.186767Z"},"links":{"cited_paper":"/paper/2310.02244","citing_paper":"/paper/2607.23777"},"observation_digest":"sha256:25badb0aa1fe3fb5f9349fcff92b376137b9d941e2756ca42ecd2bed7800d5ac","observation_id":"1e09b8ad-c1b1-4069-adca-33ab7def3d1a","resolution":{"observed_at":"2026-07-30T12:53:41.186767Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2310.02244/citation-record","integrity":"/paper/2310.02244/integrity","json":"/paper/2310.02244/citation-record.json","paper":"/paper/2310.02244"},"outbound":[],"paper":{"arxiv_id":"2310.02244","last_updated":"2023-10-12T17:50:31Z","latest_version":5,"primary_category":"cs.NE","snapshot_observed_at":"2026-08-06T03:52:25.161270Z","submitted_at":"2023-10-03T17:50:40Z","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2310.02244."}