{"as_of":"2026-08-09T17:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:14c41e95e6d77f950e63f0f3464a4fc3b8350f9e853b1d45c84d105ec8086f61","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":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":15,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:26:30.960292Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":52,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-07T00:26:30.960292Z","title":"Formal algorithms for transformers","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.14095","last_updated":"2025-06-18T12:59:54Z","snapshot_observed_at":"2026-08-08T23:56:37.973506Z","submitted_at":"2025-06-17T01:19:28Z","title":"Transformers Learn Faster with Semantic Focus","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T00:26:30.960292Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2506.14095"},"observation_digest":"sha256:418c794b81e16786433e7de53bf8d734e1d784337f6634009e1692d891e2e47e","observation_id":"9bb6606d-3f55-472b-a431-4d0742abc47c","resolution":{"observed_at":"2026-08-07T00:26:30.960292Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-06T16:19:51.668567Z","title":"Formal algorithms for transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.13858","last_updated":"2025-07-18T12:23:47Z","snapshot_observed_at":"2026-08-08T06:10:45.567459Z","submitted_at":"2025-07-18T12:23:47Z","title":"InTraVisTo: Inside Transformer Visualisation Tool","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T16:19:51.668567Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2507.13858"},"observation_digest":"sha256:63bf5cd9e326d4f689b13b5bc4a6f71f277f7ca43fc906dfa5d8030b5b43cbf5","observation_id":"825c8457-34c1-4bfb-994d-802134064ad8","resolution":{"observed_at":"2026-08-06T16:19:51.668567Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T15:19:33.843685Z","title":"Formal algorithms for transformers","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.20211","last_updated":"2025-08-27T18:37:55Z","snapshot_observed_at":"2026-08-08T01:26:25.373803Z","submitted_at":"2025-08-27T18:37:55Z","title":"What can we learn from signals and systems in a transformer? Insights for probabilistic modeling and inference architecture","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-05T15:19:33.843685Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2508.20211"},"observation_digest":"sha256:ef192cec3351bdae05818bbc70f345975b7931ad3c3830ee0c563736c81f9a62","observation_id":"b0562e88-4f4c-41c1-a8ec-3a2a58c086d5","resolution":{"observed_at":"2026-08-05T15:19:33.843685Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T14:28:41.728152Z","title":"Formal Algorithms for Transformers","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.21307","last_updated":"2025-08-29T02:08:36Z","snapshot_observed_at":"2026-08-07T20:23:24.689358Z","submitted_at":"2025-08-29T02:08:36Z","title":"MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T14:28:41.728152Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2508.21307"},"observation_digest":"sha256:cc1c4e62b402e167e7eefb052efe16b35e80e3e34ccbf84963c892e3808350e8","observation_id":"7fe056e8-ef95-44aa-8dff-ac2ef6b47d35","resolution":{"observed_at":"2026-08-05T14:28:41.728152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T12:22:09.858106Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.01679","last_updated":"2025-09-01T18:01:23Z","snapshot_observed_at":"2026-08-08T20:47:34.034449Z","submitted_at":"2025-09-01T18:01:23Z","title":"Efficient Transformer-Inspired Variants of Physics-Informed Deep Operator Networks","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T12:22:09.858106Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2509.01679"},"observation_digest":"sha256:3f1c1d5cdda6c9e4d9cb750602248893a7c77a931d3cfd66d846745811c3a3f7","observation_id":"ca26beda-9e7c-4d77-b478-458d93057bf7","resolution":{"observed_at":"2026-08-05T12:22:09.858106Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":"2207.09238","doi":"10.48550/arxiv.2207.09238","metadata_source":"arxiv_reference","pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Formal algorithms for transformers","venue":"arXiv (Cornell University)","work_id":"73b6b145-5235-439c-a424-f025332d4243","year":2022},"citing_paper":{"arxiv_id":"2604.07242","last_updated":"2026-04-18T18:29:17Z","snapshot_observed_at":"2026-08-02T14:12:00.409303Z","submitted_at":"2026-04-08T16:07:15Z","title":"Weaves, Wires, and Morphisms: Formalizing and Implementing the Algebra of Deep Learning","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T18:48:29.607354Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2604.07242"},"observation_digest":"sha256:dd29740ab6b0705c26371bef6aa9db82396ce06727cb659565820e9bbb5f3d88","observation_id":"b31eb78f-2480-4abe-aca7-4671c5fad3a7","resolution":{"observed_at":"2026-05-10T23:55:50.615737Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":"2207.09238","doi":"10.48550/arxiv.2207.09238","metadata_source":"arxiv_reference","pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Formal algorithms for transformers","venue":"arXiv (Cornell University)","work_id":"73b6b145-5235-439c-a424-f025332d4243","year":2022},"citing_paper":{"arxiv_id":"2605.02300","last_updated":"2026-05-04T07:48:02Z","snapshot_observed_at":"2026-07-06T23:15:23.301944Z","submitted_at":"2026-05-04T07:48:02Z","title":"A Meta Reinforcement Learning Approach to Goals-Based Wealth Management","version":1},"reference_index":266,"source":"arxiv_source","source_observed_at":"2026-05-08T18:42:50.962120Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2605.02300"},"observation_digest":"sha256:4d716a371f2f9ec53487596c09a367cf305bc606862e40d7811bf7f6a79b3279","observation_id":"c4768815-2771-483a-a35b-4a56947d8c22","resolution":{"observed_at":"2026-05-08T18:44:01.796452Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":"2207.09238","doi":"10.48550/arxiv.2207.09238","metadata_source":"arxiv_reference","pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Formal algorithms for transformers","venue":"arXiv (Cornell University)","work_id":"73b6b145-5235-439c-a424-f025332d4243","year":2022},"citing_paper":{"arxiv_id":"2605.06394","last_updated":"2026-05-07T15:08:49Z","snapshot_observed_at":"2026-07-06T23:18:51.157048Z","submitted_at":"2026-05-07T15:08:49Z","title":"Lecture Notes on Statistical Physics and Neural Networks","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-08T03:24:06.282053Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2605.06394"},"observation_digest":"sha256:eae1298bb7bc02a8b91e2d646e6574deab8005588d4898d94022ba0d7e62d63d","observation_id":"c8c5f7f6-0a56-42f7-8737-89095e6eb4d1","resolution":{"observed_at":"2026-05-11T22:06:24.974809Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":"2207.09238","doi":"10.48550/arxiv.2207.09238","metadata_source":"arxiv_reference","pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Formal algorithms for transformers","venue":"arXiv (Cornell University)","work_id":"73b6b145-5235-439c-a424-f025332d4243","year":2022},"citing_paper":{"arxiv_id":"2605.08679","last_updated":"2026-05-09T04:33:14Z","snapshot_observed_at":"2026-08-02T13:27:25.888990Z","submitted_at":"2026-05-09T04:33:14Z","title":"Attention-based graph neural networks: a survey","version":1},"reference_index":178,"source":"arxiv_source","source_observed_at":"2026-05-12T01:07:43.805485Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2605.08679"},"observation_digest":"sha256:f4cbbec80a13a96d2e11d9c48b2c94a8a89eb44bea6785169cec596935ece862","observation_id":"675fc558-c130-47fe-9485-c188132a2f1a","resolution":{"observed_at":"2026-05-12T08:26:24.910970Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":"2207.09238","doi":"10.48550/arxiv.2207.09238","metadata_source":"arxiv_reference","pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Formal algorithms for transformers","venue":"arXiv (Cornell University)","work_id":"73b6b145-5235-439c-a424-f025332d4243","year":2022},"citing_paper":{"arxiv_id":"2605.15092","last_updated":"2026-05-14T17:12:22Z","snapshot_observed_at":"2026-08-03T01:01:17.589865Z","submitted_at":"2026-05-14T17:12:22Z","title":"Monetary Policy in the Media Spotlight: Sentiments, Signals, and Economic Impact","version":1},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-05-15T02:58:27.599800Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2605.15092"},"observation_digest":"sha256:f41a165fe8fa98e3d4c0900fcdbed5eed75eaff119a41c29a07f8cb3e10763f5","observation_id":"ecfbf3dd-7f04-4023-aabf-6fc9c1e848b0","resolution":{"observed_at":"2026-05-15T02:58:33.865028Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":"2207.09238","doi":"10.48550/arxiv.2207.09238","metadata_source":"arxiv_reference","pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Formal algorithms for transformers","venue":"arXiv (Cornell University)","work_id":"73b6b145-5235-439c-a424-f025332d4243","year":2022},"citing_paper":{"arxiv_id":"2605.15608","last_updated":"2026-05-15T04:42:19Z","snapshot_observed_at":"2026-07-06T23:26:51.110846Z","submitted_at":"2026-05-15T04:42:19Z","title":"Transformer-like Inference from Optimal Control","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-20T21:23:54.074370Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2605.15608"},"observation_digest":"sha256:cde66878856f5f295a0e076ab8cd30a91eb46a3b63bd4f652b105c8c6d8c16e1","observation_id":"b2dda6a9-3318-49e7-83e7-e22d54b0c57f","resolution":{"observed_at":"2026-05-20T21:24:03.137173Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":"2207.09238","doi":"10.48550/arxiv.2207.09238","metadata_source":"arxiv_reference","pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Formal algorithms for transformers","venue":"arXiv (Cornell University)","work_id":"73b6b145-5235-439c-a424-f025332d4243","year":2022},"citing_paper":{"arxiv_id":"2605.18281","last_updated":"2026-05-18T12:12:16Z","snapshot_observed_at":"2026-07-06T23:29:09.538843Z","submitted_at":"2026-05-18T12:12:16Z","title":"Temporal Task Diversity: Inductive Biases Under Non-Stationarity in Synthetic Sequence Modelling","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-05-20T12:32:05.391155Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2605.18281"},"observation_digest":"sha256:9a5777f3faee2caf213cc7277d7714cb7f4c7c754871575752a98ef13623f92f","observation_id":"54335c96-d5d0-48c7-af8f-5ba762c0d32d","resolution":{"observed_at":"2026-05-20T12:33:16.820776Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":"2207.09238","doi":"10.48550/arxiv.2207.09238","metadata_source":"arxiv_reference","pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Formal algorithms for transformers","venue":"arXiv (Cornell University)","work_id":"73b6b145-5235-439c-a424-f025332d4243","year":2022},"citing_paper":{"arxiv_id":"2605.25085","last_updated":"2026-06-07T06:58:29Z","snapshot_observed_at":"2026-07-06T23:35:06.733347Z","submitted_at":"2026-05-24T13:54:13Z","title":"Polynomial Context-Truncation Sensitivity in Autoregressive Language Models: Sequential Wyner-Ziv Bounds for KV Cache Compression","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-06-29T23:46:44.498959Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2605.25085"},"observation_digest":"sha256:94de8290e2d0014aa7326adcea550df110e192064d587edb73c0847ed345f158","observation_id":"6265a17e-d8ce-4373-b3b0-3803e4a987d6","resolution":{"observed_at":"2026-06-30T00:04:06.984022Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":"2207.09238","doi":"10.48550/arxiv.2207.09238","metadata_source":"arxiv_reference","pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Formal algorithms for transformers","venue":"arXiv (Cornell University)","work_id":"73b6b145-5235-439c-a424-f025332d4243","year":2022},"citing_paper":{"arxiv_id":"2606.19993","last_updated":"2026-06-18T09:31:31Z","snapshot_observed_at":"2026-08-07T06:04:20.969024Z","submitted_at":"2026-06-18T09:31:31Z","title":"Activation- and Influence-Aware Ranks (AIR): Function-Preserving SVD Compression for LLMs","version":1},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-06-26T18:09:17.414031Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2606.19993"},"observation_digest":"sha256:659b87ac9ab73ff1fae75844c9e5ca9f78718d2ded96cadde8e54aa990a09ff9","observation_id":"a61d3b5c-5bee-4b11-86fb-805967c1fb01","resolution":{"observed_at":"2026-07-04T03:19:31.582322Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.09238","snapshot_observed_at":"2026-07-14T06:16:09.070414Z","title":"arXiv preprint arXiv:2207.09238 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.11211","last_updated":"2026-07-13T08:02:26Z","snapshot_observed_at":"2026-08-06T02:13:21.548625Z","submitted_at":"2026-07-13T08:02:26Z","title":"FastTPS: An Optimized Method for LLM Token Phase for AI accelerators","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-07-14T06:16:09.070414Z"},"links":{"cited_paper":"/paper/2207.09238","citing_paper":"/paper/2607.11211"},"observation_digest":"sha256:4566ef24aa253ed1b3394a1ec47c8523b5f5dc6d52d5318b1c70f67ae6696512","observation_id":"15aaff54-fe31-46c7-a987-dba11f36399a","resolution":{"observed_at":"2026-07-14T06:16:09.070414Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2207.09238/citation-record","integrity":"/paper/2207.09238/integrity","json":"/paper/2207.09238/citation-record.json","paper":"/paper/2207.09238"},"outbound":[],"paper":{"arxiv_id":"2207.09238","last_updated":"2022-07-19T12:49:02Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T01:24:23.937372Z","submitted_at":"2022-07-19T12:49:02Z","title":"Formal Algorithms for Transformers"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2207.09238."}